Performance of car following behaviour in microscopic traffic flow models

In this paper ten microscopic traffic flow models of very different kind are analysed concerning the correct reproduction of the car-following behaviour on single lane roads. The models are calibrated and validated with data collected via DGPSequipped cars (Differential Global Positioning System) on a test track in Japan. The positions of the cars are delivered every 0.1 second with very high accuracy, which is perfect for analysing the car following behaviour. To calibrate the models, in each case one driver pair is under consideration. The measured data of a leading car are fed into the model under consideration and the model is used to compute the behaviour of a following car. In the analysis the resulting simulated time series of headways are carried out and the deviations to the measured headways are calculated to calibrate the models. For validation purposes a driver-independent and a driver-specific approach have been conducted. The results show that calibration errors of about 13 % to 19 % are hard to undercut. The driver-independent validation results give additional errors of about 6 percentage points, which can be slightly reduced by about 1 to 3 percentage points with a driver-special validation. Most interestingly, no model could be denoted to be the best, even very sophisticated models do not perform better than simple ones.