车头时距
预测(人工智能)
非线性系统
流量(计算机网络)
理论(学习稳定性)
交叉口(航空)
计算机科学
控制理论(社会学)
流量(数学)
模拟
过程(计算)
工程类
机械
物理
人工智能
航空航天工程
量子力学
操作系统
机器学习
控制(管理)
计算机安全
作者
Ammar Jafaripournimchahi,Lu Sun,HU Wu-sheng
摘要
We developed a new car-following model to investigate the effects of driver anticipation and driver memory on traffic flow. The changes of headway, relative velocity, and driver memory to the vehicle in front are introduced as factors of driver’s anticipation behavior. Linear and nonlinear stability analyses are both applied to study the linear and nonlinear stability conditions of the new model. Through nonlinear analysis a modified Korteweg-de Vries (mKdV) equation was constructed to describe traffic flow near the traffic near the critical point. Numerical simulation shows that the stability of traffic flow can be effectively enhanced by the effect of driver anticipation and memory. The starting and breaking process of vehicles passing through the signalized intersection considering anticipation and driver memory are presented. All results demonstrate that the AMD model exhibit a greater stability as compared to existing car-following models.
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