Modeling vehicle car-following behavior in congested traffic conditions based on different vehicle combinations

ABSTRACT This paper develops an improved cellular automaton model in congested traffic conditions that differentiates vehicle combinations to consider both vehicle physical performance and driving behavior difference in car-following behavior. Car-following is divided into four groups by the lead and lag vehicle type. The vehicle behavior, including steady space gap, acceleration, and behavior choice, was studied to find out the diversity of car-following behavior in different vehicle combinations. The results show that vehicles in different vehicle combinations have different car-following behaviors. In the proposed model, each vehicle combination has its particular update rules and parameters. The model was evaluated by comparison with the existing car-following models at the microscopic and macroscopic level and the stability was also analyzed. The results show that the improved cellular automata model has a satisfactory performance.

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