基于混沌判据评价几类跟驰模型合理性的仿真研究

提出了一种评价交通流理论模型合理性的新方法:用交通流理论模型产生时间序列,计算这些时间序列的最大李雅普诺夫指数,用最大李雅普诺夫指数可以判断仿真交通流是否再现了交通流存在的混沌现象,以及反映的程度如何,进而评价交通流理论模型的合理性.文章介绍了方法的原理,给出了对伽赛斯-赫尔曼-伯兹(Gazis-Herman-Potts)模型;皮埃莱(Bierley)模型;洛克威尔-特莱德勒(Rock-well-Treiterer)模型三类典型的跟驰模型仿真实验的结果.分析了仿真结果,得出了有用的结论.

Simulation Research on Evaluating of Reasonability for the Car-Following Models Based on Chaos Criterion

In this paper, a new approach for evaluating of reasonability for the traffic flow models has been presented. The time serials of traffic flow are generated by the traffic flow model. The maximum Lyapunov exponents of the time serials of traffic flow are computed. The state of the chaos appearing can be analyzed using the maximum Lyapunov exponents. Analyzing the state of the chaos appearing, which includes weather there are chaos appearing and how is the level of the chaos appearing, then the reasonability of the car-following model can be evaluated. The principle of the approach is introduced. The simulation results for three typical Car-Following models (Gazis-Herman-Potts model, Bierley model, and Rockwell-Treiterer model) are given. The useful conclusion is obtained from the analysis of the simulation results.