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2025-04-09 16:14:38
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b931295d-02ae-4afe-b239-bc3773e2cb3c
|
completed
| 2025-04-09T16:14:38.079819
| 2025-05-26T08:51:47.460413
|
470e6330-b694-43af-be0d-44310676f8f5
|
Electric vehicles (EVs) are being endorsed as the uppermost successor to fuel-powered cars, with timetables for banning the sale of petrol-fueled vehicles announced in many countries. However, the range and charging times of EVs are still considerable concerns. Fast charging could be a solution to consumers' range anxiety and the acceptance of EVs. Nevertheless, it is a complicated and systematized challenge to realize the fast charging of EVs because it includes the coordinated development of battery cells, including electrode materials, EV battery power systems, charging piles, electric grids, etc. This paper aims to serve as an analysis for the development of fast-charging technology, with a discussion of the current situation, constraints and development direction of EV fast-charging technologies from the macroscale and microscale perspectives of fast-charging challenges. It is emphasized that to essentially solve the problem of fast charging, the development of new battery materials, especially anode materials with improved lithium ion diffusion coefficients, is the key. It is highlighted that red phosphorus is the most promising anode that can simultaneously satisfy the double standards of high-energy density and fast-charging performance to a maximum degree.
|
<li> <b>Electric vehicles (EVs):</b> Car<li> <b>cars:</b> Car<li> <b>vehicles:</b> Other Vehicle<li> <b>EVs:</b> Car<li> <b>EV:</b> Car
|
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bd88a758-af2b-4a48-a9ee-6c72eb64dc9b
|
completed
| 2025-04-09T16:14:38.079838
| 2025-05-13T06:20:24.916872
|
705d7a53-5326-4c48-a0cb-d9040b99821e
|
In this paper, we propose a trajectory tracking controller with experimental verification for torpedo-like autonomous underwater vehicles (AUVs) with underactuation characteristics. The proposed controller overcomes the underactuation problem by designing the desired error dynamics in a coupled form using state variables in body-fixed and world coordinates. Unlike the back-stepping control requiring high-order derivatives of state variables, the proposed controller only requires the first derivatives of the states, which can alleviate noise magnification issues due to differentiation. We adopt time delay estimation to estimate the dynamics indirectly using control inputs and vehicle outputs, making the proposed controller relatively easy to apply without requiring the all of the vehicle dynamics. We also address some practical issues that commonly arise in experimental environments: handling measurement noises and actuation limits. To mitigate the effects of noise on the controller, a filtering technique using a moving window average is employed. Additionally, to account for the actuation limits, we design an anti-windup structure that takes into consideration the nonlinearity between the thrusting force and rotating speed of the thruster. We verify the tracking performance of the proposed controller through experimentation using an AUV. The experimental results show that the 3D motion control of the proposed controller exhibits an RMS error of 0.3216 m and demonstrate that the proposed controller achieves accurate tracking performance, making it suitable for survey missions that require tracking errors of less than one meter.
|
<li> <b>autonomous underwater vehicles (AUVs):</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>AUV:</b> Other Vehicle
|
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"We do not deal with underwater vehicles"
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4d852154-dccf-420e-a399-27710d6e79fd
|
completed
| 2025-04-09T16:14:38.079845
| 2025-05-26T13:58:02.644003
|
f83ba31b-fd4e-4304-a257-be8428b4210d
|
The tracking performance of the proposed controller was experimentally verified using the AUV platform depicted in Figure 2. The experiments were performed in the seawater at a port located in the South Sea of Korea.For the experiment, the control gains were set as follows.The inertial gains were set to m u = 3000, m q = 0.7, m r = 1.0, α u = 1.0, α ψ = 1.5, α θ = 1.5, and α r = 1.5 by tuning, and the feedback gains K x = 1.0,K u = 2.0, K y = 0.216, K ψ = 1.08,K r = 1.8,K z = 0.125, K θ = 0.75, and K q = 1.5 were selected for the desired error dynamics having poles at p dx = -1.0(double poles), p dy = -0.6 (triple poles), and p dz = -0.5 (triple poles).In this case, the characteristic equations in Equations (23a)-(23c) had poles at p cx = -1.0(double poles), p cy = -0.502,-0.649 ± 0.740i, and p cz = -0.897,-0.302 ± 0.344i, which were placed in the LHP.Regarding the noise-handling algorithm in Figure 4, the window size for the average filter was set at N = 128, and the β values for h u , h q , and h r in Equation ( 18) were β u = 0.7, β q = 0.5, and β r = 0.9, respectively.
|
<li> <b>AUV platform:</b> Other Vehicle
|
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[
"submitted"
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[
{
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] | null | null |
ddfbcb3b-4798-4e24-ade9-bf230375e902
|
completed
| 2025-04-09T16:14:38.079851
| 2025-05-26T07:54:36.249314
|
8d849107-9822-48de-925a-0b5714d3f03e
|
Introduction. Organization of high-quality training of the vehicles’ drivers is possible only with the proper formation of professional skills. Moreover, the formation of the skills is necessary for the driver to control the vehicle safety, perhaps by using simulators at the initial stage of training. The use of simulators allows automating the actions that the driver performs, while not exposing the student to risks.Therefore, the purpose of the paper is to analyze the application of simulators in the training of the vehicles’ drivers.Materials and methods. The paper presented the basic psycho physiological principles of the learning process, which should be taken into account when using simulators for driver training. The authors demonstrated the classification of the car simulators used for training of drivers by the information models. Existing information models of simulators were divided into two groups: reproducing only visual information, without imitation of the vestibular and simulating both visual and vestibular information. The analysis reflected the advantages and disadvantages of information models.Results. As a result, the authors proposed two systematizing features: the view angle of the visual information and the simulation of vestibular information.Discussion and conclusions. The research is useful not only for the further science development, but also for the selection of simulators and for the organization of the educational process in driving schools.
|
<li> <b>vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>simulators:</b> Other Vehicle<li> <b>car simulators:</b> Other Vehicle
|
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6586aab7-5b09-4072-b8a7-7a4dbff2565a
|
pending
| 2025-04-09T16:14:38.079857
| 2025-04-09T16:14:38.079857
|
1af0be0f-2a13-4f4b-826f-84e8637a93ea
|
Содержание информационных моделей, используемых в симуляторах, зачастую не публикуется в известных авторам научных источниках, что не позволяет произвести оценку качества симуляторов с точки зрения адекватности навыков, формируемых при их использовании. В конструкцию тренажера с полноценным рабочим местом входит комплекс устройств, включающих водительское кресло, со всеми органами управления, средствами ото- 10 Англо-русский словарь по вычислительной технике и программированию (The English-Russian Dictionary of Computer Science) : около 55 тыс.статей.8-е изд., испр.и доп.© ABBYY, 2008; © Масловский Е.К., 2008. бражения информации и вспомогательным оборудованием, аналогичных тем, что устанавливаются на реальных автомобилях, предназначенных для осуществления деятельности водителя. Тренажеры данной группы позволяют сформировать первоначальные (моторные) навыки по управлению автомобилем и обеспечивают закрепление теоретических знаний, путем моделирования различных дорожно-транспортных ситуаций [9,10,11]. Такие тренажеры обычно состоят из трех модулей (рисунок 2): 1) модуль, с полноценным рабочим местом водителя; 1) аппаратно-программный модуль -это персональный компьютер, с программным обеспечением и устройством согласования, обеспечивающего совместную работу датчиков органов управления тренажера и компьютера; 2) визуально-акустический модуль, состоящий из монитора(ов), с помощью которых моделируется визуальная информация из акустических колонок, которые воспроизводят основные шумы, возникающие при движении автомобиля (шум обгоняемых автомобилей, визг шин при торможении и т.д.), а также акустические характеристики работы различных агрегатов и систем автомобиля (звук пуска двигателя). 1Там же. 13
|
<li> <b>симуляторов:</b> Other Vehicle<li> <b>автомобилях:</b> Car<li> <b>автомобилем:</b> Car<li> <b>датчиков:</b> Other Sensor<li> <b>автомобиля:</b> Car
|
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] | null | null |
4c7206f9-b562-44ca-889c-5a84fef9f775
|
completed
| 2025-04-09T16:14:38.079863
| 2025-05-13T06:44:01.265143
|
c2c5af4e-675c-48e7-b911-ba1ba4ac06b9
|
In the present day, it is crucial for individuals and companies to reduce their carbon footprints in a society more self-conscious about climate change and other environmental issues. In this sense, public and private institutions are investing in photovoltaic (PV) systems to produce clean energy for self-consumption. Nevertheless, an essential part of this energy is wasted due to lower consumption during non-business periods. This work proposes a novel framework that uses solar-generated energy surplus to charge external electric vehicles (EVs), creating new business opportunities. Furthermore, this paper introduces a novel marketplace platform based on blockchain technology to allow energy trading between institutions and EV owners. Since the energy provided to charge the EV comes from distributed PV generation, the energy’s selling price can be more attractive than the one offered by the retailers—meaning economic gains for the institutions and savings for the users. A case study was carried out to evaluate the feasibility of the proposed solution and its economic advantages. Given the assumptions considered in the study, 3213 EVs could be fully charged by one institution in one year, resulting in over EUR 45,000 in yearly profits. Further, the economic analysis depicts a payback of approximately two years, a net present value of EUR 33,485, and an internal rate of return of 61%. These results indicate that implementing the proposed framework could enable synergy between institutions and EV owners, providing clean and affordable energy to charge vehicles.
|
<li> <b>electric vehicles (EVs):</b> Car<li> <b>EV:</b> Car<li> <b>EVs:</b> Car<li> <b>vehicles:</b> Other Vehicle
|
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d219a9d2-4f8f-4606-9cb5-5d3080b81501
|
completed
| 2025-04-09T16:14:38.079869
| 2025-05-26T14:26:40.931435
|
3f78f4fb-39d1-40fa-a579-d42afd526bc3
|
Charger Reserved is the state where the smart contract locks a specific charger to a particular customer.If the user does not get to the charger within a predefined time window, the smart contract frees the charging point by reversing the smart contract's state to the Charger Available state via the Reject function.
|
None
|
[
[]
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"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
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[
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[
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[
null
] |
[
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] |
[
"submitted"
] |
[] | null | null |
7aceab38-6ca4-4e8e-b0f8-30aa1f1c0ed0
|
completed
| 2025-04-09T16:14:38.079875
| 2025-05-26T07:08:31.755155
|
b071cae4-55a9-4d70-8322-2dac0060a2e0
|
The strategic recovery of buoys is a critical task in executing deep-sea research missions, as nations extend their exploration of marine territories. This study primarily investigates the dynamics of remotely operated vehicle (ROV)-assisted salvage operations for floating bodies during the recovery of dynamic maritime targets. It focuses on the hydrodynamic coefficients of dual floating bodies in this salvage process. The interaction dynamics of the twin floats are examined using parameters such as the kinematic response amplitude operator (RAO), added mass, damping coefficient, and mean drift force. During the “berthing stage”, when the double floats are at Fr = 0.15–0.18, their roll and yaw Response Amplitude Operators are diminished, resulting in smoother motion. Thus, the optimal berthing speed range for this stage is Fr = 0.15–0.18. During the “side-by-side phase”, the spacing between the ROV and FLOAT under wave action should be approximately 0.4 L to 0.5 L. The coupled motion of twin floating bodies under the influence of following waves can further enhance their stability. The ideal towing speed during the “towing phase” is Fr = 0.2. This research aims to analyze the mutual influence between two floating bodies under wave action. By simulating the coupled motion of dual dynamic targets, we more precisely assess the risks and challenges inherent in salvage operations, thus providing a scientific basis for the design and optimization of salvage strategies.
|
<li> <b>remotely operated vehicle (ROV):</b> Other Vehicle<li> <b>ROV:</b> Other Vehicle<li> <b>floating bodies:</b> Other Vehicle
|
[
[]
] |
[
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[
"submitted"
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[
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] |
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[
"submitted"
] |
[
"Correct"
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[
"submitted"
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[
"\"remotely operated vehicle (ROV)\", \"ROV\" and \"floating bodies\" are not of interest for CCAM"
] |
[
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] | null | null |
2018faf4-39b6-47f2-bf71-709e01c18081
|
completed
| 2025-04-09T16:14:38.079881
| 2025-05-13T06:39:59.370762
|
808b1556-1dca-4a0f-b32b-add218041cb8
|
This article delves into the method of employing ROVs to recover floating artifacts in marine scientific research, systematically exploring the three phases: the ROV berthing towards the recovered float, attaching flexible cables at the proper locations, and pulling the salvaged float at a predetermined towing speed.The coupled dynamic response of the salvage system is investigated using the computational fluid dynamics (CFD) approach, with an emphasis on examining the motion response, added mass, damping coefficient, and average drift force hydrodynamic coefficient response of the two floating bodies.The following conclusions have been drawn: 1. Numerical simulation of single-float and double-float coupling. A single floater is less impacted by wave movement in the sway direction and exhibits smoother rolling.The motion response of a single floating body ROV in surge, heave, pitch, and yaw RAO is greater than that of an ROV with double floating body coupling.
|
<li> <b>ROVs:</b> Other Vehicle<li> <b>float:</b> Other Vehicle<li> <b>ROV:</b> Other Vehicle<li> <b>floater:</b> Other Vehicle<li> <b>floating body:</b> Other Vehicle
|
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[
"Partially correct"
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"Not interested in ROVs and submarines, thus characterized as incorrect"
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] | null | null |
973b3d0e-b7c4-4a7a-816a-05e721cab859
|
completed
| 2025-04-09T16:14:38.079887
| 2025-05-26T13:54:42.516393
|
35584337-6552-48f6-8aef-0ee68ab6c6f2
|
Understanding jellyfish ecology and roles in coastal ecosystems is challenging due to their patchy distribution. While standard net sampling or manned aircraft surveys are inefficient, Unmanned Aerial Vehicles (UAVs) or drones represent a promising alternative for data collection. In this technical report, we used pictures taken from a small drone to estimate the density of Aurelia sp. in a shallow fjord with a narrow entrance, where the population dynamic is well-known. We investigated the ability of an image processing software to count small and translucent jellyfish from the drone pictures at three locations with different environmental conditions (sun glare, waves or seagrass). Densities of Aurelia sp. estimated from semiautomated and manual counts from drone images were similar to densities estimated by netting. The semiautomated program was able to highlight the medusae from the background in order to discard false detections of items unlikely to be jellyfish. In spite of this, some objects (e.g., seagrass) were hardly distinguishable from jellyfish and resulted in a small number of false positives. This report presents a preview of the possible applications of drones to observe small and fragile jellyfishes, for which in situ sampling remains delicate. Drones may represent a noninvasive approach to monitoring jellyfish abundance over time, enabling the collection of a large amount of data in a short time. Software development may be useful for automatically measuring jellyfish size and even population biomass.
|
<li> <b>Unmanned Aerial Vehicles (UAVs):</b> Other Vehicle<li> <b>drones:</b> Other Vehicle<li> <b>drone:</b> Other Vehicle<li> <b>pictures:</b> Camera
|
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[
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[
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[
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[
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[
"Partially correct"
] |
[
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] |
[
"submitted"
] |
[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
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] | null | null |
6bf0599f-e78a-44da-b344-834cc1f51874
|
completed
| 2025-04-09T16:14:38.079893
| 2025-05-26T06:59:00.648285
|
88fcc715-0154-4554-aba6-d63666e87227
|
We performed a semiautomated counting of the Aurelia sp. on drone pictures using the EBImage package [38] in RStudio [39].All steps of the image processing with RStudio are illustrated in Figure 2. The drone pictures were first manually cropped in an area with reduced clutter (e.g., sun reflection, floating debris) to perform the jellyfish detection over a homogeneous background (Figure 2a,b).The medusae were highlighted by their gonads in the center of a round-elliptic umbrella.The cropped images were then automatically enhanced by increasing the contrast between the jellyfish and the background after the automatic selection of the best-fitting gamma correction (Figure 2c).The determination of the enhancement parameters is described in the R script available through the Pangea data depository.All elements that stand out from the background were segmented using an adaptive threshold for the different regions of the pictures that corrected for local changes in brightness (Figure 2d).The picture was then cleaned by discarding all elements with a size below 5 pixels and a nonround shape that were unlikely to be jellyfish (Figure 2e).The algorithm treated the greyscale images as a topographic relief to differentiate individuals very close to each other, comparing the intensity of pixels with their neighbors and applying a unique color to each individual.All image transformations enabled the software to automatically count the total number of jellyfish in each picture.The mean number of jellyfish, with a 95% confidence interval, was calculated for each picture after 100 iterations of the image processing with different enhancement parameters. At last, we manually counted the numbers of Aurelia sp. on the same cropped images as the semiautomated method using the multipoint tool in ImageJ V. 1.53a [40], an openaccess image processing software. The surface areas of the cropped images were based on the following formula determining the pixel resolution: where H is the camera height at which the picture was taken (in m, available through the AirData app.), P is the pixel size on the camera sensor (2.41 microns; based on a sensor size of 13.2 mm * 8.8 mm) and F is the focal length of the camera (24 mm).Aurelia sp.densities from drone pictures were calculated using the same formula as with the net, considering N as the number of individuals counted on the pictures.The water volume V was obtained by multiplying the surface area with the average water depth of 2 m in the sampling area [35].Information on how we treated image data and JF counting are given in the Supplementary material.
|
<li> <b>drone pictures:</b> Camera<li> <b>drone:</b> Other Vehicle<li> <b>camera:</b> Camera
|
[
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[
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[
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[
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[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
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] |
[
null
] |
[
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[
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},
{
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}
] | null | null |
880df614-9eba-444b-a885-c8a3c27d76a5
|
completed
| 2025-04-09T16:14:38.079899
| 2025-05-26T07:35:20.066631
|
0e3977f5-882c-4841-bb56-cf3b9f739cf1
|
The underwater robot is part of a project with “terrestrial–maritime” collaborative robots, whose mission is recognition and rescue. From a structural point of view, some small changes were made in this study to the original robot. These changes consisted of making supports to hold the two plexiglass tubes, since the tube containing the battery system is larger. A larger tube was chosen because the aim was to increase the travel autonomy of the mini remotely operated vehicle (ROV). The mini submarine will move in an unstructured environment and will be able to reach a depth of 100 m. The purpose of the article is to present a point of view regarding the effect of the behavior of the mini ROV on tensions produced by the forced assembly of the sealing cover of the cylinder containing its command-and-control system. Both the gripping elements and the sealing lids are made using 3D printing technology, and the material used is polylactic acid (PLA). For the numerical analysis, the finite element method is used in both static and dynamic conditions. The results of this work refer to the field of tensions and displacements. The main conclusions emphasize the fact that the gripping performed for sealing is influenced by the usage of oiled mechanisms.
|
<li> <b>underwater robot:</b> Other Vehicle<li> <b>robots:</b> Other Vehicle<li> <b>robot:</b> Other Vehicle<li> <b>remotely operated vehicle (ROV):</b> Other Vehicle<li> <b>mini submarine:</b> Other Vehicle<li> <b>mini ROV:</b> Other Vehicle
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
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] |
[
"Partially correct"
] |
[
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] |
[
"submitted"
] |
[
"Correct"
] |
[
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] |
[
"submitted"
] |
[
"\"underwater robot\", \"remotely operated vehicle(ROV)\" and \"submarine\" are not of interest to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
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] |
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{
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{
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{
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},
{
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}
] | null | null |
49a504c9-9b95-4f28-9626-e682ad2be4bc
|
completed
| 2025-04-09T16:14:38.079905
| 2025-05-26T06:52:06.170133
|
c71afe66-2c10-47cb-8b62-920297be12c3
|
Place the force sensor on the movable cross-member of the press and place the cylinder over the sensor.
|
<li> <b>force sensor:</b> Other Sensor
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"this sensor type is unknown to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 22,
"label": "sensorType",
"start": 10
}
] | null | null |
bb9dccd5-104a-4f94-a764-67cb76c4e69f
|
completed
| 2025-04-09T16:14:38.079911
| 2025-05-26T13:20:52.813644
|
b9f6af1a-70b2-4af9-abe1-2bc7ebb4f7fd
|
With the world population highly increasing, efficient methods of transportation are more necessary than ever. On the other hand, the sharing economy must be explored and applied where possible, aiming to palliate the effects of human development on the environment. In this paper we explore demand-responsive shared transportation as a system with the potential to serve its users’ displacement needs while being less polluting. In contrast with previous works, we focus on a distributed proposal that allows each vehicle to retain its private information. Our work describes a partially dynamic system in which the vehicles are self-interested: they decide which users to serve according to the benefit it reports them. With our modelling, the system can be adapted to mobility platforms of autonomous drivers and even simulate the competition among different companies.
