The dataset on the following behaviors of drivers on highways.

The highD dataset is a new dataset of naturalistic vehicle trajectories recorded on German highways. Using a drone, typical limitations of established traffic data collection methods such as occlusions are overcome by the aerial perspective. Traffic was recorded at six different locations and includes more than 110 500 vehicles. Each vehicle’s trajectory, including vehicle type, size and manoeuvres, is automatically extracted. Using state-of-the-art computer vision algorithms, the positioning error is typically less than ten centimeters. Although the dataset was created for the safety validation of highly automated vehicles, it is also suitable for many other tasks such as the analysis of traffic patterns or the parameterization of driver models.The dataset is extracted from the HighD dataset and pertains to the car type data, presented in the form of a tabular CSV file, which includes parameters such as the speed, acceleration, and longitudinal position of the ego vehicle, as well as the speed, acceleration, and longitudinal position of the preceding vehicle, among others. It can be utilized for studying driver following behavior.