Hybrid order characteristics in car-following behavior.202
Tu, Chunling Du, Shengzhi
Tu, Chunling
Du, Shengzhi
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Abstract
This paper addresses the hybrid order behavior in car-following processes, which was not reported in the existing literatures. The behavior is supported by both experimental data and theoretical simulations. To demonstrate this behavior, the first order and the second order car-following behaviors are defined. By comparing car-following behaviors in the existing analystic models and the real traffic context, this paper finds that a significant amount of the second order car-following processes in real traffic context do not match the models. The structural mismatches suggest the existence of unmodelled dynamics in the existing methods. In fact, the car following behavior is determined by more factors than the immediate proceeding vehicle. Therefore, the existing car-following models must be improved to accommodate these factors. This forms one of the main values of this paper. This paper then defines the hybrid order car-following behavior and prompts to associate this behavior with the concerned unmodelled dynamics. A neural network is employed to model such dynamics. The proposed hybrid order behavior matches the fact that the car-following behavior is determined by multiple vehicles instead of the immediate proceeding one only. This is valuable in providing guidance on the improvement of existing models.
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Date
2020-03-26
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Institute of Advanced Engineering and Science
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Keywords
Car following, Intelligent transport systems, Vehicle behavior modelling