Microscopic traffic flow model based on multi-agent in CVIS circumstance

被引：0
|
作者：
Yang F. [1 ]
Yun M. [1 ]
Yang X. [1 ]
机构：
[1] Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University
来源：
Tongji Daxue Xuebao/Journal of Tongji University | 2012年 / 40卷 / 08期
关键词：
Cooperative vehicles infrastructure system; Decision strategy; Microscopic traffic flow; Multi-agent;
D O I：
10.3969/j.issn.0253-374x.2012.08.012
中图分类号：
学科分类号：
摘要：
Concepts and attributes list of vehicle multi-agent(VMAs) in cooperative vehicles infrastructure system(CVIS) are introduced at first. Decision strategies in both traditional and CVIS circumstance are compared to analyze differences in traffic status judgment and decision at intersections and links between two circumstances. Single lane traffic flow models in CVIS are established. Microscopic traffic flow models such as acceleration and deceleration are given too. Furthermore, the intersection impacts are taken into consideration in analyzing the signal influence. The numeral experiments analyze the trajectories and macroscopic parameters in both circumstances. The results show that VMAs in CVIS decline sharply in total travel time, average travel time and average delay time which indicate that vehicles in CVIS are more stable and successive than those in traditional circumstance. Besides, headway and velocity variances in CVIS are lower than those in traditional circumstance which increases the fleet stable.
引用
收藏
页码：1189 / 1196
页数：7
相关论文
共 21 条
  • [11] Dia H., An agent-based approach to modeling driver route choice behavior under the influence of real-time information, Transport Research Part C: Emerging Technologies, 10, (2002)
  • [12] Mandiau R., Champion A., Auberlet J.M., Et al., Behavior based on decision matrices for a coordination between agents in a urban traffic simulation, Applied Intelligence, 28, (2008)
  • [13] Wei Y., Han Y., Fan B., Agent-oriented urban traffic micro simulation system, Proceeding of the 8th International IEEE Conference on Industrial Technology, pp. 1-7, (2008)
  • [14] Ehlert P.A., Rothkrantz L.J.M., Microscopic traffic simulation with reactive driving agents, 2001 IEEE Intelligent Transportation Systems Conference Proceedings, pp. 861-866, (2001)
  • [15] Zhang F., Li J.L., Zhao Q.X., Single-lane traffic simulation with multi-agent system, Proceeding of the 8th International IEEE Conference on Intelligent Transportation Systems, pp. 1183-1187, (2005)
  • [16] Dai J., Li X., Multi-agent systems for simulating traffic behaviors, Chinese Science Bulletin, 55, 3, (2010)
  • [17] Ma X., Microcosmic traffic flow modeling and simulation based on multi-agent, (2008)
  • [18] Lian Z.T., Deshmukh A., Performance prediction of an unmanned airborne vehicle multi-agent system, European Journal of Operational Research, 172, (2006)
  • [19] Eissfeldt N., Wagner P., Effects of anticipatory driving in a traffic flow model, European Physical Journal B, 33, (2003)
  • [20] Bham G.H., Benekohal R.F., A high fidelity traffic simulation model based on cellular automata and car-following concepts, Transportation Research Part C: Emerging Technologies, 12, (2004)
123