Experimental Sensor Data from Vehicles for Dynamic Vehicle Models

<b>Preliminary Information Only:</b> Files will be updated upon the article’s acceptance by <i>Sensors</i>.<br>The attached dataset contains over 17.5 hours of experimental sensor data, including measurements from the following sensors:<br>- 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]<br>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.<br>The data was collected at the Continental Test Track in Veszprém, Hungary, as well as within the city of Veszprém.<br>The data is stored in Apache Parquet format that can be processed via Pandas library in Python.<br>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