|
<li> <b>vehicle:</b> Other Vehicle<li> <b>vehicles:</b> Other Vehicle
|
[
[
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
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}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 522,
"label": "vehicleType",
"start": 515
},
{
"end": 625,
"label": "vehicleType",
"start": 617
}
] | null | null |
14c9f1c4-18e8-4aaf-b8b4-2edeee830f2c
|
completed
| 2025-04-09T16:14:38.079917
| 2025-05-13T05:51:46.620155
|
a981347e-0ea8-460f-90c6-44eef99f4e3e
|
As the world's population increases, the scarcity of our planet's resources becomes apparent.Responsible authorities have developed a strong interest in the sustainability of our means of production as well as our way of life.Urban centres, for example, need to improve their services to make them competitive in today's world.By implementing artificial intelligence in the different systems that make up a city, it becomes a Smart City.Among the different city systems, the urban transit system stands out as one of the most complex and dynamic.However, most affordable solutions still consist of high-capacity transport with fixed routes and stops, to whose operation users have to adapt.The considerably more expensive alternatives focus on a completely individual service, which does not favour a possible reduction of greenhouse gas emissions or congestion avoidance. In the current ever-changing dynamic ecosystem that cities define, static systems have become, if not obsolete, outdated and often uncomfortable to use.Demand-responsive transportation (DRT) systems initially served people with special needs or those who lived in rural, ill-connected areas of a city or country.This type of mobility is characterised by its flexibility to adapt to different demand patterns.At first, this meant creating routes according to the departure location of users specifically.Nowadays, however, we see some demand-responsive behaviour implemented in most current transportation services.Ranging from picking a customer up at their desired location to increasing the number of vehicles in a fleet in periods of high demand, plenty of strategies try to make the service operation reactive to the demand. Introducing the concept of shared transportation to DRT systems, we can develop demand-responsive shared transportation (DRST).DRST services can offer a reasonable middle-point between the stiffness of public transport and the pollution and individuality of dial-a-ride services.This mobility features strategies like dynamic modification of vehicle routes and stops, on-demand creation of routes and dynamic dispatching of vehicles according to demand.Shared mobility, however, generally involves a lower customer satisfaction with the service if compared to individual mobility.In addition, dynamic systems are complex, and their degree of dynamism affects their operation costs.DRST presents the challenge to find the balance between flexibility, shareability and sustainability of its fleet model so that (1) the service is economically viable, (2) the quality of service is maximised and (3) the pollution derived from its operation is minimised. Most DRST research focuses on exploring service configurations, management and operation strategies to find the equilibrium among the above-mentioned indicators.For that, it is necessary to model and parameterise the transportation system, which is generally done through either mathematical or agent-based approaches.In this work, we focus on agent-based modelling (ABM), as it allows the design of behaviours for each component of the system and the analysis of the system's operation, from which interactions and synergies may appear. Regarding service operation, however, the reviewed publications mainly propose centralised systems.In this type of system, a central coordination entity makes all decisions, while the fleet vehicles are expected to follow every order.In practice, a manager entity accepts or rejects travel requests, assigns and modifies vehicle routes and organises vehicle dispatching.In contrast with the centralised operation, we find decentralised systems.Decentralisation allows the decision making to be performed individually by each component of the system, taking into account that their operation must be coordinated.Given the lack of works that apply distributed techniques to their modelling, we want to explore a decentralised operation in our DRST system.Decentralisation allows for implementation with open fleets, whose number of vehicles is variable and favour the autonomy of vehicles (and drivers).Transportation services like Uber are implemented with open fleets, and their drivers can choose which requests to accept according to their own preferences.Inspired by this, we propose developing the service's operation from a distributed and self-interested perspective. Self-interested agents (or entities) are those whose actions are guided by their own private objectives.These agents accurately represent many aspects of human behaviour, which is generally motivated by personal gains.When many of these agents operate in a shared environment (such as a city), they define a non-strictly competitive scenario.The goals of the agents might not be opposed, but their operation to reach the goals may cause conflicts with the operation of other agents.The field of game theory [1] explores the interactions among self-interested entities, offering tools to develop coordination techniques that ensure a conflictless operation.In addition, automated negotiation algorithms can also be applied for conflict resolution.Modelling with self-interested agents allows us to reproduce a DRST system where vehicles of different enterprises may "compete" to serve the customers of one mobility platform.We believe such a competition may result in a better quality of service for the user and higher adaptability of the system to the demand. We hope to open a discussion on distributed demand-responsive shared mobility with this work.The aim is to analyse and discuss the requirements a DRST system needs if its fleet is implemented by self-interested vehicles.In accordance with the above, we propose a system architecture for a partially dynamic system that accepts real-time travel requests as well as bookings.We discuss the particularities that a fleet of self-interested vehicles involves and describe how the assignment of bookings and requests works in our distributed paradigm. The rest of the paper is structured as follows.Section 2 discusses relevant works in the field of DRT systems, focusing on the differences in configuration and modelling approaches.Section 3 presents an overview of the proposed system, briefly describing our modelling and the system's architecture.Section 4 discusses the operation of the static subsystem of our proposal, which takes care of booked trips.Section 5 describes how our system deals with real-time travel requests.In Section 6 our proposal is analysed and compared to other works.Finally, Section 7 assesses our work and comments on future extensions.
|
<li> <b>vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>public transport:</b> Bus
|
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Public transport can be a Bus but not only that"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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},
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},
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},
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},
{
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"label": "vehicleType",
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}
] | null | null |
8f96d260-8704-4dfe-9d42-f9e3294e9558
|
completed
| 2025-04-09T16:14:38.079923
| 2025-05-26T13:36:42.268148
|
6c6eaaf9-77d4-4f3e-a3dc-894f3e5e7180
|
This paper focuses on autonomous navigation for an electric freight vehicle designed to collect freight autonomously using pallet handling robots installed in the vehicle. Apart from autonomous vehicle navigation, the primary hurdle for vehicle autonomy is the autonomous collection of freight irrespective of freight orientation/location. This research focuses on generating parking pose for the vehicle irrespective of the orientation of freight for its autonomous collection. Freight orientation is calculated by capturing the freight through onboard sensors. Afterward, this information creates a parking pose using mathematical equations and knowledge of the vehicle and freight collection limitations. Separate parking spots are generated for separate loading bays of the vehicle depending on the availability of the loading bay. Finally, results are captured and verified for different orientations of freight to conclude the research.
|
<li> <b>electric freight vehicle:</b> Truck<li> <b>vehicle:</b> Other Vehicle<li> <b>robots:</b> Other Vehicle<li> <b>autonomous vehicle:</b> Other Vehicle<li> <b>parking:</b> Automated Parking<li> <b>onboard sensors:</b> Other Sensor
|
[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"robot\" not a vehicleType in this context\n\"parking\" is not a scenarioType in this context\n"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
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},
{
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}
] | null | null |
d20bc0ce-d5c3-4b43-ad73-9947ac899c8d
|
completed
| 2025-04-09T16:14:38.079930
| 2025-05-26T08:21:08.425770
|
8d34cea8-785e-4bd9-8618-1ac161b488b9
|
As the vehicle is equipped with two loading bays, the parking spot w.r.t each loading bay is different.To load the cargo in the front-loading bay, the vehicle needs to park a certain distance behind its center point, as shown in Figure 4.If the first loading bay is occupied by the previously loaded freight, then the vehicle needs to park a little ahead of its center point by a distance so that the forks are perfectly aligned with the freight to load the freight in the second loading bay.The center point of the parking spot thus varies depending upon the availability of the loading bay.This is further explained in Equation ( 8). where d b1 and d b2 are the positive distances of loading bay 1 and 2 from vehicle center (measurement shown in Figure 4), and (x vc , y vc ) is the center-point of parking spot.The condition bay1 = 1 denotes the condition of availability of loading bay 1.If bay 1 is available to load the freight, then the first condition applies or else the parking spot is generated w.r.t second loading bay. After defining the center of the parking spot, the four corners of the parking spot can be defined through Equations ( 9)-( 12) using the knowledge of parking width (d w ), parking length (d l ), angle of the freight (θ f ) and parking center-point (x pc , y pc ).The collection of the first corner of the parking pose requires the knowledge of parking pose width + length.The derivation of equations is based on trigonometric relations and point transformation from the known parking center-point to the first edge of the parking pose.Since all four lines of the parking pose are parallel or perpendicular to the freight, the solution is formed by adding the respective angle (90 • , 180 • , 270 • ) to the angle of the freight θ f for calculation of next point of the parking pose. The four corners of the parking pose (x p1 , y p1 ), (x p2 , y p2 ), (x p3 , y p3 ) and (x p4 , y p4 ) are the consequent four corners of the parking pose.These points are further explained later. The summary of the whole pose generation solution is as follows.The vehicle is required to detect freight and acquire the corner points of the freight from the side where it can be loaded.Afterwards, Equation ( 5)-( 12) are solved to get the correct pose for loading freight into the vehicle.The complete process of correct pose generation is further summarized in the flowchart presented in Figure 9.
|
<li> <b>vehicle:</b> Other Vehicle<li> <b>parking:</b> Automated Parking
|
[
[
{
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},
{
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{
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},
{
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}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"There appears a generalization of translating the term \"parking\" to \"automated parking\", which is actually not correct."
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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},
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},
{
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},
{
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},
{
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"label": "scenarioType",
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},
{
"end": 1965,
"label": "scenarioType",
"start": 1958
}
] | null | null |
1679bc97-d124-4d42-b79d-d7218ba523a6
|
completed
| 2025-04-09T16:14:38.079936
| 2025-05-26T08:35:45.281232
|
7f3d083b-99f1-4b72-ae8d-546370a4372b
|
In many countries, industrialization has led to rapid urbanization. Increased frequency of urban flooding is one consequence of the expansion of urban areas which can seriously affect the productivity and livelihoods of urban residents. Therefore, it is of vital importance to study the effects of rainfall and urban flooding on traffic congestion and driver behavior. In this study, a comprehensive method to analyze the influence of urban flooding on traffic congestion was developed. First, a flood simulation was conducted to predict the spatiotemporal distribution of flooding based on Storm Water Management Model (SWMM) and TELAMAC-2D. Second, an agent-based model (ABM) was used to simulate driver behavior during a period of urban flooding, and a car-following model was established. Finally, in order to study the mechanisms behind how urban flooding affects traffic congestion, the impact of flooding on urban traffic was investigated based on a case study of the urban area of Lishui, China, covering an area of 4.4 km2. It was found that for most events, two-hour rainfall has a certain impact on traffic congestion over a five-hour period, with the greatest impact during the hour following the cessation of the rain. Furthermore, the effects of rainfall with 10- and 20-year return periods were found to be similar and small, whereas the effects with a 50-year return period were obvious. Based on a combined analysis of hydrology and transportation, the proposed methods and conclusions could help to reduce traffic congestion during flood seasons, to facilitate early warning and risk management of urban flooding, and to assist users in making informed decisions regarding travel.
|
<li> <b>car:</b> Other Vehicle<li> <b>car-following:</b> Other Scenario
|
[
[
{
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"start": 756
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"car\" should be identified as \"car\" and not as \"other vehicle\""
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 759,
"label": "vehicleType",
"start": 756
},
{
"end": 769,
"label": "scenarioType",
"start": 756
}
] | null | null |
ac270e7d-4361-4df9-936f-03c200513e1d
|
completed
| 2025-04-09T16:14:38.079942
| 2025-05-26T08:40:20.789892
|
6a675961-de27-4b67-9dda-84dd434ef4a0
|
We simulated the traffic situation dynamically using the 24-h traffic volume.As each vehicle in our study was deemed an agent, the number of agents is shown in Figure 9.The simulation results match the actual situation well. Based on traffic volume data from 26 June 2017 (Monday) and 25 June 2017 (Sunday), representative of the traffic conditions on a weekday and on the weekend, we simulated both situations and obtained the results shown in Figure 9.In this figure, the left panel represents the instantaneous number of agents per hour in the entire system, and the right panel represents the traffic volume passing through the intersection of Li Qing Road and Hua Yuan Road per hour.The trends of simulated traffic volume shown in both panels are similar to the actual data at all five intersections shown in Figure 4, indicating the reliability of this traffic simulation. From Figure 9a, it is obvious that congestion on the weekday is more serious than on the weekend, especially in the morning.The level of congestion in both situations fluctuates within a certain range in the afternoon.For example, the traffic volumes at 14:00, 15:00, 16:00, 20:00, and 21:00 on the weekend were higher than during the same periods on weekdays.This finding is shown in Figure 9b, as the intersection of Li Qing Road and Hua Yuan Road is one of the main transport hubs in the entire system; it has an important role in concentrating and diffusing traffic.Consequently, the traffic volume at this junction from 09:00 to 22:00 remained high with little variation.
|
<li> <b>vehicle:</b> Other Vehicle<li> <b>intersection:</b> Other Scenario
|
[
[
{
"end": 92,
"label": "vehicleType",
"start": 85
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"intersection\" is not a scenario type itself, but it could be when referenced as such"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 92,
"label": "vehicleType",
"start": 85
},
{
"end": 644,
"label": "scenarioType",
"start": 632
},
{
"end": 1294,
"label": "scenarioType",
"start": 1282
}
] | null | null |
11f6c35a-0790-4083-a31a-7e0f7510631b
|
completed
| 2025-04-09T16:14:38.079948
| 2025-05-26T14:05:07.706664
|
f41fe581-e657-498e-9f4c-2c3198d0bc33
|
This paper reviews existing policies for supporting the treatment of electric vehicle (EV) battery waste in China, and identifies some of their major shortcomings that policy makers may like to consider while making policy decisions. The shortcomings of existing policies identified in this paper include: 1) no clear provisions for historical and orphan batteries; 2) no target for battery collection; 3) unclear definition of the scope of authority among various central and local agencies involved in the regulation of waste battery treatment; 4) unclear requirements for data auditing and verification for tracking the entire life cycle of EV batteries; 5) limited consideration of the challenges to ensure stakeholder cooperation; and 6) no explicit specification of the mechanisms for financing waste battery treatment. This paper also makes some practical policy suggestions for overcoming these shortcomings.
|
<li> <b>electric vehicle (EV):</b> Car<li> <b>EV:</b> Car
|
[
[
{
"end": 90,
"label": "vehicleType",
"start": 69
},
{
"end": 646,
"label": "vehicleType",
"start": 644
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EVs\" could be other vehicles than cars"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 90,
"label": "vehicleType",
"start": 69
},
{
"end": 89,
"label": "vehicleType",
"start": 87
},
{
"end": 646,
"label": "vehicleType",
"start": 644
}
] | null | null |
e7b3edcf-df0b-48f8-9ba3-5c73039122ab
|
completed
| 2025-04-09T16:14:38.079954
| 2025-05-26T07:28:17.501997
|
384a0e5c-7032-4200-af03-5240079b8fc2
|
Approximately one third of all traffic fatal crashes are alcohol-related in the US according to the National Highway Traffic Safety Administration (NHTSA), alcohol-related crashes cost more than $37 billion annually. Considerable research efforts are needed to understand better significant causal factors for alcohol-related crash risks and driver’s injury severities in order to develop effective countermeasures and proper policies for system-wide traffic safety performance improvements. Furthermore, since two thirds of urban Vehicle Miles Traveled (VMT) is on signal-controlled roadways, it is of practical importance to investigate injury severities of all drivers who are involved in intersection-related crashes and their corresponding significant causal factors due to control and geometric impacts on flow progression interruptions. This study aims to identify and quantify the impacts of alcohol/non-alcohol-influenced driver’s behavior and demographic features as well as geometric and environmental characteristics on driver’s injury severities around intersections in New Mexico. The econometric models, multinomial Logit models, were developed to analyze injury severities for regular sober drivers and alcohol-influenced drivers, respectively, using the crash data collected in New Mexico from 2010 to 2011. Elasticity analyzes were conducted in order to understand better the quantitative impacts of these contributing factors on driver’s injury outcomes. The research findings provide a better understanding of contributing factors and their impacts on driver injury severities in crashes around intersections. For example, the probability of having severe injuries is higher for non-alcohol-influenced drivers when the drivers are 65 years old or older. Drivers’ left-turning action will increase non-alcohol-influenced driver injury severities in crash occurring around intersections. However, different characteristics are captured for alcohol-influenced drivers involved in intersection-related crashes. For example, more severe injuries of alcohol-influenced drivers can be observed around intersections with three or more lanes on each approach. The model specifications and estimation results are also helpful for transportation agencies and decision makers to develop cost-effective solutions to reduce alcohol-involved crash severities and improve traffic system safety performance.
|
<li> <b>Vehicle:</b> Other Vehicle<li> <b>intersections:</b> Other Scenario<li> <b>intersection:</b> Other Scenario<li> <b>Vehicle:</b> Other Vehicle<li> <b>intersections:</b> Other Scenario<li> <b>intersection:</b> Other Scenario
|
[
[
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},
{
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"label": "scenarioType",
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{
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}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"linked entities appear duplicate"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
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{
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{
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},
{
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},
{
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},
{
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},
{
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"label": "scenarioType",
"start": 692
},
{
"end": 2009,
"label": "scenarioType",
"start": 1997
}
] | null | null |
6d750423-3bf8-4031-95e9-e1684b566344
|
completed
| 2025-04-09T16:14:38.079960
| 2025-05-26T14:08:08.931983
|
875ea6f5-b8db-4992-8840-dd095474a6f7
|
An ideal roadway is one that connects to our driveways (access) and at the same time leads to interruption-free drives to our destinations (mobility).To accomplish this, roadways are planned and designed differently.Local roads are chiefly to provide access (driveways, median openings), while mobility is the primary function of arterials.Since 1980 an additional 183,000 miles of public roads have been constructed, an average of 6,500 miles of new roads each year.Rural public roads have steadily decreased since 1980 as these roadways have been reclassified as urban due to increases in population and geographic dispersion.At the same time a corresponding increase in urban facilities is seen partly due to urban boundary reclassification and partly due to new construction.Since 1923 an additional 818,000 miles of public roads have been constructed, an average of 9,500 new centerline miles every year. With the highway network largely complete, nearly all population centers are linked by paved roadways and virtually all counties are connected by the Interstate highway system within the 48 contiguous States. Data Source: FHWA Note: Lane-mile data not available before 1985. Lane-miles increase as highways are widened to accommodate additional travel needs due to population growth in the various communities.In 1923, the U.S had a population of approximately 112 million.In 2010, the latest decennial census shows that there are 309 million people, a nearly three-fold increase.Adding capacity to existing highways is one of many ways transportation agencies are ready to meet the needs of a continually growing population.Bridges are key components of our nation's highway system.Maintaining their integrity is critical for safe and efficient travel. The National Bridge Inventory (NBI) collects information on the nation's bridges, including those located on interstate highways, U.S. highways, state and county roads, as well as publiclyaccessible bridges on federal lands.Each state is required to conduct periodic inspections of all bridges and report the data to FHWA. One of the most efficient ways to increase roadway operating efficiency is to separate at-grade intersections with bridges.In 2010 there are 604,460 bridges along public roads.Since 1992 32,264 bridges have been constructed, an average of 1,792 new bridges each year.Roads, bridges, and tunnels that require drivers to pay a fee for usage are referred to as toll highways, turnpikes, or toll structures.High-occupancy toll (HOT) roads are also constructed to provide free or discounted access to high-occupancy vehicles (HOVs) while allowing single-occupant vehicles to use the facility for a fee.The fees collected from these facilities are typically used to repay the money borrowed for construction.As the debt is repaid the toll may be used for ongoing operations and maintenance. Thirty states, plus Puerto Rico, have toll facilities.The length of these facilities as they're recorded varies depending on the type (toll bridge, tunnel, or roadway).Oregon, for example, has only three toll bridges, while Florida has several toll roads throughout the state, including the 300-mile-long Florida's Turnpike. While the vast majority of Interstate highways have no tolls, approximately 2,900 miles of Interstates are tolled in 21 states.These tolled facilities range in length from 500-mile New York State Thruway to tolled sections of I-95 in Delaware and Maryland.
|
<li> <b>vehicles:</b> Other Vehicle<li> <b>high-occupancy vehicles (HOVs):</b> Car<li> <b>single-occupant vehicles:</b> Car<li> <b>vehicles:</b> Other Vehicle<li> <b>high-occupancy vehicles (HOVs):</b> Car<li> <b>single-occupant vehicles:</b> Car
|
[
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},
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}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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},
{
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},
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{
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{
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"label": "vehicleType",
"start": 2583
},
{
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"label": "vehicleType",
"start": 2629
}
] | null | null |
b5ec16f1-4282-40e0-b69f-6529b7056c9f
|
completed
| 2025-04-09T16:14:38.079966
| 2025-05-26T13:56:37.233788
|
9adb9582-65c5-4dcf-88e0-d2eada5b9ba2
|
Recently, as humans have become increasingly interested in ocean resources, underwater vehicle-manipulator systems (UVMSs) have played an increasingly important role in ocean exploitation. To realize precise operation in underwater narrow spaces, the fly arm underwater vehicle manipulator system (FAUVMS) is proposed with manipulators as its core. However, this system suffers severe dynamic coupling effects due to the combination of small vehicle and big manipulators. To resolve this issue, we propose a robust adaptive controller that contains two parts. In the first part, the extended Kalman filter (EKF) is designed to estimate the system states and predicts external disturbances to achieve adaptive control. In the second part, a chattering-free sliding mode control (SMC) is designed to converge the tracking errors to zero, thus guaranteeing the robustness of the controller. We constructed the simulation platform based on the geometric model of FAUVMS, and various simulations are carried out under different situations. Compared to the traditional methods, the proposed method has a faster convergent speed, a better robustness and adaptiveness to external disturbances, and the tracking errors of positions of the vehicle and each end-effector are much smaller.
|
<li> <b>underwater vehicle-manipulator systems (UVMSs):</b> Other Vehicle<li> <b>underwater vehicle manipulator system (FAUVMS):</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>underwater vehicle-manipulator systems (UVMSs):</b> Other Vehicle<li> <b>underwater vehicle manipulator system (FAUVMS):</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle
|
[
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{
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"label": "vehicleType",
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},
{
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"start": 1230
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"UVMSs\" and \"FAUVMS\" are not of interest to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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{
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{
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{
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},
{
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},
{
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"label": "vehicleType",
"start": 1230
}
] | null | null |
b39e9126-e4f5-4575-b1d4-1f016a62ca42
|
completed
| 2025-04-09T16:14:38.079972
| 2025-05-13T06:29:24.005853
|
5a1034c3-9a94-41e8-af4a-b633d1c27edf
|
The control diagram is shown in Figure 5.Note that trajectory planning and inverse kinematics are not part of our research, so it is assumed that we already have the desired states of FAUVMS.Considering the complex underwater environment and highly nonlinear dynamic coupling, the robust adaptive controller is arranged into two parts.The first part is the main control law derived by the EKF and CTC framework; the famous nonlinear filter EKF can fuse the measurement data with zero-mean Gaussian noise and estimate the external disturbances, which are then incorporated into the control law to gain better performance.However, the EKF technique is formulated with zero-mean Gaussian noise, which never exists in the real world; thus, this method can only fuse data with zero-mean Gaussian noise and cannot guarantee robust control performance.To overcome this issue, the second part is developed with the system error model through the SMC technique.The main purpose of the SMC controller is to converge the system tracking errors to zero.
|
<li> <b>FAUVMS:</b> Other Vehicle<li> <b>FAUVMS:</b> Other Vehicle
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"I do not know what FAUVMS is, thus it is marked as incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 190,
"label": "vehicleType",
"start": 184
},
{
"end": 190,
"label": "vehicleType",
"start": 184
}
] | null | null |
19da2070-3222-4338-8031-9b8d1db01a29
|
completed
| 2025-04-09T16:14:38.079978
| 2025-05-13T05:35:35.625503
|
5b6f3af4-9db7-4d0a-977c-2da8b5d7c19b
|
Internal combustion engine (ICE)-based vehicles have contributed considerably to air pollution [...]
|
<li> <b>Internal combustion engine (ICE)-based vehicles:</b> Car<li> <b>Internal combustion engine (ICE)-based vehicles:</b> Car
|
[
[
{
"end": 47,
"label": "vehicleType",
"start": 0
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Instead of Car the linked entity could be a Truck. For simplicity, we could leave Car"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 47,
"label": "vehicleType",
"start": 0
},
{
"end": 47,
"label": "vehicleType",
"start": 0
}
] | null | null |
6131b534-a436-4be3-8b75-d4edc3d49b71
|
completed
| 2025-04-09T16:14:38.079984
| 2025-05-26T08:21:51.767354
|
e530480b-ae13-4e09-a617-a9786e27aeb5
|
To combat environmental pollution, sustainable transport, particularly electrification of the transport sector, is essential.However, several barriers still exist, such as societal, economic and technological.Researchers are still trying to obtain the best technological solution, while the government should develop strict policies to support EV penetration on the road. Funding: This research received no external funding.
