Experimental Sensor Data from Vehicles for Dynamic Vehicle Models

Preliminary Information Only: Files will be updated upon the article’s acceptance by Sensors.

The attached dataset contains over 17.5 hours of experimental sensor data, including measurements from the following sensors:

- Front axle steering angle [°]

- Longitudinal acceleration [g]

- Lateral acceleration [g]

- Yaw rate [deg/s]

- Wheel speed (front left) [km/h]

- Wheel speed (front right) [km/h]

- Wheel speed (rear left) [km/h]

- Wheel speed (rear right) [km/h]

Data was sampled at a rate of 0.01 seconds and includes three distinct driving scenarios: calm driving, aggressive driving, and city driving. The dataset also captures variations such as reduced tire pressure (one tire at a time), different passenger loads, and measurements from three different vehicles.

The data was collected at the Continental Test Track in Veszprém, Hungary, as well as within the city of Veszprém.

The data is stored in Apache Parquet format that can be processed via Pandas library in Python.

For more information please check our article:

Sensitivity Analysis of Long Short-Term Memory-based Neural Network Model for Vehicle Yaw Rate Prediction @MPDI Sensors