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# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
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# Dataset Card for Vehicle Dynamics Dataset

<!-- Provide a quick summary of the dataset. -->

This dataset contains time-series data capturing vehicle motion events such as braking, hard braking, acceleration, and hard acceleration, derived from simulated accelerometer data. It is designed to support research in vehicle dynamics, motion analysis, and driving behavior.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

The dataset provides accelerometer readings on three axes (X, Y, Z) along with annotated events based on predefined thresholds for braking, hard braking, acceleration, and hard acceleration. It includes data grouped into 10-second intervals for easy aggregation and analysis.

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

The dataset is suitable for:

- Training and evaluating machine learning models for detecting vehicle motion events.
- Analyzing driving behavior under different conditions.
- Research on vehicle safety systems.

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

- Real-world deployment without testing with real-world data.
- Applications outside the context of vehicle dynamics.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

The dataset contains the following columns:

- **Timestamp**: The timestamp of the reading.
- **AccelerationX, AccelerationY, AccelerationZ**: Accelerometer readings along the three axes.
- **Braking, HardBraking, Acceleration, HardAcceleration**: Boolean flags for motion events.
- **TimeGroup**: 10-second interval grouping.
- **Output**: The dominant event type in each interval.

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

The dataset was created to simulate and analyze vehicle motion events to support research and development in vehicle safety and dynamics.

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

The data was simulated using randomized accelerometer readings and thresholds for braking and acceleration events. It was then processed and annotated using Python libraries such as Pandas and NumPy.



#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

Annotations were programmatically added based on predefined thresholds for motion events.

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

The annotations were generated automatically using Python scripts.

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

The dataset does not contain personal or sensitive information.

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

The dataset is simulated and may not fully represent real-world scenarios. Use caution when applying models trained on this dataset to real-world data.

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should validate models with real-world data before deploying them in production systems.


## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

- **Braking**: A reduction in velocity, identified by negative acceleration.
- **Hard Braking**: Significant reduction in velocity, crossing a higher negative threshold.
- **Acceleration**: An increase in velocity, identified by positive acceleration.
- **Hard Acceleration**: Significant increase in velocity, crossing a higher positive threshold.

## More Information [optional]

[More Information Needed]