|
<li> <b>EV:</b> Car<li> <b>EV:</b> Car
|
[
[
{
"end": 346,
"label": "vehicleType",
"start": 344
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EV\" could be \"other vehicle\"\nLink entity appears duplicate\n"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 346,
"label": "vehicleType",
"start": 344
},
{
"end": 346,
"label": "vehicleType",
"start": 344
}
] | null | null |
a4e14ca0-1c23-4d89-b91e-f25c201014ef
|
completed
| 2025-04-09T16:14:38.079990
| 2025-05-26T14:24:36.929792
|
da6c9fea-1422-4990-bb95-63f713a3e72b
|
The heat dissipation characteristics of the lithium-ion battery pack will have an effect on the overall performance of electric vehicles. To investigate the effects of the structural cooling system parameters on the heat dissipation properties, the electrochemical thermal coupling model of the lithium-ion power battery has been established, and the discharge experiment of the single battery has been designed. The voltage and temperature curves with time are similar to those obtained from the numerical model at various discharge rates, and the experimental results are relatively accurate. Based on this model, the height, angle, and number of different air inlets and outlets are designed, and the heat dissipation characteristics of different structural parameters are analyzed. The results show that the maximum temperature decreases by 3.9 K when the angle increases from 0° to 6°, the average temperature decreases by 2 K and the maximum temperature difference decreases by 2.9 K when the height increases from 12 mm to 16 mm, and the more the number of air inlets and outlets there are, the better the heat dissipation effect is. Therefore, the air vent of the battery cooling system has an important impact on the heat dissipation characteristics of the battery, which should be fully considered in the design.
|
<li> <b>electric vehicles:</b> Car<li> <b>electric vehicles:</b> Car
|
[
[
{
"end": 136,
"label": "vehicleType",
"start": 119
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"electric vehicles\" could be other vehicles than cars"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 136,
"label": "vehicleType",
"start": 119
},
{
"end": 136,
"label": "vehicleType",
"start": 119
}
] | null | null |
b590273f-f5eb-44fa-8c2f-7ee228ee334e
|
completed
| 2025-04-09T16:14:38.079996
| 2025-05-13T06:07:32.743226
|
c2d10232-db2c-4848-a0a1-05b0933b1e16
|
The structure of an autonomous underwater vehicle (AUV), usually composed of a cylindrical shell, may be exposed to high hydrostatic pressures where buckling collapse occurs before yield stress failure. In conventional submarines, welded stiffeners increase the buckling resistance, however, in small AUVs, they reduce the inner space and cause residual stresses. This work presents an innovative concept for the structural design of an AUV, proposing the use of sliding stiffeners that are part of the structure used to accommodate the electronics inside it. Since the sliding stiffeners are not welded to the shell, there are no residual stresses due to welding, the AUV fabrication process is simplified, enabling a reduction of the manufacturing cost, and the inner space is available to accommodate the equipment needed for the AUV mission. Moreover, they provide a higher buckling resistance when compared to that of an unstiffened cylindrical shell. A comparative analysis of the critical buckling loads for different shell designs was carried out considering the following: (i) the unstiffened shell, (ii) the shell with ring stiffeners, and (iii) the shell with sliding stiffeners. Results evidenced that major advantages were obtained by using the latter alternative against buckling.
|
<li> <b>autonomous underwater vehicle (AUV):</b> Other Vehicle<li> <b>submarines:</b> Other Vehicle<li> <b>AUVs:</b> Other Vehicle<li> <b>autonomous underwater vehicle (AUV):</b> Other Vehicle<li> <b>submarines:</b> Other Vehicle<li> <b>AUVs:</b> Other Vehicle
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Submarines and AUVs are out of our scope"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 55,
"label": "vehicleType",
"start": 20
},
{
"end": 229,
"label": "vehicleType",
"start": 219
},
{
"end": 305,
"label": "vehicleType",
"start": 301
},
{
"end": 55,
"label": "vehicleType",
"start": 20
},
{
"end": 229,
"label": "vehicleType",
"start": 219
},
{
"end": 305,
"label": "vehicleType",
"start": 301
}
] | null | null |
0353b576-4979-46b6-a530-48f3333c80a3
|
completed
| 2025-04-09T16:14:38.080003
| 2025-05-26T08:46:38.457162
|
7e90203c-e254-4ec6-a77a-6f17fd99e805
|
Results obtained in Sections 2 and 3 have shown a good agreement between analytical formulations and finite element results.Therefore, a similar finite element methodology is expected to produce satisfactory results in the case of sliding stiffeners as well.Figure 10 shows a schematic three-dimensional view of the internal structure of the AUV which serves as a support to accommodate the electronics inside the vehicle.It must be observed that the same number of ring stiffeners (4) is considered in this case, but now they are not fixed in the shell.In this section, the effectiveness of such movable internal structure is checked in terms of the increase in the critical buckling pressure, when compared to the buckling pressures obtained by the two previous shell designs.The critical buckling pressures in this last case were once again obtained via linear buckling analyses using the same element types presented in the previous section (shell181 for the shell and solid187 for the four rings and other structural members of the inner platform).Contact elements (conta174) were also used to represent the contact between the shell and the outer surface of the ring The critical buckling pressures in this last case were once again obtained via linear buckling analyses using the same element types presented in the previous section (shell181 for the shell and solid187 for the four rings and other structural members of the inner platform).Contact elements (conta174) were also used to represent the contact between the shell and the outer surface of the ring stiffeners.Figure 11 shows the basic geometries considered in the analyses of the conventional stiffened shell (as presented in Section 3) and in the analyses of the shell with sliding stiffeners (as presented in this section) to highlight the differences.The critical buckling pressures in this last case were once again obtained via linear buckling analyses using the same element types presented in the previous section (shell181 for the shell and solid187 for the four rings and other structural members of the inner platform).Contact elements (conta174) were also used to represent the contact between the shell and the outer surface of the ring stiffeners.Figure 11 shows the basic geometries considered in the analyses of the conventional stiffened shell (as presented in Section 3) and in the analyses of the shell with sliding stiffeners (as presented in this section) to highlight the differences.It must be observed that, for this new shell design, gap formation between some parts of the shell and parts of the ring stiffeners does occur (after buckling) since the ring stiffeners are not fixed to the shell.A friction coefficient of μ = 0.2 between shell and stiffeners was used in all the analyses of this section.Figure 12 shows all the elements that were used to represent the sliding stiffeners in the finite element analysis (the longitudinal members were erased in Figure 11 to make it clearer).It must be observed that, for this new shell design, gap formation between some parts of the shell and parts of the ring stiffeners does occur (after buckling) since the ring stiffeners are not fixed to the shell.A friction coefficient of µ = 0.2 between shell and stiffeners was used in all the analyses of this section.Figure 12 shows all the elements that were used to represent the sliding stiffeners in the finite element analysis (the longitudinal members were erased in Figure 11 to make it clearer).Figure 13 shows the convergence analysis obtained in this last case, where the least value for the critical buckling pressure was about 12.85 MPa, which represents a 41% increase in the critical buckling pressure, if compared to the FEM value achieved for the unstiffened shell, and a 14% increase in the critical buckling pressure if compared to the FEM value achieved for the conventional stiffened shell.Thus, the contribution provided by the sliding stiffeners shown in Figure 12 indeed improved the buckling strength of the AUV.Although such elements have been initially conceived to serve as a simple support to the electronic devices boarded into the AUV, it was shown that they may also provide a good increment in the buckling strength of the vehicle.Figure 13 shows the convergence analysis obtained in this last case, where the least value for the critical buckling pressure was about 12.85 MPa, which represents a 41% increase in the critical buckling pressure, if compared to the FEM value achieved for the unstiffened shell, and a 14% increase in the critical buckling pressure if compared to the FEM value achieved for the conventional stiffened shell.Thus, the contribution provided by the sliding stiffeners shown in Figure 12 indeed improved the buckling strength of the AUV.Although such elements have been initially conceived to serve as a simple support to the electronic devices boarded into the AUV, it was shown that they may also provide a good increment in the buckling strength of the vehicle. buckling pressure, if compared to the FEM value achieved for the unstiffened shell, and a 14% increase in the critical buckling pressure if compared to the FEM value achieved for the conventional stiffened shell.Thus, the contribution provided by the sliding stiffeners shown in Figure 12 indeed improved the buckling strength of the AUV.Although such elements have been initially conceived to serve as a simple support to the electronic devices boarded into the AUV, it was shown that they may also provide a good increment in the buckling strength of the vehicle.Figure 14 shows the eigenmode and the corresponding eigenvalue (load multiplier = 12.85) obtained using a linear buckling analysis, showing that a generalized buckling mode is again obtained in this case.Figures 15 and16 show the meshes used to obtain the lowest eigenvalue (12.85 MPa).In this last analysis, about 153,000 elements were used in the simulation.Figure 14 shows the eigenmode and the corresponding eigenvalue (load multiplier = 12.85) obtained using a linear buckling analysis, showing that a generalized buckling mode is again obtained in this case.Figures 15 and16 show the meshes used to obtain the lowest eigenvalue (12.85 MPa).In this last analysis, about 153,000 elements were used in the simulation.Figure 17 compares the finite element results obtained for the critical buckling pressures considering the three studied cases: (i) the unstiffened shell case (Section 2), (ii) the conventional stiffened shell case (Section 3), and (iii) the shell with sliding stiffeners case (Section 4).It can be noticed that the solution provided by the sliding stiffeners added several advantages to the AUV design: ease of manufacture (since the ring stiffeners are not welded to the shell), reduction of the manufacturing cost (by the same token), and increase in the buckling strength of the structure, meaning a direct increase in the water depth at which the vehicle can operate.Figure 17 compares the finite element results obtained for the critical buckling pressures considering the three studied cases: (i) the unstiffened shell case (Section 2), (ii) the conventional stiffened shell case (Section 3), and (iii) the shell with sliding stiffeners case (Section 4).It can be noticed that the solution provided by the sliding stiffeners added several advantages to the AUV design: ease of manufacture (since the ring stiffeners are not welded to the shell), reduction of the manufacturing cost (by the same token), and increase in the buckling strength of the structure, meaning a direct increase in the water depth at which the vehicle can operate.Table 4 shows the three first eigenvalues obtained by the finite element models for each of the shell designs presented in this work.It must be stressed, however, that interactions among different buckling modes can exist in real (not "perfect") structures.Such interactions are triggered by imperfections (even very small ones) which are always present in real structures, leading to a limit load that can be significantly lower than the smallest critical load of a perfect cylindrical shell (see, e.g., Liguori et al. [18]).Thus, it is highly recommended to use nonlinear analyses to obtain safer results for the critical buckling load.Table 4 shows the three first eigenvalues obtained by the finite element models for each of the shell designs presented in this work.It must be stressed, however, that interactions among different buckling modes can exist in real (not "perfect") structures.Such interactions are triggered by imperfections (even very small ones) which are always present in real structures, leading to a limit load that can be significantly lower than the smallest critical load of a perfect cylindrical shell (see, e.g., Liguori et al. [18]).Thus, it is highly recommended to use nonlinear analyses to obtain safer results for the critical buckling load.
|
<li> <b>AUV:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>AUV:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle
|
[
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},
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},
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},
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},
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},
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[
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[
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{
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] | null | null |
6e341e1e-055a-44e2-aeac-ffd6dc08b7fb
|
completed
| 2025-04-09T16:14:38.080009
| 2025-05-26T13:58:53.610959
|
99cb7e30-2c7d-4db5-9f5c-52f530601fd2
|
Railway curves have influence on train speed on a curve and/or wheel/rail interface. Additional forces that have to be compensated appear in the curves. The purpose of superelevation is to compensate acceleration emerging in the curve thus assuring comfortable passenger transportation and equal wearing of both rails. However, it is very difficult to calculate superelevation when designing and maintaining a railway track, because the estimation of actual train speed on the curves is very complicated. As we know, railway lines can be divided into conventional, high speed and heavy haul ones. As these lines are absolutely different, requirements for the installation and maintenance of the track may also differ. Conventional rail lines are the object of research discussed in this article. The speed of freight and passenger trains is different on conventional rail lines, which is an essential factor in determining superelevation. On the ground of scientific researches, the article analyzes and evaluates the factors influencing wheel/rail interface on the curves. The paper also deals with railway line curves, superelevation and uncompensated lateral acceleration. The article presents the method used in Lithuania for calculating superelevation in the railway curves and analyzes calculation defects. For research purposes, analytical and statistical methods have been used. The obtained results have shown that actual superelevation in the researched curves does not match the calculated one. The calculations and obtained results of superelevation depend on how average train speed in the curves is estimated and used for calculations. As most of the results show that even small variations in the curve have a great influence on track/vehicle behaviour, it is necessary to find more precise methods for calculating superelevation, evaluating actual train speed and considering permissible uncompensated lateral acceleration in the curves.
|
<li> <b>train:</b> Other Vehicle<li> <b>trains:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>train:</b> Other Vehicle<li> <b>trains:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle
|
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] | null | null |
1055d70d-83dd-4799-8a61-4100952a3865
|
completed
| 2025-04-09T16:14:38.080015
| 2025-05-26T07:58:36.932442
|
d024cb03-8e99-488a-b94e-57475c9d8c4e
|
Track geometry is very important for the behaviour of vehicles.Track geometry and track/vehicle system are usually analyzed while researching wheel-rail interface, track and vehicle system modelling, various track and rolling stock parameters and behaviour modelling, the influence of various parameters on the estimation of rail side wear, contact stresses, derailment, etc. (Jin et al. 2007(Jin et al. , 2009;;Enblom 2009;Grassie, Elkins 2005).The typical conditions used for the simulations of curving are shown in Table 1 (Polach et al. 2006).Research is sometimes carried out analyzing track degradation models and estimating the degradation of the track substructure, super-structure and track geometry (Sadeghi, Askarinejad 2007;Larsson 2004;Zhang et al. 2000).As transverse, longitudinal and vertical forces acting in the curves are markedly larger than the ones acting in the straight sections of the track, they are usually used as an object of research on estimating the influence of rail wear and track geometrical parameters on the track/vehicle system.Research substantially differs if high-speed lines with no freight traffic are analyzed and if conventional rail lines are analyzed where traffic is mixed.Speed is supposed to be the essential difference.This article discusses only conventional rail lines and their curves. Designing a railway track, a track gauge, superelevation, a transition curve, horizontal curve radius, vertical curve radius and a gradient are identified in the curves.The supervision of the railway track is very important for maintaining it because the above mentioned parameters have to be kept in their permissible limits.Therefore, allowable deviations from all these parameters are regulated.This is very important for traffic safety and for lowering the expenses of railway repair and supervision, because even small changes can sometimes cause derailment, for example, superelevation can markedly change acting forces and vehicle behaviour having a negative impact on rolling stock wheels and rail wear. Research on rail wear in the curves, wear intensity and determinant factors has disclosed that the rail wear volume greatly depends on curving speed, the geometry sizes of the track, the curvature radius of the curved track, the profiles of the wheel/rail, the dynamic characters of the vehicle and track, axle loads, material physical properties and the friction coefficient of the wheel/rail (Jin et al. 2007).For that purpose, the models of a railway vehicle coupled with a curved track are composed.Sometimes, already knowing the factors that have been determined by many researches and have a negative impact on rail wear in the curves and traffic safety (derailment probability), new researches are carried out to choose one or several geometric parameters such as the research object and to evaluate their design and supervision peculiarities (Wolf 2006;Klauser 2005).Research on the intensive formation of external rail side wear in the curve points to the following factors: uncontrolled (railway line plan and profile), partially controlled (train weight, axial loads) and controlled (train speed, rail and wheel steel toughness, wheel and rail lubrication, superelevation, gauge) (Povilaitienė, Laurinavičius 2004).Researches remain topical and necessary, because expenses concerning the maintenance of track geometry are high in all countries (Bouch et al. 2010).Although the controlled factors are analyzed, however, no concrete proposals are usually given and only a theoretical analysis of the models not including practical conclusions and proposals is done. The article looks at geometrical track parametersuperelevation the determination of which may vary in different countries; however, the essence remains the same -superelevation is calculated in respect of rated track parameters: track radius and average and/or maximum permissible rated train speed.Nevertheless, during track maintenance, the value of rated superelevation is no longer important unlike uncompensated lateral acceleration as superelevation excess, superelevation deficiency expression, equilibrium superelevation and balanced speed.Therefore, the paper primarily discusses and analyzes the influence of superelevation on wheel-rail interface.The article reviews the influence of determining superelevation on wheel/rail interface, focuses on how uncompensated lateral acceleration and other parameters have a negative impact on track and rolling stock emerge, describes the determination of superelevation and explains the importance of the value of uncompensated lateral acceleration.Lithuanian railway curves having different radii have been chosen and detailed analysis estimating the value of superelevation, speed and uncompensated lateral acceleration has been performed.Separate curves have been examined to estimate how the value of actual superelevation differs from the one calculated according to the valid methodology.The paper suggests the means that correctly calculate superelevation regulating permissible uncompensated lateral acceleration for freight trains and evaluating train speeds.
|
<li> <b>vehicles:</b> Other Vehicle<li> <b>rolling stock:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle
|
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[
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[
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] |
[
"Partially correct"
] |
[
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[
"submitted"
] |
[
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"rolling stock\" not of interest for CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
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] |
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] | null | null |
f0226ef5-aa81-4e7d-a818-e6bfd32676dc
|
completed
| 2025-04-09T16:14:38.080021
| 2025-05-26T08:56:18.081268
|
0ab4a8cd-1b90-486e-98a8-eed19fa51afb
|
As one of the internationally recognized solutions to environmental problems, electric vehicles feature zero direct emissions and can reduce dependence on petroleum. An increasing number of countries have attached importance to the electric vehicle and developed it, and it is predicted that it will become a main force in the transportation system. Hence, it is necessary to explore the factors that drive consumers to buy electric vehicles. This study analyzes the factors that influence the consumer’s intention to buy electric vehicles and tests the relationship between them, and intends to offer information for the formulation of policies designed to popularize electric vehicles in order to reduce carbon emissions from transportation. As a result, consumer attitudes are the most important factor influencing the intention to purchase electric vehicles. The greatest effect is found in this line: Brand Trust→Perceived Benefit→Attitude→Purchase Intention. This means that the brand can increase the consumer’s perceived benefit of electric vehicles, make consumers more attracted to electric vehicles, and influence their final purchase intention.
|
<li> <b>electric vehicles:</b> Car<li> <b>vehicle:</b> Other Vehicle
|
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[
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] |
[
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[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"submitted"
] |
[
"- \"electric vehicles\" are not cars exclusively\n- difference between singular and plural: \"electric vehicles\" is identified as vehicleType while in the phrase \"...electric vehicle...\" only the term \"vehicle\" is considered a vehicleType\n"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
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{
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{
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}
] | null | null |
4804b117-6afa-4715-9447-95e4f14ffe6b
|
completed
| 2025-04-09T16:14:38.080027
| 2025-05-26T08:48:19.022048
|
377807a7-203d-4f96-b42e-66e43fcaea94
|
As shown in Table 7, "Brand Trust (BT)" (b = 0.345, p < 0.001) and "New Production Knowledge (NPK)" (b = 0.103, p < 0.001) had significant impacts on "PB"; "Brand Trust (BT)" (b = -0.182,p = 0.015) had a marked effect on "Perceived Risk (PR)"; "Perceived Benefit" (PB) (b = 1.163, p < 0.001) and "Perceived Risk (PR)" (b = -0.205,p = 0.002) had a noticeable influence on "Attitude (ATT)"; "Perceived Benefit (PB)" (b = 0.385, p < 0.001) and "Attitude (ATT)" (b = 0.630, p < 0.001) exerted a remarkable effect on "Purchase Intention (PI)."The power of "Perceived Risk (PR)," "Brand Trust (BT)," and "New Production Knowledge (NPK)" to explain "Perceived Benefit (PB)" was 40.4%; the power of "Brand Trust (BT)" and "New Production Knowledge (NPK)" to explain "Perceived Risk (PR)" was 3.3%; the power of "Perceived Benefit (PB)" and "Perceived Risk (PR)" to explain "Attitude (ATT)" was 44.6%; the power of "Perceived Benefit (PB)," "Perceived Risk (PR)," and "Attitude (ATT)" to explain "Purchase Intention (PI)" was 62.3%.It is obvious that the research results support the model and research questions of this study.
|
None
|
[
[]
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"submitted"
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"Correct"
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[] | null | null |
e7a50267-10fa-4ae3-8a7b-124934aa4bfe
|
completed
| 2025-04-09T16:14:38.080033
| 2025-05-13T06:09:38.790828
|
6d2749d1-c28f-48c5-9589-6ff08b261eee
|
The aim of this article is to describe estimates of data difficulty and aspects of the data viewpoint within Vehicle-to-Infrastructure (V2I) communication in the Smart Mobility concept. The historical development of the database system’s architecture, that stores and processes a larger amount of data, is currently sufficient and effective for the needs of today’s society. The goal of vehicle manufacturers is the continual increase in driving comfort and the use of multiple sensors to sense the vehicle’s surroundings, as well as to help the driver in critical situations avoid danger. The increasing number of sensors is directly related to the amount of data generated by the vehicle. In the automotive industry, it is crucial that autonomous vehicles can process data in real time or can locate itself in precise accuracy, for the decision-making process. To meet these requirements, we will describe HD maps as a key segment of autonomous control. It alerts the reader to the need to address the issue of real-time Big Data processing, which represents an important role in the concept of Smart Mobility.
