交通流多预期延迟模型与数值仿真

为了更准确地描述交通流，考虑驾驶员反应延迟时间和前车信息的非均衡使用，建立一种多预期延迟跟驰模型。线性稳定性分析表明，驾驶员反应延迟时间的增加会降低交通流的稳定性，多个前车信息的使用可以提高交通流的稳定性。数值仿真的结果表明，减少司机的反映延迟时间和适当地增加前车信息都能提高交通流的稳定性。为尽可能少地引入输入变量，不均衡地利用前车的车间距和速度差信息是必要的。理论和数值模拟的结果均表明驾驶员反应延迟在交通拥堵的形成过程中起着重要作用。

A multi-anticipation delay model for traffic flow and numerical simulation

In order to describe the traffic flow more accurately, this paper proposed an extended multi-anticipation delayed car-following model by considering the reaction-time delay of drivers and using the unbalanced information of front vehicles. Linear stability analyses show that increasing the reaction-time delay of drivers weakens the stability of traffic flow. Appending the information of more vehicles ahead can enhance the stability. The results of numerical simulations demonstrate that decreasing the delay time or properly increasing the information from leading vehicles can promote the stability of traffic flow. It is necessary to unevenly use information of headways and velocity differences of front vehicles in order to introduce variables as little as possible. Both theoretical analysis and numerical simulations show that the reaction-time delay of drivers play an important role in the formation of traffic jams.