Datasets:
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license: apache-2.0
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license: apache-2.0
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# VED - Vehicle Energy Dataset
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Este dataset é uma cópia. O original pode ser obitido diretamente no github dos autores: [https://github.com/gsoh/VED](https://github.com/gsoh/VED).
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---
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VED captures GPS trajectories of vehicles along with their timeseries data of fuel, energy, speed, and auxiliary power usage, and the data was collected through onboard OBD-II loggers from Nov, 2017 to Nov, 2018.
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The fleet consists of total 383 personal cars (264 gasoline vehicles, 92 HEVs, and 27 PHEV/EVs) in Ann Arbor, Michigan, USA.
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Driving scenarios range from highways to traffic-dense downtown area in various driving conditions and seasons.
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In total, VED accumulates approximately 374,000 miles.
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A number of examples were presented in the paper to demonstrate how VED can be utilized for vehicle energy and behavior studies. Potential research opportunities include data-driven vehicle energy consumption modeling, driver behavior modeling, machine and deep learning, calibration of traffic simulators, optimal route choice modeling, prediction of human driver behaviors, and decision making of self-driving cars.
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Link to the paper:
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[Vehicle Energy Dataset (VED), A Large-scale Dataset for Vehicle Energy Consumption Research](https://doi.org/10.1109/TITS.2020.3035596)\
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**Geunseob (GS) Oh**, David J. LeBlanc, Huei Peng\
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IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020.\
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The paper is also available on [Arxiv](https://arxiv.org/pdf/1905.02081.pdf).
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