|
<li> <b>Vehicle-to-Infrastructure (V2I):</b> V2I<li> <b>vehicle:</b> Other Vehicle<li> <b>sensors:</b> Other Sensor<li> <b>autonomous vehicles:</b> Other Vehicle
|
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[
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[
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] |
[
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] |
[
null
] |
[
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] |
[
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] |
[
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{
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},
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}
] | null | null |
387240fe-cbc2-4672-9406-8f65af958b4f
|
completed
| 2025-04-09T16:14:38.080039
| 2025-05-13T06:25:43.600601
|
78e38ed0-db03-4c20-9534-879d256eb19e
|
Meeting the objectives defined in the Smart Mobility concept will bring several key solutions that should ensure a higher level of traffic using advanced information and communication technologies.Travel will be easier and smoother, traffic management efficiency will be increased and information on traffic intensity will be provided over time, which will allow prediction and optimization of planning and information on free parking spaces will be available.The overall architecture and mode of shared transport will be proposed, which will affect every single inhabitant of the city.The aim of the transformation is primarily to turn transport as a product into a mobility service (Mobility-as-a-Service). Mobility services will be a part of the lives of residents.As the population increases, it is important to effectively design a mode of transport for many people in a limited range of the physical capacity of the transport infrastructure.It is also important to respect the degree of environmental friendliness of the means of transport, together with sustainability.The introduction of low-emission and emission-free zones will bring a new perspective on shared transport, where bicycles and scooters will not only be an exceptional transport option but a common part of people's daily lives. With the advent of new technologies in the automotive industry, we are increasingly faced with the concept of autonomous vehicles, which are often seen as an important element of Smart Mobility. The definition of an autonomous vehicle (AV) can be understood as a vehicle capable of sensing the surrounding environment, evaluating the traffic situation and performing activities and maneuvers without the need for human intervention.It is not at all necessary for a person to take control of the vehicle or to be in the vehicle at all.An AV is able to drive on the same roads, evaluate traffic situations (react more quickly in crisis situations), do everything as an experienced human driver.The SAE has defined six levels of driving automation-from level 0 (fully manual) to level 5 (full autonomy) [16].These six categories are divided into two groups of three levels.The first group consists of levels 0-2 inclusive, where the driver monitors the environment around him.The second group are levels 3-5 inclusive, where the environment is monitored by an automated system capable of reacting in time based on the information obtained (Figure 3).munication technologies.Travel will be easier and smoother, traffic management effi-ciency will be increased and information on traffic intensity will be provided over time, which will allow prediction and optimization of planning and information on free parking spaces will be available.The overall architecture and mode of shared transport will be proposed, which will affect every single inhabitant of the city.The aim of the transformation is primarily to turn transport as a product into a mobility service (Mobility-as-a-Service). Mobility services will be a part of the lives of residents.As the population increases, it is important to effectively design a mode of transport for many people in a limited range of the physical capacity of the transport infrastructure.It is also important to respect the degree of environmental friendliness of the means of transport, together with sustainability.The introduction of low-emission and emission-free zones will bring a new perspective on shared transport, where bicycles and scooters will not only be an exceptional transport option but a common part of people's daily lives. With the advent of new technologies in the automotive industry, we are increasingly faced with the concept of autonomous vehicles, which are often seen as an important element of Smart Mobility. The definition of an autonomous vehicle (AV) can be understood as a vehicle capable of sensing the surrounding environment, evaluating the traffic situation and performing activities and maneuvers without the need for human intervention.It is not at all necessary for a person to take control of the vehicle or to be in the vehicle at all.An AV is able to drive on the same roads, evaluate traffic situations (react more quickly in crisis situations), do everything as an experienced human driver.The SAE has defined six levels of driving automation-from level 0 (fully manual) to level 5 (full autonomy) [16].These six categories are divided into two groups of three levels.The first group consists of levels 0-2 inclusive, where the driver monitors the environment around him.The second group are levels 3-5 inclusive, where the environment is monitored by an automated system capable of reacting in time based on the information obtained (Figure 3).The development of technologies to support autonomous vehicles and their future is exciting.Technological backgrounds, radars and sensors receive a wealth of support in their improvement, use and adjustment.According to a published study by the Ponemon Institute entitled "Securing the Connected Car: A Study of Automotive Industry Cybersecurity Practices", connected vehicles (as well as autonomous vehicles) have a rich background in physical safety (seat belts, airbags and others).Today, physical safety is relatively well covered, as is also reported in the annual decrease in road accident deaths based on European Commission statistics (Figure 4) [18].
|
<li> <b>bicycles:</b> Cyclist<li> <b>scooters:</b> Electric Scooter / Moped User<li> <b>autonomous vehicles:</b> Other Vehicle<li> <b>autonomous vehicle (AV):</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>AV:</b> Other Vehicle<li> <b>level 0:</b> Level 0<li> <b>level 5:</b> Level 5<li> <b>levels 0-2:</b> Other Level of Automation<li> <b>levels 3-5:</b> Other Level of Automation<li> <b>radars:</b> Radar<li> <b>sensors:</b> Other Sensor<li> <b>vehicles:</b> Other Vehicle
|
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},
{
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"label": "vehicleType",
"start": 5128
}
] | null | null |
ddf5bd07-bc37-4e8e-b501-7fd2db56f473
|
completed
| 2025-04-09T16:14:38.080046
| 2025-05-26T07:01:34.097557
|
ffa09eca-ff96-44f1-a1f7-319f71b5a82c
|
Older drivers are at increased risk of intersection crashes. Previous work found that older drivers execute less frequent glances for detecting potential threats at intersections than middle-aged drivers. Yet, earlier work has also shown that an active training program doubled the frequency of these glances among older drivers, suggesting that these effects are not necessarily due to age-related functional declines. In light of findings, the current study sought to explore the ability of older drivers to coordinate their head and eye movements while simultaneously steering the vehicle as well as their glance behavior at intersections. In a driving simulator, older (M = 76 yrs) and middle-aged (M = 58 yrs) drivers completed different driving tasks: (1) travelling straight on a highway while scanning for peripheral information (a visual search task) and (2) navigating intersections with areas potential hazard. The results replicate that the older drivers did not execute glances for potential threats to the sides when turning at intersections as frequently as the middle-aged drivers. Furthermore, the results demonstrate costs of performing two concurrent tasks, highway driving and visual search task on the side displays: the older drivers performed more poorly on the visual search task and needed to correct their steering positions more compared to the middle-aged counterparts. The findings are consistent with the predictions and discussed in terms of a decoupling hypothesis, providing an account for the effects of the active training program.
|
<li> <b>intersections:</b> Other Scenario<li> <b>intersection:</b> Other Scenario<li> <b>vehicle:</b> Other Vehicle
|
[
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[
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[
null
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] |
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{
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}
] | null | null |
d2894f1d-87b5-4e30-91d9-3d9f88e85ff0
|
completed
| 2025-04-09T16:14:38.080052
| 2025-05-20T14:43:22.594154
|
3c9bdeda-04a0-4e37-ac88-27b80f8e32ca
|
Proportion of primary glances.Consistent with the previous report [18], older drivers made statistically significantly smaller proportion of correct primary glances than middle-aged drivers [M = 70% vs. 94%; t (22) = 3.04, p < .01]. Proportion of secondary glances.Consistent with the previous reports [16,18], older drivers executed statistically significantly fewer secondary glances than middle-aged drivers [M = 31% vs. 64%; t (22) = 2.78, p = .01].Moreover, the percentage of secondary glances of the older drivers was roughly half that of the middle-aged drivers.Target detection rates in the visual search task.In the driving scenarios (Task 2), mean target detection rates were lower for older drivers than middle-aged drivers [M = 0.58 vs. 0.78; F (1,22) = 6.77, p = 0.02, MSE = 0.07, η 2 p = 0.24].The presence of wind turbulence numerically decreased the detection rates, but the main and interaction effects were not reliable [both ps > 0.55].False alarm rates were low for both middle-aged and older drivers (0 vs. 0.008, n.s.). Baseline (Static) Proportion correct detections in the visual search task.When performing the visual search task only, mean proportion correct detections were not statistically significantly different between older and middle-aged drivers [M = 0.79 vs. 0.91, t (22) = 1.12, p = 0.28].
|
None
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
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[
"submitted"
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[
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[
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[
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[
null
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] |
[
"submitted"
] |
[] | null | null |
ee9c25a6-6154-46f6-afc5-52e6f7cb86f3
|
completed
| 2025-04-09T16:14:38.080058
| 2025-05-26T14:25:20.096887
|
44c4a0fd-f5c0-4a8e-864c-02dd213640bf
|
In order to promote low-carbon fuels such as hydrogen to decarbonize the maritime sector, it is crucial to promote clean fuels and zero-emission propulsion systems in demonstrative projects and to showcase innovative technologies such as fuel cells in vessels operating in local public transport that could increase general audience acceptability thanks to their showcase potential. In this study, a short sea journey ferry used in the port of Genova as a public transport vehicle is analyzed to evaluate a ”zero emission propulsion” retrofitting process. In the paper, different types of solutions (batteries, proton exchange membrane fuel cell (PEMFC), solid oxide fuel cell (SOFC)) and fuels (hydrogen, ammonia, natural gas, and methanol) are investigated to identify the most feasible technology to be implemented onboard according to different aspects: ferry daily journey and scheduling, available volumes and spaces, propulsion power needs, energy storage/fuel tank capacity needed, economics, etc. The paper presents a multi-aspect analysis that resulted in the identification of the hydrogen-powered PEMFC as the best clean power system to guarantee, for this specific case study, a suitable retrofitting of the vessel that could guarantee a zero-emission journey.
|
<li> <b>vessels:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>vessel:</b> Other Vehicle
|
[
[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"vessels\" not of interest to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
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},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
"start": 1221
}
] | null | null |
d35754a2-a06b-45a9-a80c-949ef56562b1
|
completed
| 2025-04-09T16:14:38.080064
| 2025-05-20T12:07:26.454613
|
df2665be-f4fb-4343-9357-bf194b62134b
|
The paper presents a multi-aspect analysis to determine the most feasible clean power system to be implemented onboard the case study according to different aspects: ferry daily journey and scheduling, available volumes and spaces, propulsion power needs, energy storage/fuel tank capacity needed, economics, etc. Different types of clean power systems (batteries, PEMFC, and SOFC) are proposed to be investigated to assess and evaluate their effectiveness onboard from an economic and design perspective.Therefore, this target can be investigated and accomplished by using the following methodology as shown in Figure 4.The first step is to consider the input data at the start of the assessment procedu including the ship design specifications (available volumes, surface, weights), the sh operational profile based on voyage details, daily journey/scheduling, and the power r quirements.Second, the power system boundaries in terms of its power capacity nee The first step is to consider the input data at the start of the assessment procedure including the ship design specifications (available volumes, surface, weights), the ship operational profile based on voyage details, daily journey/scheduling, and the power requirements.Second, the power system boundaries in terms of its power capacity needs and fuel needs must be determined and it must be identified whether it is a FC-based system or a full battery electric power system.This step includes the identification of the methods to evaluate the energy requirement and fuel mass for the identified power system.The energy requirements for each potential clean power system scenario are then determined using an energy analysis.After that, the feasibility assessment is divided into economic and design aspects, the latter one intends to look at volume/spaces onboard and assess the clean power system's weight and volume, while the economic feasibility aspect is applied to the case study considering the total costs that contain capital expenses (CapEx), operational expenses (OpEx), and voyage expenses (VoyEx).Followed by a systematic comparison process that will be studied by using cost assessment indicators (CAI) as shown in Figure 5.The first step is to consider the input data at the start of the assessment procedure including the ship design specifications (available volumes, surface, weights), the ship operational profile based on voyage details, daily journey/scheduling, and the power requirements.Second, the power system boundaries in terms of its power capacity needs and fuel needs must be determined and it must be identified whether it is a FC-based system or a full battery electric power system.This step includes the identification of the methods to evaluate the energy requirement and fuel mass for the identified power system.The energy requirements for each potential clean power system scenario are then determined using an energy analysis.After that, the feasibility assessment is divided into economic and design aspects, the latter one intends to look at volume/spaces onboard and assess the clean power system's weight and volume, while the economic feasibility aspect is applied to the case study considering the total costs that contain capital expenses (CapEx), operational expenses (OpEx), and voyage expenses (VoyEx).Followed by a systematic comparison process that will be studied by using cost assessment indicators (CAI) as shown in Figure 5.These indicators are used to quantify and reflect the performance of the power system from an economical perspective such as NPV, LCOE, ROI, and MAC.The last step of the assessment methodology is to present the results of the multi-aspect analysis and identify the best clean power system to guarantee a suitable retrofitting of the vessel and pledge a zero-emission journey to the ferry.
|
<li> <b>ship:</b> Other Vehicle<li> <b>vessel:</b> Other Vehicle<li> <b>ferry:</b> Other Vehicle
|
[
[]
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"Incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
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[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"ship\", \"vessel\" and \"ferry\" are not of interest to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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},
{
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}
] | null | null |
f22bdc8f-cec4-483d-b1ea-3e424dbebe2d
|
completed
| 2025-04-09T16:14:38.080070
| 2025-05-26T13:45:49.463413
|
bcbd91db-506b-4ead-8b10-8d4bcb609608
|
This paper presents a numerical study of the depth tracking control for an underwater towed system under wave–ship interference condition. To overcome the laminations of ignoring the hydrodynamic factors and wave–ship interference in the existing simulation model for the depth tracking operation of the underwater towed system, a numerical model combining the control system with the computational fluid dynamics (CFD) method based on the overset mesh technique is explored and constructed; the influence of towing ship and head waves is introduced into the numerical analysis of the underwater towed system; a depth control system based on the center of gravity adjustment is proposed and its control characteristics are discussed. The fluid motion around the towed vehicle and the towing ship is governed by the Navier–Stokes equations, and the overset mesh technique is applied for the numerical solution of the equations. The towing cable connecting the towed vehicle and towing ship is governed by the quasi-steady-state catenary equations. The depth tracking controller adjusting the longitudinal position of a shifting weight is constructed based on the proportional–integral–derivative (PID) algorithm. The simulation results show that the numerical simulation system is practicable, and the depth tracking control system is feasible, effective, and robust.
|
<li> <b>underwater towed system:</b> Other Vehicle<li> <b>ship:</b> Other Vehicle<li> <b>towing ship:</b> Other Vehicle<li> <b>towed vehicle:</b> Other Vehicle
|
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]
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[
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[
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[
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[
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] |
[
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] |
[
"\"ship\", \"towing ship\" and \"underwater towed system\" are not of interest to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
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},
{
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"start": 959
}
] | null | null |
ea7e92ab-c4d1-43f9-bafa-a10db6f33cd9
|
completed
| 2025-04-09T16:14:38.080076
| 2025-05-26T13:41:44.183602
|
dbffff6c-61cb-4e6f-a54c-4d703906c14b
|
The amplitude of the instantaneous vertical trajectory of the towed vehicle under the system's control was equivalent to that of the non-control condition, and the fluctuation was not worsened by the disturbance of the trajectory tracking control in the head waves.
|
<li> <b>towed vehicle:</b> Other Vehicle
|
[
[
{
"end": 75,
"label": "vehicleType",
"start": 62
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 75,
"label": "vehicleType",
"start": 62
}
] | null | null |
46d4cf2e-1e56-4ad9-a456-371b35e3ef3e
|
completed
| 2025-04-09T16:14:38.080082
| 2025-05-26T14:26:16.205976
|
28029e05-ebff-4028-b8ae-282a36ddab14
|
To solve the problem of the real-time path-planning of autonomous vehicles for obstacle avoidance on structured roads, a path-planning approach based on the B-spline algorithm is proposed in this paper. Firstly, the mechanism of driver path planning is analyzed, and a dynamic risk-identification model based on the support vector machine is proposed. It combines the driver’s risk perception characteristics and a risk model. Then, the B-spline algorithm model is improved based on the risk-identification model. Furthermore, road features, road constraints and dynamic constraints are considered to further optimize the planning algorithm. To verify the path-planning approach proposed in this paper, a co-simulation experiment based on CarSim/Simulink is conducted. Results show that the improved algorithm is effective in static and dynamic obstacles avoidance. The algorithm can generate collision-free obstacle avoidance paths, and the paths meet the real-time requirements and dynamic constraints of obstacle avoidance scenarios. In addition, the proposed algorithm optimizes the path according to the driver’s operating characteristics, which can further improve the safety and comfort of autonomous vehicles.
|
<li> <b>autonomous vehicles:</b> Other Vehicle
|
[
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{
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 74,
"label": "vehicleType",
"start": 55
},
{
"end": 1216,
"label": "vehicleType",
"start": 1197
}
] | null | null |
8e9600bb-154e-43a5-b037-d093050b04ca
|
completed
| 2025-04-09T16:14:38.080088
| 2025-05-20T11:29:13.913953
|
70f71c5a-3bb8-4a33-939c-ab3fcace07fd
|
The path-planning algorithm for autonomous vehicles should not only meet the requirements of a collision-free path, but also meets the requirements of path smoothness.The generated paths are smooth and can be tracked by autonomous vehicles.The generated path should conform to the dynamic constraints of the vehicle.Therefore, it is necessary to further verify the availability of the generation paths.The effectiveness of the path generated by the obstacle avoidance path algorithm can be fully verified through real vehicle experiments.However, due to the high cost of real vehicle experiments and the risk of real vehicle high-speed path tracking experiments, most path availability experiments are currently completed through Co-simulation experiments. In order to verify the path availability, a path tracking model based on a Linear Quadratic Regulator (LQR) approach for autonomous vehicles is established in this paper.This method mainly obtains the optimal control effect by solving the state space equation and performance index function of the system [19].The tracking control system in this paper consists of a prediction module, an error calculation module, a feedback coefficient calculation module, a feedforward control module and a front-wheel-angle control module.The tracking system calculates the next vehicle state according to the current vehicle position, speed, yaw angle, yaw rate and other parameters.Then, the calculated vehicle state is compared with the tracking path parameters to obtain the error.Finally, the error is combined with the feedback coefficient and feedforward value obtained from the vehicle steering index to control the front wheel angle of the vehicle. Combined with the two-degree-of-freedom vehicle dynamics model, the state space of the vehicle error model can be expressed as: . where: where C ∂ f is the front wheel steering stiffness, C ∂r is the rear wheel steering stiffness, u is the front wheel angle, m is the vehicle mass, ϕ is the vehicle yaw angle and θ is the course angle of the vehicle speed at the projection point under the Frenet coordinate system. . θ is the course angle derivative of vehicle speed at the projection point in the Frenet coordinate system.v x is the longitudinal speed of the vehicle.a is the distance from the front axle to the barycenter.b is the distance from the rear axle to the barycenter.e d is the lateral error. . e d is the derivative of lateral error.I z is the moment of inertia of the vehicle about the z-axis perpendicular to the ground. Due to the discrete LQR control mode in this paper, Equation ( 16) needs to be discretized.Ignoring C .θ, the formula can be expressed as: . e = Ae + Bu, Then, after discretization of the formula, the following formula is obtained: where: where I is the identity matrix.By establishing the following cost function: where Q and R are the diagonal matrix, the parameter represents the weight coefficient of each variable.By calculating its minimum value under the constraint of Equation (23), then: where , it is called the feedback coefficient.P is obtained by the Riccati formula constructed in the solution process through multiple iterations.The Riccati formula is: when u =ke, the formula of ( 16) can be converted into: . In this formula, . e and e cannot be zero at the same time; that is, the error cannot be kept to zero during vehicle driving.Therefore, it needs the feedforward control part to optimize.The following formula is established: where δ f is the feedforward control part.So To satisfy that e is as zero as possible when . e is zero, after approximating some values, then: where K is the curvature of the curve. In order to verify the availability of the generated path, a steering control module for autonomous vehicles based on LQR is established in this paper.Then, based on the proposed LQR tracking control algorithm, the MATLAB/CarSim Co-simulation experiments are carried out.For the four obstacle avoidance scenarios in this paper, the scenario of ego-vehicle to avoid dynamic obstacles requires high smoothness of the path.Therefore, a series of co-simulation tests are conducted to verify the availability of the generated paths.In the test scenarios, the speed of the obstacle vehicle is 10 km/h, and the controlled vehicle runs along the planned path at 35 km/h and 70 km/h, respectively.The ego-vehicle detects the obstacle and completes obstacle avoidance, and returns to the original lane after overtaking the obstacle vehicle.The proposed path-planning module generates the obstacle avoidance path according to the obstacle vehicle and environmental information, and the controlled vehicle tracks the generated path based on the proposed LQR algorithm.The simulation parameters of controlled vehicle are shown in Table 1.The steering wheel angle curve of the vehicle during the simulation is shown in Figure 9.The steering wheel angle curve is smooth and continuous without oscillation and sudden change.The simulation results show that the generated path is available and conforms to the operating characteristics of human drivers. Electr.Veh.J. 2022, 13, x FOR PEER REVIEW and the controlled vehicle tracks the generated path based on the prop rithm.The simulation parameters of controlled vehicle are shown in Tab The steering wheel angle curve of the vehicle during the simulation ure 9.The steering wheel angle curve is smooth and continuous withou sudden change.The simulation results show that the generated path is a forms to the operating characteristics of human drivers.Figure 11 shows the lateral acceleration curve of the controlled vehic the figure, when the controlled vehicle avoids obstacles at a speed of 70 k acceleration of the vehicle is large, and the maximum acceleration is 3.65 m ulation scenario, the vehicle is running on a dry asphalt road.In order to vehicle tires are in a linear working area, the maximum lateral acceleration than 3.92 m/s 2 (0.4 times of the gravitational acceleration).The small late ensures the stability and comfort of the vehicle and proves the availability Figure 11 shows the lateral acceleration curve of the controlled vehicle.As shown in the figure, when the controlled vehicle avoids obstacles at a speed of 70 km/h, the lateral acceleration of the vehicle is large, and the maximum acceleration is 3.65 m/s 2 .In this simulation scenario, the vehicle is running on a dry asphalt road.In order to ensure that the vehicle tires are in a linear working area, the maximum lateral acceleration should be less than 3.92 m/s 2 (0.4 times of the gravitational acceleration).The small lateral acceleration ensures the stability and comfort of the vehicle and proves the availability of the path.The simulation results show that the paths generated by the path-p are collision free in both scenarios, and the controlled vehicle can accurate The simulation results show that the paths generated by the path-planning module are collision free in both scenarios, and the controlled vehicle can accurately track the generated reference path at speeds of 35 km/h and 70 km/h.The key dynamic parameters of the vehicle in the simulation process are analyzed.The results show that the controlled vehicle can ensure the vehicle handling stability when tracking the generated obstacle avoidance paths.The relatively small lateral acceleration can also ensure the driving comfort of the controlled vehicle, and can meet the vehicle dynamics constraints and lane constraints.All results prove that the proposed path-planning algorithm is consistent with the expected lane change results, and it meets the requirements of autonomous vehicle obstacle avoidance path planning.
|
<li> <b>autonomous vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>vehicles:</b> Other Vehicle<li> <b>ego-vehicle:</b> Other Vehicle<li> <b>obstacle vehicle:</b> Other Vehicle<li> <b>controlled vehicle:</b> Other Vehicle
|
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
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[
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] |
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[
"submitted"
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[
null
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] | null | null |
475d4354-519a-484c-bfca-63ae06bd1279
|
completed
| 2025-04-09T16:14:38.080433
| 2025-05-13T06:19:11.183157
|
8bb533ed-8b7d-41db-943d-b678efe522d6
|
Electric vehicles (EVs) have become increasingly popular because they are highly efficient and sustainable. However, EVs have intensive electric loads. Their penetrations into the power system pose significant challenges to the operation and control of the power distribution system, such as a voltage drop or transformer overloading. Therefore, grid operators need to prepare for high-level EV penetration into the power system. This study proposes data-driven, parameterized, individual, and aggregated EV charging models to predict EV charging loads in the urban residential sector. Actual EV charging profiles in Saskatchewan, Canada, were analyzed to understand the characteristics of EV charging. A location-based algorithm was developed to identify residential EV charging from raw data. The residential EV charging data were then used to tune the EV charging model parameters, including battery capacity, charging power level, start charging time, daily EV charging energy, and the initial state of charge (SOC). These parameters were modeled by random variables using statistic methods, such as the Burr distribution, the uniform distribution, and the inverse transformation methods. The Monte Carlo method was used for EV charging aggregation. The simulation results show that the proposed models are valid, accurate, and robust. The EV charging models can predict the EV charging loads in various future scenarios, such as different EV numbers, initial SOC, charging levels, and EV types (e.g., electric trucks). The EV charging models can be embedded into load flow studies to evaluate the impact of EV penetration on the power distribution systems, e.g., sustained under voltage, line loss, and transformer overloading. Although the proposed EV charging models are based on Saskatchewan’s situation, the model parameters can be tuned using other actual data so that the proposed model can be widely applied in different cities or countries.
