Abstract

Parameter identification of microscopic driving models is a difficult task. This is caused by the fact that parameters-such as reaction time, sensitivity to stimuli, etc.-are generally not directly observable from common traffic data, but also due to the lack of reliable statistical estimation techniques. This contribution puts forward a new approach to identifying parameters of car-following models.

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