Ge H X, Dai S Q, Dong L Y, Xue Y
Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200072, China.
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Dec;70(6 Pt 2):066134. doi: 10.1103/PhysRevE.70.066134. Epub 2004 Dec 23.
An extended car following model is proposed by incorporating an intelligent transportation system in traffic. The stability condition of this model is obtained by using the linear stability theory. The results show that anticipating the behavior of more vehicles ahead leads to the stabilization of traffic systems. The modified Korteweg-de Vries equation (the mKdV equation, for short) near the critical point is derived by applying the reductive perturbation method. The traffic jam could be thus described by the kink-antikink soliton solution for the mKdV equation. From the simulation of space-time evolution of the vehicle headway, it is shown that the traffic jam is suppressed efficiently with taking into account the information about the motion of more vehicles in front, and the analytical result is consonant with the simulation one.
通过在交通中引入智能交通系统,提出了一种扩展的跟车模型。利用线性稳定性理论得到了该模型的稳定性条件。结果表明,预测前方更多车辆的行为会导致交通系统的稳定。应用约化摄动法推导了临界点附近的修正科特韦格-德弗里斯方程(简称为mKdV方程)。因此,交通拥堵可以用mKdV方程的扭结-反扭结孤子解来描述。从车头间距的时空演化模拟结果可以看出,考虑前方更多车辆的运动信息能有效地抑制交通拥堵,且分析结果与模拟结果一致。