Multi-Agent Traffic Simulation Considering Heterogeneous Driving Behaviors and Collision

Great differences present between human driving behaviors. It is essential to model the heterogeneous driving behavior affected by varies surrounding traffic environment and collision factors. Based on natural behavior rules, we build a decision-making model of driving behavior where car-following and lane-change are heterogeneous. A series of simulations were conducted as well as the vehicle's driving behavior, potential conflict, collision, congestion traffic flow evolution phenomena were investigated on major urban arterials. According to the operation data of vehicle agent output by simulation, the driver's heterogeneous speed regulation, lane change characteristics, accident impact, and space-time distribution of traffic flow are analyzed. Simulation results show that the braking acceleration of aggressive drivers is relatively small when the congestion is light. With the increase of congestion degree, conservative drivers tend to queue orderly, resulting in a faster decrease in their patience value, which makes all heterogeneous drivers generate lane change motivation when congestion is serious. The development of the collision group will aggravate the degree of congestion and the change of lanes is conducive to the dissipation of the congestion at the bottleneck. This model reflects the process of traffic flow collision, congestion and dissipation, which has reference significance for understanding the evolution of traffic flow and accident prevention.