中国物理B ›› 2011, Vol. 20 ›› Issue (4): 40514-040514.doi: 10.1088/1674-1056/20/4/040514

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An improved cellular automaton model considering the effect of traffic lights and driving behaviour

卢伟真1, 何红弟2, 董力耘3   

  1. (1)Department of Building and Construction, City University of Hong Kong, Hong Kong, China; (2)Logistics Research Center and Shanghai Engineering Research Center of Shipping Logistics Information, Shanghai Maritime University, Shanghai 200135, China; (3)Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200072, China
  • 收稿日期:2010-09-24 修回日期:2010-11-05 出版日期:2011-04-15 发布日期:2011-04-15
  • 基金资助:
    Project supported by the Strategic Research Grants from City University of Hong Kong [Project No. CityU-SRG 7002370] and the National Natural Science Foundation of China (Grant No. 10972135), Science Foundation of Shanghai Maritime University (Grant No. 20110046) and the Science Foundation of Shanghai Science Commission (Grant Nos. 09DZ2250400 and 09530708200).

An improved cellular automaton model considering the effect of traffic lights and driving behaviour

He Hong-Di(何红弟)a), Lu Wei-Zhen(卢伟真)b)†, and Dong Li-Yun(董力耘)c)   

  1. a Logistics Research Center and Shanghai Engineering Research Center of Shipping Logistics Information, Shanghai Maritime University, Shanghai 200135, China; b Department of Building and Construction, City University of Hong Kong, Hong Kong, China; c Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200072, China
  • Received:2010-09-24 Revised:2010-11-05 Online:2011-04-15 Published:2011-04-15
  • Supported by:
    Project supported by the Strategic Research Grants from City University of Hong Kong [Project No. CityU-SRG 7002370] and the National Natural Science Foundation of China (Grant No. 10972135), Science Foundation of Shanghai Maritime University (Grant No. 20110046) and the Science Foundation of Shanghai Science Commission (Grant Nos. 09DZ2250400 and 09530708200).

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摘要： This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model, the characteristics of the urban traffic flow on a single-lane road are investigated under three different control strategies, i.e., the synchronized, the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control, while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.

关键词: traffic flow, cellular automaton, control strategy, vehicle density

Abstract: This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model, the characteristics of the urban traffic flow on a single-lane road are investigated under three different control strategies, i.e., the synchronized, the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control, while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.

Key words: traffic flow, cellular automaton, control strategy, vehicle density

中图分类号:  (Lattice theory and statistics)

  • 05.50.+q
64.70.-p (Specific phase transitions) 64.75.-g (Phase equilibria)