|
<li> <b>Electric vehicles (EVs):</b> Car<li> <b>EVs:</b> Car<li> <b>EV:</b> Car<li> <b>electric trucks:</b> Truck
|
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},
{
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},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
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},
{
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"start": 1506
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
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"label": "vehicleType",
"start": 0
},
{
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"label": "vehicleType",
"start": 19
},
{
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{
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},
{
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},
{
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"start": 535
},
{
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"label": "vehicleType",
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},
{
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},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
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},
{
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},
{
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"start": 962
},
{
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"label": "vehicleType",
"start": 1229
},
{
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"label": "vehicleType",
"start": 1344
},
{
"end": 1381,
"label": "vehicleType",
"start": 1379
},
{
"end": 1446,
"label": "vehicleType",
"start": 1444
},
{
"end": 1492,
"label": "vehicleType",
"start": 1490
},
{
"end": 1530,
"label": "vehicleType",
"start": 1528
},
{
"end": 1614,
"label": "vehicleType",
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},
{
"end": 1757,
"label": "vehicleType",
"start": 1755
},
{
"end": 1521,
"label": "vehicleType",
"start": 1506
}
] | null | null |
a9d36487-692b-4dd3-ae70-8c872b7f7c06
|
completed
| 2025-04-09T16:14:38.080440
| 2025-05-26T13:42:40.611605
|
bce8dad4-3e8d-44f5-a629-164e65a714a4
|
To build the individual EV charging model, various parameters that depend on the EV owners charging habits have been analyzed and tuned.These parameters include EV battery capacity, rated charging power, start charging time, daily energy consumption, and initial SOC.Various statistical methods, such as the Burr distribution, normal distribution, and the inverse transform sampling method were used to capture the distribution of each parameter and generate the individual EV charging model.Then, the Monte Carlo simulation was used to build the aggregated EV charging model. In the proposed model, various types of EVs with various capacities were utilized.The simulation period was one day, and the time interval was 5 minutes.In the simulation, the EVs were charged up to 90%, i.e., the final SOC was 90%.
|
<li> <b>EV:</b> Car<li> <b>EVs:</b> Car
|
[
[
{
"end": 26,
"label": "vehicleType",
"start": 24
},
{
"end": 83,
"label": "vehicleType",
"start": 81
},
{
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"label": "vehicleType",
"start": 161
},
{
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"label": "vehicleType",
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},
{
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},
{
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"label": "vehicleType",
"start": 617
},
{
"end": 756,
"label": "vehicleType",
"start": 753
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EVs\" may include other vehicles besides cars as well (2-wheelers, 3-wheelers, minivans, etc.)"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 26,
"label": "vehicleType",
"start": 24
},
{
"end": 83,
"label": "vehicleType",
"start": 81
},
{
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"label": "vehicleType",
"start": 161
},
{
"end": 476,
"label": "vehicleType",
"start": 474
},
{
"end": 560,
"label": "vehicleType",
"start": 558
},
{
"end": 620,
"label": "vehicleType",
"start": 617
},
{
"end": 756,
"label": "vehicleType",
"start": 753
}
] | null | null |
886dbed1-d943-4cff-8b00-ec53a9067ceb
|
completed
| 2025-04-09T16:14:38.080446
| 2025-05-26T08:57:37.356082
|
55cd3799-23b7-4037-a9c1-926085cbc87a
|
Freight transportation is a crucial part of the global economy, but it encounters several complex challenges, with truck drivers at the centre of these issues. These professionals, responsible for transporting goods over long distances, often work in challenging conditions, exposing them to a range of risks, including physical, psychological, and chemical hazards. These risks make the profession less appealing to younger drivers, leading to an ageing workforce and worsening the driver shortage crisis in the road transport sector. This article aims to identify the various risks faced by truck drivers and examine their negative impacts on several critical aspects, including company image, service quality, financial implications, and road safety. Additionally, the article explores the transformative impact of the Internet of Things (IoT) and autonomous vehicles (AV) on the truck driving profession.
|
<li> <b>truck drivers:</b> Truck<li> <b>truck:</b> Truck<li> <b>autonomous vehicles (AV):</b> Other Vehicle
|
[
[
{
"end": 120,
"label": "vehicleType",
"start": 115
},
{
"end": 598,
"label": "vehicleType",
"start": 593
},
{
"end": 888,
"label": "vehicleType",
"start": 883
},
{
"end": 875,
"label": "vehicleType",
"start": 851
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"truck driver\" should not be considered as a vehicleType (it is sufficient to assign the term \"truck\")"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 128,
"label": "vehicleType",
"start": 115
},
{
"end": 606,
"label": "vehicleType",
"start": 593
},
{
"end": 120,
"label": "vehicleType",
"start": 115
},
{
"end": 598,
"label": "vehicleType",
"start": 593
},
{
"end": 888,
"label": "vehicleType",
"start": 883
},
{
"end": 875,
"label": "vehicleType",
"start": 851
}
] | null | null |
8d4d0514-4318-42c8-85ab-592e2f2f32af
|
completed
| 2025-04-09T16:14:38.080452
| 2025-05-13T05:38:47.001357
|
6ca87033-c4b6-4ccf-a05b-c9790c1f28ea
|
The profession of heavy goods vehicle (HGV) driver involves significant physical risks that necessitate special attention to ensure the safety and well-being of the drivers.These risks include musculoskeletal disorders affecting the musculoskeletal system, cardiovascular diseases such as heart attacks, and digestive issues like gastritis.These conditions are common among HGV drivers and can lead to occupational disability.Additionally, slips, trips, falls from heights, road accidents, and accidents on loading docks contribute to many injuries among these professionals.
|
<li> <b>heavy goods vehicle (HGV):</b> Truck<li> <b>HGV drivers:</b> Truck
|
[
[
{
"end": 43,
"label": "vehicleType",
"start": 18
},
{
"end": 377,
"label": "vehicleType",
"start": 374
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"The second instance should not include the term \"drivers\". So, only HGV should be linked to Truck"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 43,
"label": "vehicleType",
"start": 18
},
{
"end": 385,
"label": "vehicleType",
"start": 374
}
] | null | null |
ccf7c5bd-9e26-4b24-8c6e-38152f6e321d
|
completed
| 2025-04-09T16:14:38.080458
| 2025-05-26T13:38:55.575975
|
b38c7985-c0fe-491c-81b2-ed9131377ab9
|
Bus rapid transit (BRT) is one of the strategies to promote improvements in urban mobility. In this study, BRT scenarios, which integrate exclusive bus lanes and bus priority signal control in mixed traffic scenarios, were modelled using a VISSIM microsimulation. Three scenarios of BRT were modelled to represent 16:84, 38:62 and 54:46 modal splits between public transport and private vehicles. It was found that Scenario 4 (the 54:46 scenario) offers better benefits in terms of delay time saving and economic benefits. In general, it was found that the BRT system enhances the functioning of the transport system and provides people with faster and better mobility facilities, resulting in attractive social and economic benefits, especially on a higher modal split of public transport. It is regarded as one strategy to alleviate traffic congestion and reduce dependency on private vehicles. The finding of this study provides an insight on the effective concept of the BRT system, which may promote the dissemination of an urban mobility solution in the city. The results can help policymakers and local authorities in the management of a transport network in order to ensure reliable and sustainable transport.
|
<li> <b>Bus rapid transit (BRT):</b> Bus<li> <b>bus:</b> Bus<li> <b>BRT:</b> Bus<li> <b>public transport:</b> Bus<li> <b>private vehicles:</b> Other Vehicle
|
[
[
{
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},
{
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"label": "vehicleType",
"start": 148
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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{
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"label": "vehicleType",
"start": 379
},
{
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"label": "vehicleType",
"start": 879
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"public transport\" is not identical to bus in the context of vehicleType"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
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"start": 0
},
{
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"label": "vehicleType",
"start": 148
},
{
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},
{
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"start": 19
},
{
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},
{
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"label": "vehicleType",
"start": 283
},
{
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"label": "vehicleType",
"start": 557
},
{
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"label": "vehicleType",
"start": 975
},
{
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"label": "vehicleType",
"start": 358
},
{
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"label": "vehicleType",
"start": 773
},
{
"end": 395,
"label": "vehicleType",
"start": 379
},
{
"end": 895,
"label": "vehicleType",
"start": 879
}
] | null | null |
d9d50211-6e6e-4c9f-9752-380d2fdb1437
|
completed
| 2025-04-09T16:14:38.080464
| 2025-05-19T11:03:32.423855
|
a4bd0348-c5fc-486f-9427-c222c7d54a58
|
The proposed BRT system at the junction has a dedicated BRT lane with signal ority in mixed traffic scenarios.In the BRT scenarios, the road section is widened to commodate an additional 9 m lane width for two-way directions of BRT.The media the existing layout is replaced with a BRT lane.The existing geometrical layout o junction such as the number of lanes and turning movements remains unchanged parameters such as driving behaviour, lane-changing behaviour, reduced speed areas simulation run parameters are same as the base case model.The occupancy of the ve was 1.21, 1.41 and 10.54 for motorcycles, passenger cars and buses, respectively [43].layout of the BRT scenario on the road network is shown in a red-painted road segm in Figure 8. Traffic volume and speed data for both field data and simulated data were compared, as shown in Figure 7.The RSMPE and the GEH values for both traffic parameters are within the validation threshold of 5% and 3%, respectively; hence the base model was validated [48].A calibrated and validated model is essential in model development to ensure a valid and reliable evaluation [56][57][58].The calibrated and validated base case model was then expanded further to model the bus rapid transit (BRT) strategies.
|
<li> <b>BRT:</b> Bus<li> <b>motorcycles:</b> Motorcycle<li> <b>passenger cars:</b> Car<li> <b>buses:</b> Bus<li> <b>bus rapid transit (BRT):</b> Bus
|
[
[
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
"start": 56
},
{
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"label": "vehicleType",
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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"label": "scenarioType",
"start": 117
},
{
"end": 678,
"label": "scenarioType",
"start": 666
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 16,
"label": "vehicleType",
"start": 13
},
{
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"label": "vehicleType",
"start": 56
},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
"start": 666
},
{
"end": 1242,
"label": "vehicleType",
"start": 1239
},
{
"end": 606,
"label": "vehicleType",
"start": 595
},
{
"end": 622,
"label": "vehicleType",
"start": 608
},
{
"end": 632,
"label": "vehicleType",
"start": 627
},
{
"end": 1243,
"label": "vehicleType",
"start": 1220
}
] | null | null |
56b7377e-6322-49fd-92b4-f7f3e0caba4c
|
completed
| 2025-04-09T16:14:38.080470
| 2025-05-19T08:28:21.206974
|
6c2c5fb6-77b1-4c2a-824f-1f1c94b610f0
|
Lithium-ion batteries are considered the most suitable option for powering electric vehicles in modern transportation systems due to their high energy density, high energy efficiency, long cycle life, and low weight. Nonetheless, several safety concerns and their tendency to lose charge over time demand methods capable of determining their state of health accurately, as well as estimating a range of relevant parameters in order to ensure their safe and efficient use. In this framework, non-destructive inspection methods play a fundamental role in assessing the condition of lithium-ion batteries, allowing for their thorough examination without causing any damage. This aspect is particularly crucial when batteries are exploited in critical applications and when evaluating the potential second life usage of the cells. This review explores various non-destructive methods for evaluating lithium batteries, i.e., electrochemical impedance spectroscopy, infrared thermography, X-ray computed tomography and ultrasonic testing, considers and compares several aspects such as sensitivity, flexibility, accuracy, complexity, industrial applicability, and cost. Hence, this work aims at providing academic and industrial professionals with a tool for choosing the most appropriate methodology for a given application.
|
<li> <b>electric vehicles:</b> Car<li> <b>infrared thermography:</b> Other Sensor<li> <b>X-ray computed tomography:</b> Other Sensor<li> <b>ultrasonic testing:</b> Other Sensor
|
[
[
{
"end": 92,
"label": "vehicleType",
"start": 75
},
{
"end": 1031,
"label": "sensorType",
"start": 1013
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"infrared thermography, X-Ray --> sensors not related to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 92,
"label": "vehicleType",
"start": 75
},
{
"end": 981,
"label": "sensorType",
"start": 960
},
{
"end": 1008,
"label": "sensorType",
"start": 983
},
{
"end": 1031,
"label": "sensorType",
"start": 1013
}
] | null | null |
e169581e-7ffb-4923-9cf7-3164a5e480f4
|
completed
| 2025-04-09T16:14:38.080476
| 2025-05-26T07:33:10.549261
|
d7e28ca7-662b-457a-b7b5-12cfca673403
|
In [25,32], the authors provided an overview of strategies for battery temperature estimation based on EIS.These strategies involve direct phase shift and intercept frequency measurements.To establish the effectiveness of these EIS-based techniques, the authors ran a comparative analysis with other existing apparatus and methods such as temperature sensors, equivalent circuits, and numerical models.Their findings demonstrated that the EIS response profiles are faster in detecting temperature peaks occurring within the LIB compared to conventional temperature measurements. Furthermore, a study [28] presented a review of how to construct a physically sound circuit model according to the characteristics of the battery system.By establishing a precise circuit model and constructing a uniform cell system to perform an EIS analysis, crucial information about each LIB's component can be obtained.EIS can separate and quantify the Rb, RSEI, R ct and W by a single experiment, and this can be used to analyze the battery characteristics regarding the state of charge (SOC), temperature, and SOH.EIS can be used to identify highly sensitive parameters (Ohmic resistance, capacitance of the SEI film, charge conduction resistance, and others) that are related to a change in the SOH. In [33], the authors proposed a time-domain EIS measurement technique followed by an equivalent circuit model interpretation.One of the difficulties in modelling is the choice of initial values, which often makes numerical convergence unachievable if these are wrongly set.The authors of [27] proposed a method to determine and optimize suitable parameters for battery analysis.The method was tested by applying it to two different kinds of LIBs: a lithium iron phosphate (LFP) battery and a lithium cobalt oxide (LCO) one.The proposed method combines several criteria to select a set of suitable values for each parameter, and then employs a quantitative criterion, the so-called Kramers-Kronig relations, to select an optimal parameter value among them.The proposed algorithm is computationally light, and it has been demonstrated that it helps provide meaningful information when used to interpret experimental EIS data. Recent works make use of ECM and machine learning, including artificial (ANNs) or recurrent neural networks.In particular, machine learning methods have been utilized to enhance the precision and effectiveness of EIS data, enabling the analysis of large datasets of measurements and the creation of predictive models for electrochemical systems.A model for high energy density that uses impedance spectroscopy measurements to monitor the SOH with ANNs has been proposed in [34], and it is based on an equivalent circuit approach.This phenomena is considered important and occurs inside the cell and the subsequent non-linearity of some parameters.In [35], two models for SOH estimation were proposed: one uses a convolution neural network (CNN) to process EIS data, while the other employs a bidirectional long short-term memory (BiLSTM) model for serial regression prediction.Additionally, the authors of [36] established the mapping relationship between health features and SOH using a BP neural network algorithm. Table 1 provides a summary regarding the primary studies focusing on the prediction of SOC and SOH using EIS.As discussed above, these studies encompass the utilization of two main methodologies: ECMs and machine learning techniques (MLTs).In the case of ECMs, it is possible to obtain important values from each component in a lithium-ion cell via a single experiment.If a circuit model is established with due care and a uniform cell system is constructed to perform an EIS analysis, crucial information about each component of the LIB can be obtained.The experimental measurements can be carried out easily regardless of the battery's state and size.The MLT approach is instead useful when the underlying physical models are not known and/or when the analyzed LIB's systems are rather complex.The effectiveness of MLTs depends largely on the quality of the data, on the appropriate choice of algorithm, and on the correct interpretation of the results.As shown in Table 1, several studies try to combine both the approaches, i.e., the ECMs and MLTs, to speed up the process and reduce the amount of error, leading to more robust and interpretable results with respect to their standalone usage. To sum up, the EIS data is often analyzed using mathematical models, signal processing techniques, and statistical algorithms to extract the relevant features and patterns associated with the condition of the material.These characteristics can be used to identify and characterize different types of defects, and to estimate their severity and monitor their progression over time.The choice between using a real circuit or a simplified model depends on several factors, including the precision of experimental data, the level of detail required, the complexity of the system, and the objectives of the analysis.In general, detailed information and a deep understanding of the system are sought, hence the need to employ complex models.However, if a faster analysis is needed or detailed data is lacking, employing a simplified model might be a suitable, yet forced choice.In any case, it is important to keep in mind the limitations of any approach. In conclusion, EIS is a method that in combination with data-driven techniques can achieve high accuracy and it is commonly used for battery characterization and moni-toring in the automotive and energy storage industries.It can be used to evaluate the electrochemical properties, SOC, SOH, and battery performance.EIS helps in identifying degradation mechanisms, tracking aging effects, and to optimize battery management strategies.Based on the various studies and works analyzed here, this NDT technique is a cost-effective solution in various industrial applications.The cost to arrange an EIS setup can vary depending on the specific requirements, the desired accuracy, and the frequency range of interest, but is in general relatively low.
|
<li> <b>temperature sensors:</b> Other Sensor<li> <b>EIS:</b> Other Sensor
|
[
[
{
"end": 358,
"label": "sensorType",
"start": 339
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EIS\" is not of interest to CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
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{
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{
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},
{
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},
{
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},
{
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},
{
"end": 5972,
"label": "sensorType",
"start": 5969
}
] | null | null |
8d6a4a76-e3d1-463c-b06a-32edd2811b4f
|
completed
| 2025-04-09T16:14:38.080482
| 2025-05-13T06:43:01.739063
|
893bbe0a-631d-4ddf-ab01-9c0692a807de
|
Here, we introduce Traffic Ear, an acoustic sensor pack that determines the engine noise of each passing vehicle without interrupting traffic flow. The device consists of an array of microphones combined with a computer vision camera. The class and speed of passing vehicles were estimated using sound wave analysis, image processing, and machine learning algorithms. We compared the traffic composition estimated with the Traffic Ear sensor with that recorded using an automatic number plate recognition (ANPR) camera and found a high level of agreement between the two approaches for determining the vehicle type and fuel, with uncertainties of 1–4%. We also developed a new bottom-up assessment approach that used the noise analysis provided by the Traffic Ear sensor along with the extensively detailed urban mobility maps that were produced using the geospatial and temporal mapping of urban mobility (GeoSTMUM) approach. It was applied to vehicles travelling on roads in the West Midlands region of the UK. The results showed that the reduction in traffic engine noise over the whole of the study road was over 8% during rush hours, while the weekday–weekend effect had a deterioration effect of almost half. Traffic noise factors (dB/m) on a per-vehicle basis were almost always higher on motorways compared the other roads studied.
|
<li> <b>acoustic sensor:</b> Other Sensor<li> <b>vehicle:</b> Other Vehicle<li> <b>microphones:</b> Other Sensor<li> <b>computer vision camera:</b> Camera<li> <b>vehicles:</b> Other Vehicle<li> <b>automatic number plate recognition (ANPR) camera:</b> Camera
|
[
[
{
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{
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{
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{
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{
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},
{
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}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Added sensorType to plain term \"sensor\""
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
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{
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{
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},
{
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},
{
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"start": 211
},
{
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"start": 266
},
{
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"label": "vehicleType",
"start": 945
},
{
"end": 518,
"label": "sensorType",
"start": 470
}
] | null | null |
b45cc330-4ca0-4b7e-b406-8fab3f5f6f71
|
completed
| 2025-04-09T16:14:38.080488
| 2025-05-26T14:10:04.465355
|
1c4d8b0d-9117-4354-99e9-33d1c2c159c6
|
This study introduces a novel hydro-pneumatic inerter suspension (HPIS) system for engineering vehicles, aiming at enhancing ride comfort and handling stability. The research focuses on addressing the limitations of conventional suspension systems by incorporating an inerter element into the vehicle suspension. The unique aspects of HPIS, such as nonlinear stiffness and nonlinear damping characteristics of the hydro-pneumatic spring, are explored. Firstly, a half-car dynamic model of the HPIS suspension is established, and an improved simulated annealing algorithm is applied to optimize the suspension parameters. Then, we compare the dynamic performance of different HPIS structures, specifically parallel and series layouts. For practical analysis, a simplified three-element HPIS suspension model is used, and the suspension parameters are optimized by a simulated annealing algorithm at speeds of 10 m/s, 15 m/s, and 20 m/s. Key findings reveal that compared to the traditional suspension system of S0, the front and rear suspension working space of S1 decreased by 40%, 40.1%, 40.2% and 30.7%, 30.8%, 30.9%, while with the body acceleration and pitch acceleration deteriorated by 3.1%, 3.2%, 3.3% and 63.4%, 63.8%, 64.0%. However, the S2 can improve all the dynamic performance and offer better ride comfort and handling stability.
|
<li> <b>engineering vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle
|
[
[
{
"end": 300,
"label": "vehicleType",
"start": 293
},
{
"end": 103,
"label": "vehicleType",
"start": 95
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 103,
"label": "vehicleType",
"start": 83
},
{
"end": 300,
"label": "vehicleType",
"start": 293
}
] | null | null |
ebb7bf66-646c-4a6d-ae6c-9de24da3407f
|
completed
| 2025-04-09T16:14:38.080494
| 2025-05-26T13:20:26.688535
|
e84bb059-aaa8-4d5c-9aa4-a9a9c3646837
|
To evaluate ride comfort and handling stability in a vehicle, the key factors include the dynamic load on the wheels, suspension deflection, pitch angular acceleration, and body acceleration [18].The traditional suspension is selected as the evaluation benchmark, and the optimal objective function is established as follows:
|
<li> <b>vehicle:</b> Other Vehicle
|
[
[
{
"end": 60,
"label": "vehicleType",
"start": 53
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 60,
"label": "vehicleType",
"start": 53
}
] | null | null |
71cb6a0c-9360-4c98-8352-ca318de64d8b
|
completed
| 2025-04-09T16:14:38.080501
| 2025-05-26T13:55:38.425062
|
d355f64c-964a-4e00-b695-7f4068ad2fe0
|
One of the greatest issues for electric vehicles such as an electric vehicle (EV), a hybrid vehicle (HV), a plug-in hybrid electric vehicle (PHEV) and a fuel cell vehicle (FCV) is further improvement of effective motor cooling, since higher rated torque is achieved with higher cooling performance. In this paper, we introduce and propose a newly developed motor cooling method we tested using refrigerant, comparing with conventional water cooling. Test results show higher cooling performance of refrigerant cooling, which achieved the rated torque 60% higher than that of water cooling.
