Empirical description of car-following

Abstract

This contribution reports a recently recorded data-set that helps to understand the car-following process better. Since the empirical basis of most traffic flow models can be called weak, these findings may help to design better models. They demonstrate, that the process of car-following seems to have a very interestic stochastic dynamics. Especially, and different from most of the existing models the data show clearly that car following cannot be described by a noisy fixed point dynamics. This is because the acceleration of the cars is smooth and roughly constant for a certain time, with fast changes to a new value at so called action points. Furthermore, the data can be used for calibration and validation purposes of the various models. This has been done with very interesting results indicating that all the models tested behave very similar and cannot describe the data better than with 15 % difference between models and data.