中国物理B ›› 2012, Vol. 21 ›› Issue (6): 68901-068901.doi: 10.1088/1674-1056/21/6/068901

• GEOPHYSICS, ASTRONOMY, AND ASTROPHYSICS • 上一篇    下一篇

A genetic resampling particle filter for freeway traffic-state estimation

毕军, 关伟, 齐龙涛   

  1. Key Laboratory for Urban Transportation Complex Systems Theory and Technologyof the Ministry of Education, Beijing Jiaotong University, Beijing 100044, China
  • 收稿日期:2011-10-19 修回日期:2011-12-06 出版日期:2012-05-01 发布日期:2012-05-01
  • 基金资助:
    Project supported by the National High Technology Research and Development Program of China (Grant No. 2011AA110303).

A genetic resampling particle filter for freeway traffic-state estimation

Bi Jun(毕军)†, Guan Wei(关伟), and Qi Long-Tao(齐龙涛)   

  1. Key Laboratory for Urban Transportation Complex Systems Theory and Technologyof the Ministry of Education, Beijing Jiaotong University, Beijing 100044, China
  • Received:2011-10-19 Revised:2011-12-06 Online:2012-05-01 Published:2012-05-01
  • Contact: Bi Jun E-mail:bilinghc@163.com
  • Supported by:
    Project supported by the National High Technology Research and Development Program of China (Grant No. 2011AA110303).

PDF (PC)

775

赞

摘要： On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control. Because a nonlinear feature exists in the traffic state, and because particle filters have good characteristics when it comes to solving the nonlinear problem, a genetic resampling particle filter is proposed to estimate the state of freeway traffic. In this paper, a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object. By analysing the traffic-state characteristics of the freeway, the traffic is modeled based on the second-order validated macroscopic traffic flow model. In order to solve the particle degeneration issue in the performance of the particle filter, a genetic mechanism is introduced into the resampling process. The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail, and the filter estimation performance is validated and evaluated by the achieved experimental data.

关键词: particle filter, genetic mechanism, traffic-state estimation, traffic flow model

Abstract: On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control. Because a nonlinear feature exists in the traffic state, and because particle filters have good characteristics when it comes to solving the nonlinear problem, a genetic resampling particle filter is proposed to estimate the state of freeway traffic. In this paper, a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object. By analysing the traffic-state characteristics of the freeway, the traffic is modeled based on the second-order validated macroscopic traffic flow model. In order to solve the particle degeneration issue in the performance of the particle filter, a genetic mechanism is introduced into the resampling process. The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail, and the filter estimation performance is validated and evaluated by the achieved experimental data.

Key words: particle filter, genetic mechanism, traffic-state estimation, traffic flow model

中图分类号:  (Land transportation)

  • 89.40.Bb
45.70.Vn (Granular models of complex systems; traffic flow) 07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)