|
<li> <b>electric vehicles:</b> Car<li> <b>electric vehicle (EV):</b> Car<li> <b>hybrid vehicle (HV):</b> Car<li> <b>plug-in hybrid electric vehicle (PHEV):</b> Car<li> <b>fuel cell vehicle (FCV):</b> Car
|
[
[
{
"end": 48,
"label": "vehicleType",
"start": 31
},
{
"end": 81,
"label": "vehicleType",
"start": 60
},
{
"end": 104,
"label": "vehicleType",
"start": 85
},
{
"end": 146,
"label": "vehicleType",
"start": 108
},
{
"end": 176,
"label": "vehicleType",
"start": 153
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EVs\", \"HVs\", \"PHEVs\" and \"FCVs\" might not be cars exclusively"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 48,
"label": "vehicleType",
"start": 31
},
{
"end": 81,
"label": "vehicleType",
"start": 60
},
{
"end": 104,
"label": "vehicleType",
"start": 85
},
{
"end": 146,
"label": "vehicleType",
"start": 108
},
{
"end": 176,
"label": "vehicleType",
"start": 153
}
] | null | null |
e4680715-f76c-45d4-94c9-015e7ebb4efa
|
completed
| 2025-04-09T16:14:38.080515
| 2025-05-19T09:38:33.371201
|
c82a80eb-251d-40e0-8e42-678fde3c945d
|
The cooling performance was compared between water and refrigerant by using the same motor of the specification in Table 4.All experiments started with water cooling as shown in Figure 4a.A TXV was installed at the inlet of the water jacket as shown in Figure 4b before experimenting refrigerant cooling.The refrigerant cooling experiment used the same motor as the water cooling experiment.The water jacket worked as the refrigerant path.In addition, the water circulation system was replaced by an A/C system.Compressor regulated its operation rate to control the refrigerant cooling performance.The compressor kept operating until the motor surface temperature declined to a target temperature.Note that the target temperatures for refrigerant cooling were set at 0, 10, and 20 • C. The compressor stopped its operation when the motor surface temperature was lowered below the target temperature.Three experiments were performed as shown in Table 5.In experiment 1, the motor temperature, which was operated at rated torque for 30 min, was measured. In experiment 2, new rated torque was estimated when water cooling was replaced by refrigerant cooling. In experiment 3, operation time at the maximum torque was measured.Figure 5 shows that refrigerant cooling kept the coil temperature lower than water cooling.Comparing water cooling of 60 • C and refrigerant cooling of 0 • C, the difference of the coil temperatures extended up to 53 • C after 30 minutes of motor operation at rated torque.The water cooling of 60 • C was the highest water temperature allowed in the specification.The refrigerant cooling of 0 • C was the lowest refrigerant temperature, which was determined by compressor ability.When the water temperature was set at 20 • C to adjust the initial coil temperature, refrigerant cooling even showed the higher cooling performance by 12 • C than water cooling.
|
None
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[] | null | null |
db8b7003-4a02-4a02-a59c-8cbd320b4dba
|
completed
| 2025-04-09T16:14:38.080528
| 2025-05-26T08:44:37.381381
|
9e05d5ab-edac-47c1-a2a5-096d3b70ba46
|
This paper aims to define an algorithm capable of building the origin-destination matrix from check-in data collected in the extra-urban area of Torino, Italy, where thousands of people commute every day, using smart cards to validate their travel documents while boarding. To this end, the methodological approach relied on a survey over three months to record smart-card validations. Peak and off-peak periods have been defined according to validation frequency. Then, the origin-destination matrix has been estimated using the time interval between two validations to outline the different legs of the journey. Finally, transport demand has been matched with existing bus services, showing which areas were not adequately covered by public transport. The results of this research could assist public transport operators and local authorities in the design of a more suitable transport supply and mobility services in accordance with user needs. Indeed, tailoring public transport to user needs attracts both more customers and latent demand, reducing reliance on cars and making transport more sustainable.
|
<li> <b>bus:</b> Bus<li> <b>public transport:</b> Bus<li> <b>cars:</b> Car
|
[
[
{
"end": 674,
"label": "vehicleType",
"start": 671
},
{
"end": 1070,
"label": "vehicleType",
"start": 1066
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"public transport\" is not a \"bus\" exclusively, so it is considered incorect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 674,
"label": "vehicleType",
"start": 671
},
{
"end": 752,
"label": "vehicleType",
"start": 736
},
{
"end": 812,
"label": "vehicleType",
"start": 796
},
{
"end": 982,
"label": "vehicleType",
"start": 966
},
{
"end": 1070,
"label": "vehicleType",
"start": 1066
}
] | null | null |
03acec26-7f7d-4bd1-8c2c-cecd73984e4e
|
completed
| 2025-04-09T16:14:38.080534
| 2025-05-13T06:07:59.461411
|
d9d1a407-936b-4745-a70a-174bbe62ccf7
|
According to the methodology concerning bus line classifications, three main classes were obtained.Figure 10 shows the classification of the bus lines where the "main lines" predominantly operate along the north-south axis.All cross the city of Torino. Sustainability 2018, 10, x FOR PEER REVIEW 13 of 21
|
<li> <b>bus:</b> Bus
|
[
[
{
"end": 43,
"label": "vehicleType",
"start": 40
},
{
"end": 144,
"label": "vehicleType",
"start": 141
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 43,
"label": "vehicleType",
"start": 40
},
{
"end": 144,
"label": "vehicleType",
"start": 141
}
] | null | null |
4133b560-d4a0-4a8b-80da-dde779933486
|
completed
| 2025-04-09T16:14:38.080541
| 2025-05-26T07:06:38.743058
|
925891fd-0141-4246-b7f2-e6437ba84b26
|
A system of functional relationships between speed, traffic safety and costs, based on a set of criteria describing transportation quality is presented. The overall technological costs of transportation can be determined, when the costs of using road, rail and sea transport are calculated. For this purpose, a case study of creating a mathematical model for choosing the optimal route, taking into account time, costs and safety of transportation, is considered. The model evaluates the time of freight loading and storage at terminals. The total time of transportation, loading and storage differs for particular routes, depending on route structure and terminal operation. Freight safety is calculated in terms of insurance payments, depending on the type of goods, route and time of transportation. The model may be used for calculating any route, when applying the data on particular parks of vehicles.
|
<li> <b>vehicles:</b> Other Vehicle
|
[
[
{
"end": 906,
"label": "vehicleType",
"start": 898
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 906,
"label": "vehicleType",
"start": 898
}
] | null | null |
72cdc1d9-6972-4eae-8db3-22b93c9aef5c
|
completed
| 2025-04-09T16:14:38.080547
| 2025-05-13T09:38:40.688148
|
ce141a4e-294e-42de-a873-0a129770a03d
|
Efficiency function T ≥ min; Limitation Z < Zmax.The efficiency function for the second alternative is to minimize time, when transportation costs are limited.This variant is acceptable when a customer needs urgent freight delivery and is ready to pay not a small sum of money for it.For example, in delivering parts to assembly shops, they should be provided in time (because in modern assembly shops parts are not stored and should be delivered exactly before assembling).Therefore, time is the priority in parts delivery.
|
None
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[] | null | null |
5482bf64-217d-4334-a4f8-060acb3b525e
|
completed
| 2025-04-09T16:14:38.080553
| 2025-05-23T21:36:57.210778
|
86298bb4-2fd1-4191-a82e-c64b47a9027f
|
In today’s world, parking area constitutes nearly most of traffic congestion is caused by vehicles cruising around their destination and looking for a place to park. Due to this reason many day-to-day activities are affected such as waste of time, fuel wastage, frustration to drivers, theft fear, pollution etc. These factors motivated to pave a new method for smart parking system. In this method the detection is reliable, even when tests are performed using images captured from a different viewpoint. It also provides to design a highly reliable & compatible image segmentation measures for parking slot identification system and a user key driven data base measures to detect the vehicle using theft alarm system.
|
<li> <b>parking:</b> Automated Parking<li> <b>vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>smart parking system:</b> Automated Parking
|
[
[
{
"end": 98,
"label": "vehicleType",
"start": 90
},
{
"end": 693,
"label": "vehicleType",
"start": 686
},
{
"end": 382,
"label": "scenarioType",
"start": 362
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 25,
"label": "scenarioType",
"start": 18
},
{
"end": 375,
"label": "scenarioType",
"start": 368
},
{
"end": 603,
"label": "scenarioType",
"start": 596
},
{
"end": 98,
"label": "vehicleType",
"start": 90
},
{
"end": 693,
"label": "vehicleType",
"start": 686
},
{
"end": 382,
"label": "scenarioType",
"start": 362
}
] | null | null |
61639bc1-5a5b-4cf9-aacf-c42fbe1b88a2
|
completed
| 2025-04-09T16:14:38.080559
| 2025-05-26T08:52:18.761525
|
93db3ef7-87de-414d-bb28-93ff4473d4f5
|
The Publisher's rights to the Article shall especially include, but shall not be limited to: • ability to publish an electronic version of the Article via the website of the publisher, as well as the copublisher's website or any other electronic format or means of electronic distribution.Publisher agrees to send the text of the Article to the e-mail address of Author indicated in the present Statement for preview before the first publishing either in paper and/or electronic format (Proof).Author shall return the corrected text of the Article within 2 days to the Publisher.Author shall, however, not make any change to the content of the Article during the First Proof preview.
|
None
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[] | null | null |
b7b4053c-2fc4-4f8f-91f6-592682fe03cb
|
completed
| 2025-04-09T16:14:38.080565
| 2025-05-26T09:23:56.621909
|
87934764-14ba-49c3-890c-5d48b35240be
|
Most light-duty vehicle crashes occur due to human error. Many of these crashes could be avoided or made less severe with the aid of crash avoidance technologies. These technologies can assist the driver in maintaining control of the vehicle when a possibly dangerous situation arises by issuing alerts to the driver and in a few cases, responding to the situation itself. This paper estimates the societal and private benefits and costs associated with three crash avoidance technologies, blind-spot monitoring, lane departure warning, and forward-collision warning, for all light duty passenger vehicles in the U.S. for the year 2015. The three technologies could collectively prevent up to 1.6 million crashes each year including 7,200 fatal crashes. In this paper, the authors estimated the net-societal benefits to the overall society from avoiding the cost of the crashes while also estimating the private share of those benefits that are directly affecting the crash victims. For the first generation warning systems, net-societal benefits and net-private benefits are positive. Moreover, the newer generation of improved warning systems and active braking should make net benefits even more advantageous.
|
<li> <b>vehicle:</b> Other Vehicle<li> <b>crash avoidance technologies:</b> Other Level of Automation<li> <b>passenger vehicles:</b> Car
|
[
[
{
"end": 23,
"label": "vehicleType",
"start": 16
},
{
"end": 241,
"label": "vehicleType",
"start": 234
},
{
"end": 161,
"label": "levelOfAutomation",
"start": 133
},
{
"end": 488,
"label": "levelOfAutomation",
"start": 460
},
{
"end": 605,
"label": "vehicleType",
"start": 587
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"passenger cars\" could be also minivans"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 23,
"label": "vehicleType",
"start": 16
},
{
"end": 241,
"label": "vehicleType",
"start": 234
},
{
"end": 161,
"label": "levelOfAutomation",
"start": 133
},
{
"end": 488,
"label": "levelOfAutomation",
"start": 460
},
{
"end": 605,
"label": "vehicleType",
"start": 587
}
] | null | null |
31786b64-54a9-4924-92a8-235ea16fbe99
|
completed
| 2025-04-09T16:14:38.080571
| 2025-05-13T09:11:53.879159
|
3d6efd6b-62b9-40df-b483-12169bca6e89
|
In this paper, the authors provide two estimates of potential societal benefits: 1) the total annual societal benefits based on observed insurance data from the Highway Loss Data Institute (HLDI) and 2) the upper bound crash prevention cost savings by assuming all relevant crashes are avoided.In order to estimate the total annual societal benefits of fleet-wide deployment of LDW, FCW, and BSM systems, the authors estimate the changes in crash frequency and severity from vehicles equipped with these systems.To estimate the upper bound crash prevention cost savings, the authors identify which types of crashes could potentially be prevented or made less severe by each technology.The primary sources of data used are the 2015 General Estimate System (GES) which provides information on crashes of all severities, the 2015 Fatality Analysis Reporting System (FARS) which provides information on fatal crashes, and insurance data from various reports written by HLDI.
|
<li> <b>vehicles:</b> Other Vehicle
|
[
[
{
"end": 483,
"label": "vehicleType",
"start": 475
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 483,
"label": "vehicleType",
"start": 475
}
] | null | null |
b81b2d3b-9d89-440d-9a4e-ebcd97606449
|
completed
| 2025-04-09T16:14:38.080577
| 2025-05-20T11:12:41.937881
|
ca3e8f35-c98b-429c-9223-90a2f9720f85
|
With the rapid breakthroughs in artificial intelligence technology and intelligent manufacturing technology, automotive intelligence has become a research hotspot, and much progress has been made. However, a skeptical attitude is still held towards intelligent vehicles, especially when driving in a complex multi-vehicle interaction environment. The interaction among multi-vehicles generally involves more uncertainties in vehicle motion and entails higher driving risk, and thus deserves more research concerns and efforts. Targeting the safety assessment issue of complex multi-vehicle interaction scenarios, this article summarizes the existing literature on the relevant data collection methodologies, vehicle interaction mechanisms, and driving risk evaluation methods for intelligent vehicles. The limitations of the existing assessment methods and the prospects for their future development are analyzed. The results of this article can provide a reference for intelligent vehicles in terms of timely and accurate driving risk assessment in real-world multi-vehicle scenarios and help improve the safe driving technologies of intelligent vehicles.
|
<li> <b>intelligent vehicles:</b> Other Vehicle<li> <b>multi-vehicle interaction:</b> Other Scenario<li> <b>vehicle:</b> Other Vehicle
|
[
[
{
"end": 269,
"label": "vehicleType",
"start": 249
},
{
"end": 800,
"label": "vehicleType",
"start": 780
},
{
"end": 990,
"label": "vehicleType",
"start": 970
},
{
"end": 1155,
"label": "vehicleType",
"start": 1135
},
{
"end": 333,
"label": "scenarioType",
"start": 308
},
{
"end": 601,
"label": "scenarioType",
"start": 576
},
{
"end": 432,
"label": "vehicleType",
"start": 425
},
{
"end": 715,
"label": "vehicleType",
"start": 708
},
{
"end": 1084,
"label": "scenarioType",
"start": 1061
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 269,
"label": "vehicleType",
"start": 249
},
{
"end": 800,
"label": "vehicleType",
"start": 780
},
{
"end": 990,
"label": "vehicleType",
"start": 970
},
{
"end": 1155,
"label": "vehicleType",
"start": 1135
},
{
"end": 333,
"label": "scenarioType",
"start": 308
},
{
"end": 601,
"label": "scenarioType",
"start": 576
},
{
"end": 321,
"label": "vehicleType",
"start": 314
},
{
"end": 432,
"label": "vehicleType",
"start": 425
},
{
"end": 589,
"label": "vehicleType",
"start": 582
},
{
"end": 715,
"label": "vehicleType",
"start": 708
},
{
"end": 1074,
"label": "vehicleType",
"start": 1067
}
] | null | null |
97af6a5f-09b5-4243-bcf0-05f5895d02a3
|
completed
| 2025-04-09T16:14:38.080583
| 2025-05-26T07:43:35.901751
|
5898c35a-8a1d-4a1f-acde-57041310ba39
|
Trajectory prediction refers to outputting the predicted trajectories of the target vehicles over a period of time (usually 1 s for short-term and 3-5 s for medium-term) based on given information (such as vehicle dynamics, historical trajectories, traffic rules, etc.), which can be of great significance for functional modules such as path planning and driving risk assessment.The trajectory prediction-based risk evaluation method analyzes the future spatiotemporal distribution of different vehicle trajectories based on the trajectory prediction results, based on which risk assessment for multi-vehicle interaction is ultimately achieved.Table 9 summarizes the evaluation method based on trajectory prediction.
|
<li> <b>vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>path planning:</b> Other Scenario<li> <b>multi-vehicle interaction:</b> Other Scenario
|
[
[
{
"end": 92,
"label": "vehicleType",
"start": 84
},
{
"end": 213,
"label": "vehicleType",
"start": 206
},
{
"end": 502,
"label": "vehicleType",
"start": 495
},
{
"end": 620,
"label": "scenarioType",
"start": 595
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"path planning\" is not a scenarioType"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 92,
"label": "vehicleType",
"start": 84
},
{
"end": 213,
"label": "vehicleType",
"start": 206
},
{
"end": 502,
"label": "vehicleType",
"start": 495
},
{
"end": 608,
"label": "vehicleType",
"start": 601
},
{
"end": 350,
"label": "scenarioType",
"start": 337
},
{
"end": 620,
"label": "scenarioType",
"start": 595
}
] | null | null |
26f403d1-cc95-4adc-9d21-f45e1eeaeac6
|
completed
| 2025-04-09T16:14:38.080589
| 2025-05-26T13:59:33.658327
|
052c4c2b-9ffe-42d0-8950-981a48affb96
|
One of the most challenging fields in vehicular communications has been the experimental assessment of protocols and novel technologies. Researchers usually tend to simulate vehicular scenarios and/or partially validate new contributions in the area by using constrained testbeds and carrying out minor tests. In this line, the present work reviews the issues that pioneers in the area of vehicular communications and, in general, in telematics, have to deal with if they want to perform a good evaluation campaign by real testing. The key needs for a good experimental evaluation is the use of proper software tools for gathering testing data, post-processing and generating relevant figures of merit and, finally, properly showing the most important results. For this reason, a key contribution of this paper is the presentation of an evaluation environment called AnaVANET, which covers the previous needs. By using this tool and presenting a reference case of study, a generic testing methodology is described and applied. This way, the usage of the IPv6 protocol over a vehicle-to-vehicle routing protocol, and supporting IETF-based network mobility, is tested at the same time the main features of the AnaVANET system are presented. This work contributes in laying the foundations for a proper experimental evaluation of vehicular networks and will be useful for many researchers in the area.
|
<li> <b>vehicular communications:</b> Other Communication Type<li> <b>vehicle-to-vehicle:</b> V2V<li> <b>vehicular networks:</b> Other Communication Type
|
[
[
{
"end": 62,
"label": "communicationType",
"start": 38
},
{
"end": 413,
"label": "communicationType",
"start": 389
},
{
"end": 1093,
"label": "entityConnectionType",
"start": 1075
},
{
"end": 1345,
"label": "communicationType",
"start": 1327
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 62,
"label": "communicationType",
"start": 38
},
{
"end": 413,
"label": "communicationType",
"start": 389
},
{
"end": 1093,
"label": "entityConnectionType",
"start": 1075
},
{
"end": 1345,
"label": "communicationType",
"start": 1327
}
] | null | null |
e9fd05b0-9c32-48dc-9247-63d03e1917ad
|
completed
| 2025-04-09T16:14:38.080595
| 2025-05-26T14:17:48.369162
|
dee97c22-57db-4743-9a68-587bd59ffc04
|
The paper has presented the peculiarities of evaluating vehicular networks experimentally, through presenting the most used protocols and detailing the needs of the software tools to be used for this task.After that, the importance of the testing methodology is described, and a reference design of a vehicular network evaluation is used to exemplify it.The testbed design and implementation, testing scenarios, routing protocols and data flows, are found essential to be fixed beforehand to avoid improvisation during the testing campaign.The AnaVANET platform is then presented
|
<li> <b>vehicular networks:</b> Other Communication Type
|
[
[
{
"end": 74,
"label": "communicationType",
"start": 56
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 74,
"label": "communicationType",
"start": 56
}
] | null | null |
89f28a9a-3ed6-4dd7-881a-b05f060ab611
|
completed
| 2025-04-09T16:14:38.080601
| 2025-05-26T08:53:49.581803
|
dbef7636-2f27-4b76-8551-9b15d400ad1a
|
Demand for electric vehicles (EVs), and thus EV charging, has steadily increased over the last decade. However, there is limited fast-charging infrastructure in most parts of the world to support EV travel, especially long-distance trips. The goal of this study is to develop a stochastic dynamic simulation modeling framework of a regional system of EV fast-charging stations for real-time management and strategic planning (i.e., capacity allocation) purposes. To model EV user behavior, specifically fast-charging station choices, the framework incorporates a multinomial logit station choice model that considers charging prices, expected wait times, and detour distances. To capture the dynamics of supply and demand at each fast-charging station, the framework incorporates a multi-server queueing model in the simulation. The study assumes that multiple fast-charging stations are managed by a single entity and that the demand for these stations are interrelated. To manage the system of stations, the study proposes and tests dynamic demand-responsive price adjustment (DDRPA) schemes based on station queue lengths. The study applies the modeling framework to a system of EV fast-charging stations in Southern California. The results indicate that DDRPA strategies are an effective mechanism to balance charging demand across fast-charging stations. Specifically, compared to the no DDRPA scheme case, the quadratic DDRPA scheme reduces average wait time by 26%, increases charging station revenue (and user costs) by 5.8%, while, most importantly, increasing social welfare by 2.7% in the base scenario. Moreover, the study also illustrates that the modeling framework can evaluate the allocation of EV fast-charging station capacity, to identify stations that require additional chargers and areas that would benefit from additional fast-charging stations.
|
<li> <b>electric vehicles (EVs):</b> Car<li> <b>EV:</b> Car
|
[
[
{
"end": 34,
"label": "vehicleType",
"start": 11
},
{
"end": 47,
"label": "vehicleType",
"start": 45
},
{
"end": 198,
"label": "vehicleType",
"start": 196
},
{
"end": 353,
"label": "vehicleType",
"start": 351
},
{
"end": 474,
"label": "vehicleType",
"start": 472
},
{
"end": 1184,
"label": "vehicleType",
"start": 1182
},
{
"end": 1713,
"label": "vehicleType",
"start": 1711
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EVs\" are not cars exclusively"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 34,
"label": "vehicleType",
"start": 11
},
{
"end": 47,
"label": "vehicleType",
"start": 45
},
{
"end": 198,
"label": "vehicleType",
"start": 196
},
{
"end": 353,
"label": "vehicleType",
"start": 351
},
{
"end": 474,
"label": "vehicleType",
"start": 472
},
{
"end": 1184,
"label": "vehicleType",
"start": 1182
},
{
"end": 1713,
"label": "vehicleType",
"start": 1711
}
] | null | null |
734ba674-0045-4868-954b-92aab07117c8
|
completed
| 2025-04-09T16:14:38.080607
| 2025-05-19T09:37:33.653479
|
f4a61fe0-8b15-4f6b-be6c-8e2266023471
|
This subsection describes the behavioral models of the EV user station choice that underlay the demand for fast-charging stations.As mentioned previously, the study employs an MNL model to capture the station choice (or 'no station' choice) of individual EV users.However, another behavioral model is required to determine each EV user's station choice set. The behavioral model used to determine the EV user's choice set is a straightforward deterministic model with two parameters-the EV user's current SOC and his/her willingness-to-detour.Fig. 2 displays how the deterministic model, with the SOC and willingness-to-detour parameters, produces a choice set for each EV user.The subregion delineated by the yellow circle includes the set of charging stations the EV can reach based on its current SOC (S 1 ,S 2 ,S 3 ,S 4 ).The subregion delineated by the blue ellipse includes the set of charging stations the EV is willing to visit between its current location and its destination given his/her willingness to detour (S 2 , S 3 ,S 4 ,S 6 ).The intersection of the blue ellipse and the yellow circle includes all the charging stations in the EV user's choice set (S 2 ,S 3 , S 4 ). After determining a set of feasible charging stations, each EV user chooses an individual charging station S i considering the price, detour distance, and expected waiting time of each charging station in his/her choice set.This study assumes the initial station choice is made when the EV user's trip begins based on the current information about station prices and queue lengths, available through a mobile or desktop application.When an EV user arrives at a station, the study assumes he/she reconsiders his/her station choice before entering the queue.In all cases, station choices are based on the MNL model.A future model extension might assume EV users regularly re-consider their station choice while driving based on evolving information about queue lengths and charging prices at stations in the system. Based on the MNL assumptions, Eq. ( 1) displays the probability of choosing station S i at time t for vehicle j as a function of the three variables (P (i,t) , Det (i,j,t) and W t i ) and the parameter values (β 1 , β 2 , β 3 ) associated with each variable.Pr(S i ) = e β 1 ×P (i,t) +β 2 ×Det (i,j,t) +β 3 ×W (i,t) ∑ K k=1 e β 1 ×P (k,t) +β 2 ×Det (k,j,t) +β 3 ×W (k,t) . (1)where P (i,t) , Det (i,j,t) and W t i represent the current charging price at Station i, total detour trip distance to use Station i, and current expected waiting time at Station i, respectively.Notably, this behavioral modeling approach does not explicitly incorporate charging urgency, an important behavioral factor.Despite its importance, it is quite elusive to quantify and calibrate, especially given that it is often confounded with factors like state-ofcharge, willingness-to-detour, price sensitivity, and also the disutility of not charging at a fast-charging station.
