计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (5): 232-235.DOI: 10.3778/j.issn.1002-8331.2009.05.068

• 工程与应用 • 上一篇    下一篇

仿真交通流混沌转化过程研究

李 松1,2,刘力军3,贺国光2   

  1. 1.河北大学 管理学院,河北 保定 071002
    2.天津大学 系统工程研究所,天津 300072
    3.河北经济贸易大学 旅游学院,石家庄 050061
  • 收稿日期:2008-01-03 修回日期:2008-03-13 出版日期:2009-02-11 发布日期:2009-02-11
  • 通讯作者: 李 松

Study on transformation process of chaos in simulation traffic flow based on distance headway

LI Song1,2,LIU Li-jun3,HE Guo-guang2   

  1. 1.School of Management,Hebei University,Baoding,Hebei 071002,China
    2.Institute of Systems Engineering,Tianjin University,Tianjin 300072,China
    3.School of Tourism,Hebei University of Economics and Business,Shijiazhuang 050061,China
  • Received:2008-01-03 Revised:2008-03-13 Online:2009-02-11 Published:2009-02-11
  • Contact: LI Song

摘要: 为分析交通流混沌转化机理,探讨了车头间距和交通流混沌之间的关系。利用Matlab软件编制皮埃莱(Bierley)模型来产生仿真交通流时间序列,在一定参数组合情况下,研究了交通流车队中前后车辆的车头间距变化过程。通过分析这种车头间距变化曲线相轨迹,可以明显地观察到交通流混沌运动和有序运动之间的转化过程;在此基础上,应用最大Lyapunov指数改进算法对仿真交通流混沌转化过程进行了理论分析,讨论了车头间距对交通流混沌转化过程的影响作用。研究表明,车头间距的变化是交通流混沌现象产生和转化的根本原因。该研究结果有助于进一步理解交通流混沌现象,并为短时交通流预测和智能交通控制提供理论依据。

Abstract: The relationship between distance headway and chaos in traffic flow is investigated in order to analyze the transformation mechanism of chaos in traffic flow.The simulation time series of traffic flow is generated based on Bierley car-following model,which is programmed using Matlab.The changing processes of distance headway of the front vehicle and the following vehicle in the traffic flow are analyzed under the parameters combinations.From the orbit in phase space the transformation process between chaos and order motion can be seen clearly.The transformation processes of chaos in traffic flow are investigated with the improved algorithm for largest Lyapunov exponent.The influence of distance headway to the transformation process of chaos in traffic flow is discussed.The research shows that the change in distance headway is the main factor causing chaos and its transformation in traffic flow.The results are helpful to understand the chaos in traffic flow and provide theoretical foundation for the short time traffic flow forecasting and intelligent transportation control.