|
<li> <b>EV:</b> Car<li> <b>vehicle:</b> Other Vehicle
|
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] | null | null |
43eefe8b-ef7b-4de4-a6a8-54f227fef181
|
completed
| 2025-04-09T16:14:38.080613
| 2025-05-23T21:14:48.306039
|
90dda05a-85cf-4055-bebf-d6b051b8dfb6
|
Radar sensors were among the first perceptual sensors used for automated driving. Although several other technologies such as lidar, camera, and ultrasonic sensors are available, radar sensors have maintained and will continue to maintain their importance due to their reliability in adverse weather conditions. Virtual methods are being developed for verification and validation of automated driving functions to reduce the time and cost of testing. Due to the complexity of modelling high-frequency wave propagation and signal processing and perception algorithms, sensor models that seek a high degree of accuracy are challenging to simulate. Therefore, a variety of different modelling approaches have been presented in the last two decades. This paper comprehensively summarises the heterogeneous state of the art in radar sensor modelling. Instead of a technology-oriented classification as introduced in previous review articles, we present a classification of how these models can be used in vehicle development by using the V-model originating from software development. Sensor models are divided into operational, functional, technical, and individual models. The application and usability of these models along the development process are summarised in a comprehensive tabular overview, which is intended to support future research and development at the vehicle level and will be continuously updated.
|
<li> <b>Radar sensors:</b> Radar<li> <b>perceptual sensors:</b> Other Sensor<li> <b>automated driving:</b> Other Level of Automation<li> <b>lidar:</b> LiDAR<li> <b>camera:</b> Camera<li> <b>ultrasonic sensors:</b> Other Sensor<li> <b>radar sensors:</b> Radar<li> <b>automated driving functions:</b> Other Level of Automation<li> <b>sensor models:</b> Other Sensor<li> <b>radar sensor:</b> Radar<li> <b>vehicle:</b> Other Vehicle<li> <b>Sensor models:</b> Other Sensor
|
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] | null | null |
b8cb2c13-c1d9-46a8-b976-18240efd697c
|
completed
| 2025-04-09T16:14:38.080619
| 2025-05-26T13:20:10.662255
|
84c9eb09-15e0-4246-9bf8-1baf179c5c8a
|
The use of marine cabled video observatories with multiparametric environmental data collection capability is becoming relevant for ecological monitoring strategies. Their ecosystem surveying can be enforced in real time, remotely, and continuously, over consecutive days, seasons, and even years. Unfortunately, as most observatories perform such monitoring with fixed cameras, the ecological value of their data is limited to a narrow field of view, possibly not representative of the local habitat heterogeneity. Docked mobile robotic platforms could be used to extend data collection to larger, and hence more ecologically representative areas. Among the various state-of-the-art underwater robotic platforms available, benthic crawlers are excellent candidates to perform ecological monitoring tasks in combination with cabled observatories. Although they are normally used in the deep sea, their high positioning stability, low acoustic signature, and low energetic consumption, especially during stationary phases, make them suitable for coastal operations. In this paper, we present the integration of a benthic crawler into a coastal cabled observatory (OBSEA) to extend its monitoring radius and collect more ecologically representative data. The extension of the monitoring radius was obtained by remotely operating the crawler to enforce back-and-forth drives along specific transects while recording videos with the onboard cameras. The ecological relevance of the monitoring-radius extension was demonstrated by performing a visual census of the species observed with the crawler’s cameras in comparison to the observatory’s fixed cameras, revealing non-negligible differences. Additionally, the videos recorded from the crawler’s cameras during the transects were used to demonstrate an automated photo-mosaic of the seabed for the first time on this class of vehicles. In the present work, the crawler travelled in an area of 40 m away from the OBSEA, producing an extension of the monitoring field of view (FOV), and covering an area approximately 230 times larger than OBSEA’s camera. The analysis of the videos obtained from the crawler’s and the observatory’s cameras revealed differences in the species observed. Future implementation scenarios are also discussed in relation to mission autonomy to perform imaging across spatial heterogeneity gradients around the OBSEA.
|
<li> <b>cameras:</b> Camera<li> <b>mobile robotic platforms:</b> Other Vehicle<li> <b>underwater robotic platforms:</b> Other Vehicle<li> <b>benthic crawlers:</b> Other Vehicle<li> <b>crawler:</b> Other Vehicle<li> <b>onboard cameras:</b> Camera<li> <b>vehicles:</b> Other Vehicle
|
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"\"benthic crawlers\", \"underwater robotic platforms\" and \"mobile robotic platforms\" are not of interest to CCAM"
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] | null | null |
96a8e0fc-9ec5-49d1-a534-849d431af8ae
|
completed
| 2025-04-09T16:14:38.080625
| 2025-05-13T09:36:39.539191
|
88d02abb-d44d-40bd-a0ba-92a285ce3eb0
|
We implemented a new crawler prototype (i.e., width 55 cm, length 100 cm, and height 40 cm, with a total weight in air and in the water of 56 kg and 12.1 kg, respectively) as a modified and lower-cost version of the "Wally" platform; The "Wally" crawler has been operating at the Ocean Networks Canada (ONC; www.oceannetworks.ca,accessed on 18 April 2023) since 2010 [41].Figure 3 shows the crawler developed for shallow water operations and its various components.The choice of the vehicle and its dimensioning were driven by several factors.Unlike propeller-driven vehicles, which must continuously compensate for current disturbances, benthic crawlers can passively maintain a fixed position, reducing power consumption and acoustic noise during long stationary phases.This is particularly appealing in ecological monitoring operations in which the disturbance introduced by the tool may bias the observation.The dimensions of the crawler resemble those of a typical observation class Remotely Operated Vehicle (ROV; [56]) and allow convenient mobility around the OBSEA, and simple deployment/recovery from a vessel of opportunity.The crawler is endowed with a new HD camera (SNC-241 RSIA; resolution of 1920 × 1080; 2 megapixels) (see Figure 3, Label 1).This camera can operate at a 180° tilt and 360° pan to allow for a hemispherical panoramic FOV around the platform itself.The camera is installed into a glass sphere, rated up to 3000 m depth, in the front part of the crawler.Two white LED lights (ExtraStar) are placed aside, on top of the camera. The tracks, which are mounted on a broader chassis (see Figure 3, Label 2), are independent parts that allow the mobilisation of the inner part of the vehicle.A Faulhaber DC motor with a reduction gear of 989:1 was used as a propulsion system for each track.The motor housing is oil-filled and can operate at up to a 100 m depth.The crawler is equipped with two watertight cylinders, one hosting the main control unit and electronics (see Figure 3, Label 3), and the other hosting the power supply unit and the Ethernet switch (see Figure 3, Label 5) connected to the cabled observatory.The main unit (see Figure 3, Label 3) is also in charge of running the crawler, providing control for the motors, measurements of the internal sensors, and control of external instruments such as the HD camera, lights (see Figure 3, Label 4), and S2C-Evologic R 18/34 acoustic modem.The current housing is rated for operations at depths up to 100 m.Furthermore, the main cable (see Figure 3, Label 6) is a 50 m long underwater umbilical cable, designed to be used in deep-water, subsea applications, for transmission data and preparing electrical power.The cable was endowed with foam floaters (190 mm in diameter and buoyancy of 1800 g) to reduce drag, prevent entanglement and abrasion on the seabed, and so as to not impair the platform navigation functionalities. In order to achieve both driving autonomy and the onboard processing of images and videos to derive high-value ecological monitoring data (see below), we developed a main controller.This was based on a Single-Board Computer (SBC) using an ODROID C4 plate [57].Although the efficiency of this implementation is described here only in relation The crawler is endowed with a new HD camera (SNC-241 RSIA; resolution of 1920 × 1080; 2 megapixels) (see Figure 3, Label 1).This camera can operate at a 180 • tilt and 360 • pan to allow for a hemispherical panoramic FOV around the platform itself.The camera is installed into a glass sphere, rated up to 3000 m depth, in the front part of the crawler.Two white LED lights (ExtraStar) are placed aside, on top of the camera. The tracks, which are mounted on a broader chassis (see Figure 3, Label 2), are independent parts that allow the mobilisation of the inner part of the vehicle.A Faulhaber DC motor with a reduction gear of 989:1 was used as a propulsion system for each track.The motor housing is oil-filled and can operate at up to a 100 m depth.The crawler is equipped with two watertight cylinders, one hosting the main control unit and electronics (see Figure 3, Label 3), and the other hosting the power supply unit and the Ethernet switch (see Figure 3, Label 5) connected to the cabled observatory.The main unit (see Figure 3, Label 3) is also in charge of running the crawler, providing control for the motors, measurements of the internal sensors, and control of external instruments such as the HD camera, lights (see Figure 3, Label 4), and S2C-Evologic R 18/34 acoustic modem.The current housing is rated for operations at depths up to 100 m.Furthermore, the main cable (see Figure 3, Label 6) is a 50 m long underwater umbilical cable, designed to be used in deep-water, subsea applications, for transmission data and preparing electrical power.The cable was endowed with foam floaters (190 mm in diameter and buoyancy of 1800 g) to reduce drag, prevent entanglement and abrasion on the seabed, and so as to not impair the platform navigation functionalities. In order to achieve both driving autonomy and the onboard processing of images and videos to derive high-value ecological monitoring data (see below), we developed a main controller.This was based on a Single-Board Computer (SBC) using an ODROID C4 plate [57].Although the efficiency of this implementation is described here only in relation to navigation autonomy (see the next section), this board has also been selected because of its potential to autonomously process data onboard.That processing autonomy capability is required for automated fish species identification, classification, and tracking. Technical specifications for the crawler components, in terms of brand, voltage, and power consumption, are detailed in Table 1 where we also detail the overall costs of our implementation to provide a range of the economic costs required to create other similar platforms.The "Structure and Mechanical Parts" category in this table includes the chassis, switch, and control cylinder housings, aluminium frame, tracks, camera sphere glass housing, support, and motor housings."Additional Costs" include specific oil used for filling the motor housing, resin, 3D printed components, the Plexiglas chassis, etc.The control cylinder (Figure 4) is divided into four main components: a power supply board (see Figure 4, Label 1) to provide the energy for the motor drivers, motors, lights, and compass, and the main controller board.In the main controller board (see Figure 4, Label 2), the ODROID C4 and the backplate board, which provide connections with all the other elements, are included.Moreover, there are two motor drivers (see Figure 4, Label 3) to supply the left and right tracks.Finally, a compass (see Figure 4, Label 4) is used for navigation.The control cylinder (Figure 4) is divided into four main components: a power supply board (see Figure 4, Label 1) to provide the energy for the motor drivers, motors, lights, and compass, and the main controller board.In the main controller board (see Figure 4, Label 2), the ODROID C4 and the backplate board, which provide connections with all the other elements, are included.Moreover, there are two motor drivers (see Figure 4, Label 3) to supply the left and right tracks.Finally, a compass (see Figure 4, Label 4) is used for navigation.
|
<li> <b>crawler:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>vehicles:</b> Other Vehicle<li> <b>Remotely Operated Vehicle (ROV; [56]):</b> Other Vehicle<li> <b>vessel:</b> Other Vehicle<li> <b>HD camera:</b> Camera<li> <b>camera:</b> Camera<li> <b>LED lights:</b> Other Sensor<li> <b>lights:</b> Other Sensor<li> <b>internal sensors:</b> Other Sensor<li> <b>acoustic modem:</b> Other Sensor<li> <b>compass:</b> Other Sensor
|
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"Removed \"crawler\" and \"vessel\" from vehicleType\nAssigned as levelOfAutomation the term \"driving autonomy\"\nRemoved \"lights\" and \"compass\" from sensorType\n"
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},
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},
{
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},
{
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},
{
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},
{
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},
{
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"start": 6973
},
{
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"label": "sensorType",
"start": 7282
}
] | null | null |
980d08bf-5516-4cac-ae25-07c0c64d5a25
|
completed
| 2025-04-09T16:14:38.080631
| 2025-05-26T14:12:41.075645
|
f13089ae-139a-4134-bac0-5aad72a524b3
|
In the analysis of the readiness of means of transport, the Markov and semi-Markov processes are particularly applicable, allowing for the description of the usage process over long periods of time, determination of indicators of the exploitability and readiness of the used set of objects, as well as simulation of long-term forecasts of the usage process results. The studies presented in the literature usually concern the theoretical side of the matter, mainly the construction of formal models of the process of changing the operating states of a vehicle. Less attention is paid to the empirical side, especially with regard to the actual conditions of use. Examples of experimental observations presented in the literature most often concern individual cases. This paper lists selected irregularities and presents an example of a study of a real transport system based on semi-Markov processes.
|
<li> <b>vehicle:</b> Other Vehicle
|
[
[
{
"end": 559,
"label": "vehicleType",
"start": 552
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 559,
"label": "vehicleType",
"start": 552
}
] | null | null |
1963b75b-7745-402a-a4b6-42a411b95ff7
|
completed
| 2025-04-09T16:14:38.080637
| 2025-05-13T09:38:43.649254
|
0d8458b1-0e6a-4bc8-a158-e26599a95317
|
: 0 N t t ≥ determined by the equation: ( ) is called a counting process. Definition 2. The stochastic process Is called the semi-Markov process generated by the Markov renewal process ( ) { } 0 , : n n n N ξ ϑ ∈ with the initial decomposition p and kernel ( ) Thus defined semi-Markov process is a stochastic one with a discrete space of states S at time t T R + ∈ = .The semi-Markov process is defined when its kernel and initial distribution are specified.The definition shows that: This means that functions that take fixed values in the ranges constitute realizations of the semi-Markov process. From the definition of both the Markov renewal and SM process, it follows that the state of the semi-Markov process and its duration depends only on the previous state, and not on previous states and their duration.The process kernel and the initial distribution fully define the semi-Markov process (Duan et al. 2019;Wu et al. 2019).
|
None
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[] | null | null |
1fd4a4c9-5a8e-450c-a589-c0eb55f22622
|
completed
| 2025-04-09T16:14:38.080643
| 2025-05-21T13:53:37.631972
|
7383f097-44c9-482e-98b7-002e0c327a5b
|
The overwhelming majority of compartment cars owned by Ukrzaliznytsia JSC were manufactured in Germany in the 70-80s of the last century. They have exhausted their resource. The metal structures of the frame and body are badly worn. Extending the service life of such cars requires a thorough study of the possibilities of their further use. The article discusses the results of an analysis of the stress-strain state of passenger car bodies. A three-dimensional model of the body was built. Body strength calculations were performed using the finite element method using the ANSYS software package. The racks and upper trim of the side walls, roof arches, etc. were considered as rods. The body frame, substructure, side wall cladding, end walls, roof cladding and floor deck were modeled using plate finite elements. Calculations were carried out in accordance with the requirements of current regulatory documents. The maximum speed was assumed to be 160 km/h. The developed model was verified. The results obtained were compared with the results of experimental studies (strength tests). The similarity of the results confirmed the correctness of the created model. A study was carried out of the stress-strain state of the body at nominal sizes with standard skin thicknesses. It has been established that the stresses arising in the most loaded areas do not exceed the permissible values for structural steels. The resulting model of the body will subsequently make it possible to determine the wear limits of the load-bearing structures of the frame and body. It also allows, using the calculation-probabilistic method, taking into account the probabilistic nature of all existing loads, to calculate the reliability indicators of the car and its final life.
|
<li> <b>compartment cars:</b> Other Vehicle<li> <b>cars:</b> Other Vehicle<li> <b>passenger car:</b> Other Vehicle<li> <b>car:</b> Other Vehicle
|
[
[
{
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"label": "vehicleType",
"start": 41
},
{
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"label": "vehicleType",
"start": 268
},
{
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"label": "vehicleType",
"start": 421
},
{
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"label": "vehicleType",
"start": 1742
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"compartment car\" not of interest for CCAM"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 45,
"label": "vehicleType",
"start": 29
},
{
"end": 45,
"label": "vehicleType",
"start": 41
},
{
"end": 272,
"label": "vehicleType",
"start": 268
},
{
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"label": "vehicleType",
"start": 421
},
{
"end": 434,
"label": "vehicleType",
"start": 431
},
{
"end": 1745,
"label": "vehicleType",
"start": 1742
}
] | null | null |
30195108-338c-42b3-bcb7-a0dc7f997789
|
pending
| 2025-04-09T16:14:38.080649
| 2025-04-09T16:14:38.080649
|
974164c1-1963-4adf-a314-4036cb1b4687
|
1.A finite element model of the body of a rigid compartment car 47D has been constructed.Beam and plate finite elements were used for modeling. 2. A study of the stress-strain state of the body at nominal dimensions with standard sheathing thicknesses was conducted.It was found that the stress occurring in the most loaded areas do not exceed the permissible values for structural steels. 3. The obtained body model will further allow determining the limit values of wear for the loadbearing structures of the frame and body and calculating, by probabilistic methods considering the probabilistic nature of all acting loads, the reliability indicators of the car and its ultimate service life.розробленої моделі.Отримані результати порівнювали з результатами експериментальних досліджень (випробувань міцності).Подібність результатів підтвердила правильність створеної моделі.Проведено дослідження напружено деформованого стану кузова при номінальних розмірах зі стандартними товщинами обшиви.Встановлено, що напруги, що виникають у найбільш навантажених місцях, не перевищують допустимі значення конструкційних сталей.Отримана модель кузова надалі дозволить визначати граничні величини зношування несучих конструкцій рами і кузова і розраховувати розрахунково-імовірнісним методом з урахуванням імовірнісного характеру всіх навантажень, що діють, показники надійності вагона і його остаточний ресурс. Ключові слова: пасажирський вагон, кузов, ресурс, спрацювання, напруження.
|
<li> <b>compartment car:</b> Other Vehicle<li> <b>car:</b> Other Vehicle<li> <b>вагона:</b> Other Vehicle
|
[
[
{
"end": 63,
"label": "vehicleType",
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},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
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},
{
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}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"discarded"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"discarded"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"discarded"
] |
[
"half text is non-recognizable --> to be discarded"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"discarded"
] |
[
{
"end": 63,
"label": "vehicleType",
"start": 48
},
{
"end": 63,
"label": "vehicleType",
"start": 60
},
{
"end": 663,
"label": "vehicleType",
"start": 660
},
{
"end": 1376,
"label": "vehicleType",
"start": 1370
}
] | null | null |
4c2605c3-e22a-4f7e-9551-a16b14d62573
|
completed
| 2025-04-09T16:14:38.080655
| 2025-05-26T08:06:13.770925
|
399ad624-8d2c-4e4b-97fd-96d9fd1f251d
|
Lateral vehicle control is a high importance in automated vehicles as it directly influences the vehicle’s performance and safety during operation. The Linear Quadratic Regulator (LQR) controller stands out due to its high-performance characteristics and is used in the open source for self driving functions. However, a notable limitation of the current approach is the manual calibration of LQR controllers based on the experience and intuition of the designers, leading to empirical uncertainties. To address this issue and enhance the lateral control performance, this paper concentrates on refining the LQR by employing three optimization algorithms: Artificial Bee Colony Optimization (ABC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). These algorithms aim to overcome the reliance on empirical methods and enable a data-driven approach to LQR calibration. By comparing the outcomes of these optimization algorithms to the manual LQR controller within an offline multibody simulation as testing platform, the study highlights the superiority of the best-performing optimization approach. Following this, the optimal algorithm is implemented on a real-time system for the full vehicle level, revealing the Model-in-the-Loop and the Hardware-in-the-Loop gap up to 78,89% with lateral velocity when we use Relative Error Criterion (REC) method to validate and 2.35m with lateral displacement when considering by maximum absolute value method.
|
<li> <b>automated vehicles:</b> Other Vehicle<li> <b>vehicle’s:</b> Other Vehicle<li> <b>self driving functions:</b> Other Level of Automation<li> <b>vehicle:</b> Other Vehicle
|
[
[
{
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"label": "vehicleType",
"start": 48
},
{
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"label": "levelOfAutomation",
"start": 286
},
{
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"label": "vehicleType",
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},
{
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"label": "vehicleType",
"start": 1201
},
{
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"label": "vehicleType",
"start": 97
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"vehicle's\" should not be identified additionally to \"vehicle\" as a vehicleType"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 66,
"label": "vehicleType",
"start": 48
},
{
"end": 106,
"label": "vehicleType",
"start": 97
},
{
"end": 308,
"label": "levelOfAutomation",
"start": 286
},
{
"end": 15,
"label": "vehicleType",
"start": 8
},
{
"end": 104,
"label": "vehicleType",
"start": 97
},
{
"end": 1208,
"label": "vehicleType",
"start": 1201
}
] | null | null |
880386f0-d991-4c1c-ab60-118dd93a6dc9
|
completed
| 2025-04-09T16:14:38.080661
| 2025-05-13T06:45:25.749401
|
0799472b-ea53-4f10-8de7-4efa82b5babc
|
In this study, a BMW5 model is used for simulation.The model was calibrated with experiments performed at the Institute of Automotive Engineering laboratory and on a proving ground.Firstly, test the BMW 5 car on the real road to measure the parameters and save these in the datasheet.Then, a simple model with parameter adjustment from the datasheet is created.After that, the car was simulated on the test road, and the parameters were measured and the compared with the simulation.Finally, calibrate the steering model and stabilizer model for good fitting of the curves and choose the best tire model.The results of the model calibration refer to [46].The BMW5 model is simulated in the CarMaker environment on a 50 m circular road, as depicted in Figure 6.The car drives in 48 s, with a maximum speed of 50 km/h and the speed step is 0.01.Therefore, there are 5000 values of matrix K corresponding to each speed step, and the lateral errors are evaluated during driving.
|
<li> <b>car:</b> Car
|
[
[
{
"end": 208,
"label": "vehicleType",
"start": 205
},
{
"end": 380,
"label": "vehicleType",
"start": 377
},
{
"end": 767,
"label": "vehicleType",
"start": 764
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 208,
"label": "vehicleType",
"start": 205
},
{
"end": 380,
"label": "vehicleType",
"start": 377
},
{
"end": 767,
"label": "vehicleType",
"start": 764
}
] | null | null |
d46cacaa-e1b3-4025-8d9b-efe209d9ff65
|
completed
| 2025-04-09T16:14:38.080667
| 2025-05-26T14:13:47.774429
|
2dd962b8-a7cc-45d0-9514-4be55e70ee0e
|
The main task of this paper is to review the principal aspects in organization of interurban long haul service by use of road trains on the basis of the “district” traffic system. The goal of the paper is to determine the most effective methods of trucking operations in order to highlight the regularities that characterize these methods. The paper describes practicable methods of freight flow analysis, some factors and parameters concerning movement of motor‐vehicle trains and original route schedules as well. Of special interest is the obtained algorithm of economically effective trucking operations of motor‐vehicle trains on the route.
|
<li> <b>road trains:</b> Truck<li> <b>trucking:</b> Truck<li> <b>motor‐vehicle trains:</b> Truck<li> <b>motor‐vehicle:</b> Other Vehicle
|
[
[
{
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"label": "vehicleType",
"start": 121
},
{
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"label": "vehicleType",
"start": 248
},
{
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"label": "vehicleType",
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},
{
"end": 477,
"label": "vehicleType",
"start": 457
},
{
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"label": "vehicleType",
"start": 611
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 132,
"label": "vehicleType",
"start": 121
},
{
"end": 256,
"label": "vehicleType",
"start": 248
},
{
"end": 596,
"label": "vehicleType",
"start": 588
},
{
"end": 477,
"label": "vehicleType",
"start": 457
},
{
"end": 631,
"label": "vehicleType",
"start": 611
},
{
"end": 470,
"label": "vehicleType",
"start": 457
},
{
"end": 624,
"label": "vehicleType",
"start": 611
}
] | null | null |
63e86fa7-a947-4bac-8f5c-e364b095f15b
|
completed
| 2025-04-09T16:14:38.080673
| 2025-05-23T21:34:56.202131
|
1d1ca2d1-9758-4414-b91f-a6ae5c6727a0
|
. The total time of movement of the semi-trailers with line-haul trucks en route: Dwell time of the semi-trailers at the final terminal: The number of semi-trailers: ( ) C scheme (see Fig 4 c): In this range beginning with a certain number of dispatches of road trains ("n"), the trailers that have managed to make the maneuvering turnaround may also appear at the initial point of the route (terminal A). In this case, dwell time of the semi-trailers at the initial terminal: The total time of movement of the semi-trailers with line-haul trucks en route: Dwell time of the semi-trailers at the final terminal (point B): The number of semi-trailers: . The number of trucks: ) it can be called the zone in which further increase in the traffic flow (or the number of scheduled runs) does not require increase in the number of trucks and semitrailers (Fig 5). Summing up these three components, at any meaning of "n" (14-24) in our case, the reader will obtain a constant value (384/24) or 16 semi-trailers.The operators may take any meaning of "n" and change above factors and parameters from their own version, the result will be the same.The author would like to attract special attention to this phenomenon because this is the key for solving the problem of cutting short the rolling stock at the increasing scopes of delivery ("effect of shuttle").The number of trucks also becomes constant.), performs another turnaround within this route section, i.e. the route time of each truck is 16 h and the load run is . Varying the interval of dispatching the trucks, i.e. compacting or expanding the "packet-system", by using the trucks of higher load-carrying capacity, or by dispatching the trucks by "stringet" standard schedule (when h 1 ) one after another (in practice it can be min 10 5 -= d i ) the zone may retain operational control.The main factors here are the volume of freight flow and the structure of the transportation motor pool. In case of passive control of operation of the rolling stock, we find ourselves in the other type of schedule, when . The second and third types of the schedules which have their own regularities and specific features are not considered here, like the optimum location of terminals, trucking companies, grounds for changing trucks and other facilities along the route.It should be pointed out that these regularities are preserved for the increase in number of route sections when the route consists of adjacent sections of different length and different duty time of customer's warehouses ( h 24 ) (Fig 4 d).In general case, when the route includes " m " sections: 2 The next stage of our research deals with the choice of the most cost-effective motor-vehicle train from the range of the large trucks and semi-trailers by use of equivalent truck loading table (Table 3). It is commonly supposed that the motor-vehicle train with the highest load-carrying capacity is considered to be most effective.In the majority of cases it is actually so but different combinations of the above factors, parameters and schedules may drastically change this stereotype.The economic evaluation can be made by using the suggested model (Fig 6).For economic evaluation of this model optimum use could be made of the following formula: ; where: R -the total annual costs; E -the operating costs/wages, fuel, maintenance, repair of rolling stock, renovation, depreciation, overhead costs; ε -the rate of return T ; T -the pay-off period (5 years); k -the investments (investments in the rolling stock, buildings, constructions, equipment, etc.).
|
<li> <b>semi-trailers:</b> Truck<li> <b>trucks:</b> Truck<li> <b>road trains:</b> Truck<li> <b>rolling stock:</b> Other Vehicle<li> <b>motor-vehicle train:</b> Truck<li> <b>motor-vehicle:</b> Other Vehicle
|
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[
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[
"Partially correct"
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[
"submitted"
] |
[
"Partially correct"
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[
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[
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] |
[
"\"Semitrailer\" should be also recognized as vehicleType exactly like \"semi-trailer\"\n\"Rolling stock\" does not seem to be of interest to CCAM\n\"trains\" are not of interest to CCAM\n"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
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{
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"label": "vehicleType",
"start": 2852
}
] | null | null |
8d5445df-7a8d-4596-89aa-459407e38e38
|
completed
| 2025-04-09T16:14:38.080680
| 2025-05-23T21:16:01.773809
|
89d9d456-0e36-4fa9-b08d-92b2a88af28c
|
Vehicles are a major source of atmospheric pollutants and greenhouse gases. Real Driving Emissions (RDE) testing is used to study the real-world effects of parameters that are not considered in laboratory testing but that can influence fuel consumption and vehicle emissions. This paper analyzes the vehicle specific power (VSP) and the effects of positive and negative road slopes on the fuel consumption of a sport utility vehicle (SUV). The vehicle was tested on a route at an altitude of 2750 meters in Riobamba, Ecuador. The circuit design included urban, rural, and highway driving that met the requirements of European Union (EU) Regulation 2018/1832. Low-cost devices were used to record data from the road tests to determine fuel consumption as a function of road slope. VSP+ analysis revealed that there is a good correlation with fuel consumption, with an R2 of 0.86. For road slopes of -6% to +6%, the percentage variation in fuel consumption is linearly correlated (R2 = 0.85) with the slope variations.
|
<li> <b>Vehicles:</b> Other Vehicle<li> <b>vehicle:</b> Other Vehicle<li> <b>sport utility vehicle (SUV):</b> Car
|
[
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[
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[
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] |
[
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
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[
"submitted"
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[
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[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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{
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},
{
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"label": "vehicleType",
"start": 411
}
] | null | null |
b994533e-10a4-4a9d-b0e7-b10eedcef4e9
|
completed
| 2025-04-09T16:14:38.080687
| 2025-05-26T14:25:43.880496
|
566eb201-a8c0-4eb1-9b1f-a0e21a7db45c
|
The RDE test dynamics in Riobamba, Ecuador, were analyzed.The results showed that VSP+ is a good indicator of fuel consumption, especially on hilly roads.VSP+ shows a good correlation with fuel consumption, allowing a better understanding of the dynamics of RDE tests.This is because VSP+ considers the road slope, unlike the dynamic parameters RPA and v*a_pos95.VSP+ is useful for evaluating the power requirement of the highest accelerations and altitude gain.The influence of the road slope was evident, with a direct correlation between the slope and fuel consumption in the rural section of the RDE test.The increases and decreases in fuel consumption associated with positive and negative road slopes were similar, and with the same slope value of 6% + and/orit meant an increase/decrease of around 80% of the fuel consumption compared to a flat section. At higher altitudes, vehicle fuel consumption increases.However, it is important to note that something beyond altitude gain also influences fuel consumption, such as ECU strategy, catalyst design, or less aggressive driving behavior. The test analyzed here only covers a limited number of scenarios.Further research is needed to expand this analysis to more extensive conditions, such as different altitude gains, different driver behaviors, power-to-weight ratio, etc., to define the limits of VSP + more clearly as an RDE test indicator and its potential use to predict fuel consumption and develop fuel saving strategies in high altitude cities.
|
<li> <b>vehicle:</b> Other Vehicle
|
[
[
{
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"start": 882
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 889,
"label": "vehicleType",
"start": 882
}
] | null | null |
1313a6e8-bf03-4916-a79c-49b68de311f3
|
completed
| 2025-04-09T16:14:38.080693
| 2025-05-26T08:37:25.998035
|
6bf0ff2e-d637-467a-8c78-31338650f751
|
Noise from cars is one of the main sources of harmful pollution. In the presented paper, an octave frequency band analysis is conducted according to standard methods of external and internal noise measurement. Experiments at different speeds, with three types of cars—conventional gasoline (GV), hybrid (HEV) and pure electric (BEV)— were carried out on two types of pavement—damaged coarse-grained and smooth finegrained asphalt. The results show variations in external and internal noise levels vs. speed in different octave bands. At each speed, a spectral analysis was done. The diagrams with results show changes in noise level vs. speed and the positions of noise maximums. Regression models for the octave spectrum at different speeds and pavements are developed.
|
<li> <b>cars:</b> Car<li> <b>gasoline (GV):</b> Car<li> <b>hybrid (HEV):</b> Car<li> <b>electric (BEV):</b> Car
|
[
[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"gasoline (GV)\", \"hybrid (HEV)\" and \"electric (BEV)\" should not be recognized as \"cars\" but as \"other vehicles\""
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
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{
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{
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},
{
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"label": "vehicleType",
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}
] | null | null |
6f9d8637-41d9-4d82-ad34-316ee29748c7
|
completed
| 2025-04-09T16:14:38.080699
| 2025-05-13T09:13:33.037888
|
7d512ab5-db11-4422-aaf2-17ad2a38e9ba
|
The internal noise dissipation for all three cars on both pavements was also high, at 31.5 Hz.In this range, the electric car was the loudest.In the middle frequencies, the gasoline car had the lowest noise levels, and the hybrid car had the highest. As the driving speed increased from 20 to 90 km/h, the maximum values of the noise level at 1000 Hz increased from 43-48 dB to about 59-61 dB on the damaged coarse-grained pavement. On the smooth fine-grained pavement, the analogous variation ranged from about 40-45 dB to about 49-56 dB.The difference between the two pavements at the same speed varied from 3-8 dB. The results for external noise on the damaged coarse-grained pavement show that at low frequencies (31.5 and 63 Hz), there was no clear domination of external noise for some of the cars.At the frequencies of 125, 250, 500, and 1000 Hz, the electric car and hybrid car yielded similar results, while the petrol car had a lower noise level.At high frequencies, the results for all three cars were very similar.The graphs show that on the smooth asphalt pavement at low frequencies (31.5, 63, and 125 Hz), the outcomes were the same.At frequencies above 250 Hz, the hybrid car was the loudest.At high frequencies, the results for all three cars were very similar. The results obtained by octave bands show that the values for the external noise dominated the values in the middle-frequency bands and for the internal noise in the low-frequency bands.For all types of vehicles and road surfaces, the external noise's maximum value was 1000 Hz, while the maximum levels of internal noise ranged from 125-500 Hz.This shows that the external noise was strongly influenced by the noise generated by the contact of the tires with the road and the internal noise generated by the elements of the drive system.These conclusions are valid for all three types of cars.
|
<li> <b>cars:</b> Car<li> <b>electric car:</b> Car<li> <b>gasoline car:</b> Car<li> <b>hybrid car:</b> Car<li> <b>petrol car:</b> Car<li> <b>vehicles:</b> Other Vehicle
|
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[
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[
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] |
[
"Correct"
] |
[
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[
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{
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"label": "vehicleType",
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}
] | null | null |
4f9763bc-d08e-4568-8d6b-a95f1be42ada
|
completed
| 2025-04-09T16:14:38.080705
| 2025-05-20T14:28:56.529192
|
f95494e0-2062-4d98-a569-671df1799e12
|
This paper investigates heterogeneity in truck drivers’ route choice preferences. A latent class model is estimated to identify heterogeneous segments of drivers. A stated choice experiment designed for identifying route choice behavior of truck drivers provides the data for model estimation. The effects of road pricing and environmental bonus are examined considering context dependency. Results reveal that size of truck is a significant segmentation variable of preferences for route attributes. Drivers of light trucks care more about congestion than drivers of heavy trucks, and are highly sensitive to road pricing and slightly sensitive to a road bonus. Drivers of heavy trucks are more sensitive to road category and urban area than drivers of light trucks, and are insensitive to bonus and slightly sensitive to pricing.
|
<li> <b>truck drivers:</b> Truck<li> <b>truck:</b> Truck<li> <b>light trucks:</b> Truck<li> <b>heavy trucks:</b> Truck
|
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[
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[
"submitted"
] |
[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
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] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
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[
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},
{
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}
] | null | null |
08b74105-64b7-4c3f-8670-ff65a963381b
|
completed
| 2025-04-09T16:14:38.080711
| 2025-05-26T14:12:08.949902
|
e9e76dc9-82d6-47bd-8e69-baf7e42aa2a1
|
In the field of discrete choice modeling, two models are commonly used to identify heterogeneity: the mixed logit model (ML) and latent class model (LCM).The former method assumes that the parameters of the utility function follow a particular type of distribution.The mean and variance of the parameters are both estimated and the significance of the variance indicates the existence of heterogeneous preferences.In real applications, the problem is how to specify a feasible distribution function for certain parameters, which leads to considerable testing work for different types of density functions.In contrast, the latent class model imposes the assumption that there are certain numbers of latent segments among individuals.Different from the mixed logit model in econometric approaches which estimates the random parameters by drawing randomly from some continuous joint density function, LCM uses a discrete number of segments to describe the density function of the parameters.Within each segment, the choice preferences are assumed to be homogeneous.(4) EJTIR 13(4), 2013, pp.259-273 262 Feng, Arentze, Timmermans Capturing preference heterogeneity of truck drivers' route choice behavior with context effects using a latent class model where Zi is a vector of segment variables of respondent related characteristics; is the vector of parameters to be estimated for segment s. Segment variables Z are commonly called concomitant variables of a latent class model.If no concomitant variables are specified, the theta parameters reduce to constants. To identify the optimal number of classes, the Bayesian Information Criterion BIC is often used.It can be expressed as: (5 where LL is the log likelihood function at convergence; K is the number of parameters in the model. The advantage of BIC, compared with minimum log likelihood, is the incorporation of a penalty term on the number of parameters.When estimating parameters with different number of classes, the model with the least BIC value is thought to be the best.
|
None
|
[
[]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[] | null | null |
78c0c29c-e409-4eb3-bb64-5c297fc700ce
|
completed
| 2025-04-09T16:14:38.080717
| 2025-05-19T11:43:33.908774
|
d0c4e5d9-908f-4c79-953e-197ae3f8a62e
|
Passenger motor vehicle transport is a significant and growing emissions source contributing to climate change. Switching from internal combustion engines to electric vehicles (EV) would significantly reduce most countries’ emissions, but for many consumers perceived barriers deter EV adoption. Consequently, government policies designed to incentivise a transition to EVs could benefit from consideration of the utility of communication channels such as print media for influencing consumer behaviour. This research explores the role that media and other communication channels writing about EVs play in consumer perceptions and awareness of government-initiated programs and policies to incentivise EV market transition. Using mixed methods of a media review and New Zealand car buyer surveys (questionnaires, interviews) (n = 893), we identified car buyers’ media use to update knowledge about cars, perceptions about EVs, and likelihood to buy, and tested awareness and popularity of incentives. We derive recommendations for policy improvements to accelerate EV uptake, including a significant role for the print media to disseminate relevant information, increase awareness of policies, and shift perceptions about EVs. We argue that social marketing programs should be enhanced to overcome lack of knowledge and misinformation, focusing on the market segment next most likely to buy EVs.
|
<li> <b>motor vehicle:</b> Other Vehicle<li> <b>electric vehicles (EV):</b> Car<li> <b>EV:</b> Car<li> <b>EVs:</b> Car<li> <b>car:</b> Car
|
[
[
{
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{
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},
{
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},
{
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},
{
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},
{
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{
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},
{
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},
{
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},
{
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"label": "vehicleType",
"start": 1222
},
{
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"label": "vehicleType",
"start": 1391
},
{
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"label": "vehicleType",
"start": 778
},
{
"end": 853,
"label": "vehicleType",
"start": 850
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"(general comment in various annotation comments): EV could be a scooter or a mini-van, not a car exclusively"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 23,
"label": "vehicleType",
"start": 10
},
{
"end": 180,
"label": "vehicleType",
"start": 158
},
{
"end": 179,
"label": "vehicleType",
"start": 177
},
{
"end": 285,
"label": "vehicleType",
"start": 283
},
{
"end": 704,
"label": "vehicleType",
"start": 702
},
{
"end": 1067,
"label": "vehicleType",
"start": 1065
},
{
"end": 373,
"label": "vehicleType",
"start": 370
},
{
"end": 597,
"label": "vehicleType",
"start": 594
},
{
"end": 925,
"label": "vehicleType",
"start": 922
},
{
"end": 1225,
"label": "vehicleType",
"start": 1222
},
{
"end": 1394,
"label": "vehicleType",
"start": 1391
},
{
"end": 781,
"label": "vehicleType",
"start": 778
},
{
"end": 853,
"label": "vehicleType",
"start": 850
}
] | null | null |
545f2d85-9f41-4a1d-9601-655b9f8880de
|
completed
| 2025-04-09T16:14:38.080723
| 2025-05-26T08:22:43.976346
|
11063424-a0bf-42ad-9b1e-59ff5f491e4b
|
We compared car consumers in two samples, EV owners, and ICEV buyers by conducting two online questionnaires, followed by interviews with some respondents randomly selected from a panel of volunteers from each group.
|
<li> <b>car:</b> Car<li> <b>EV:</b> Car<li> <b>ICEV:</b> Car
|
[
[
{
"end": 15,
"label": "vehicleType",
"start": 12
},
{
"end": 44,
"label": "vehicleType",
"start": 42
},
{
"end": 61,
"label": "vehicleType",
"start": 57
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"\"EV\" could be other vehicle than \"car\""
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 15,
"label": "vehicleType",
"start": 12
},
{
"end": 44,
"label": "vehicleType",
"start": 42
},
{
"end": 61,
"label": "vehicleType",
"start": 57
}
] | null | null |
a2ad45c7-4b78-43a5-b672-8d6c82da10b1
|
completed
| 2025-04-09T16:14:38.080729
| 2025-05-13T06:30:30.532683
|
41ba85b0-31d1-4e7c-af20-a3a922f7da52
|
The use of Hybrid Electric Vehicles (HEVs) across the world is growing enormously every day. The single-phase bi-directional convertors are presented in this study for HEVs on-board charging(OBC). In HEVs, we use power electronics converters for the converting and inverting operations. Artificial Neural Network(ANN) is presented in this study for simple operation and high optimization approaches. ANN control technique regulates the system's THD and enhances charging system optimization, enables two-way power delivery that is from the grid to vehicle and the vehicle to grid. An ANN based current controller model that achieves fast-dynamic reaction and that improves grid current harmonic characteristics is proposed in this study. The system's THD is reduced by the ANN controller being suggested. The results prove the validity and feasibility of design and control technique of the proposed integrated charging system.
|
<li> <b>Hybrid Electric Vehicles (HEVs):</b> Car<li> <b>HEVs:</b> Car<li> <b>vehicle:</b> Other Vehicle<li> <b>grid to vehicle:</b> I2V<li> <b>vehicle to grid:</b> V2N
|
[
[
{
"end": 42,
"label": "vehicleType",
"start": 11
},
{
"end": 172,
"label": "vehicleType",
"start": 168
},
{
"end": 204,
"label": "vehicleType",
"start": 200
},
{
"end": 555,
"label": "entityConnectionType",
"start": 540
},
{
"end": 579,
"label": "entityConnectionType",
"start": 564
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 42,
"label": "vehicleType",
"start": 11
},
{
"end": 41,
"label": "vehicleType",
"start": 37
},
{
"end": 172,
"label": "vehicleType",
"start": 168
},
{
"end": 204,
"label": "vehicleType",
"start": 200
},
{
"end": 555,
"label": "vehicleType",
"start": 548
},
{
"end": 571,
"label": "vehicleType",
"start": 564
},
{
"end": 555,
"label": "entityConnectionType",
"start": 540
},
{
"end": 579,
"label": "entityConnectionType",
"start": 564
}
] | null | null |
1a30cb04-5c55-495a-bcf9-5d3f51edfd1c
|
completed
| 2025-04-09T16:14:38.080735
| 2025-05-13T06:26:25.666489
|
9bfb5267-bc4d-4d25-952f-3fb420aa7c02
|
As illustrated in Fig. 1(b), integral circuit is modified to provide a single-phase, two-way OBC circuit.Grid filter reactor, full-bridge ac-dc converter, and battery comprise OBC method circuit.Relay 05 and 07 will be triggered in order to employ starter generator winding as filter reactor for DC-DC conversion.Then, the grid will be connected to full bridge conversion unit via relays 01 and 02, which will be ON.The corresponding induction equivalent of the filter is 1.5 times that of generator's single winding.On this OBC circuit, two alternate transmission statuses are provided.When power is delivered to the car from the grid, the battery is charged and the state is referred to as G2V mode.Rather than that, V2G mode uses the battery's energy as a standard energy storage device.
|
<li> <b>car:</b> Car<li> <b>G2V:</b> I2V<li> <b>V2G:</b> V2N
|
[
[
{
"end": 621,
"label": "vehicleType",
"start": 618
},
{
"end": 695,
"label": "entityConnectionType",
"start": 692
},
{
"end": 722,
"label": "entityConnectionType",
"start": 719
}
]
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
null
] |
[
"4b8c3fe0-5d19-47b2-b4b5-276e7f0356d0"
] |
[
"submitted"
] |
[
{
"end": 621,
"label": "vehicleType",
"start": 618
},
{
"end": 695,
"label": "entityConnectionType",
"start": 692
},
{
"end": 722,
"label": "entityConnectionType",
"start": 719
}
] | null | null |
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