交通运输系统工程与信息 ›› 2013, Vol. 13 ›› Issue (6): 120-126.

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信息系统下弹性需求随机用户均衡演化模型

度巍*1,黄崇超2,肖海燕3,王先甲4   

  1. 1.南通大学 交通学院, 江苏 南通 226019; 2. 武汉大学 数学与统计学院, 武汉 430072;3. 湖北第二师范学院 数学与数量经济学院, 武汉 430205; 4. 武汉大学 系统工程研究所, 武汉430072
  • 收稿日期:2013-03-29 修回日期:2013-05-19 出版日期:2013-12-24 发布日期:2014-01-14
  • 作者简介:度巍(1982-),男,湖北荆州人,讲师,博士.
  • 基金资助:

    国家自然科学基金(71171133,71231007,71071119);上海市优秀青年教师基金(jr10007).

Stochastic User Equilibrium Evolutionary Model with Elastic Demand and Advanced Traveler Information Systems

DU Wei1,HUANG Chong-chao2,XIAO Hai-yan3,WANG Xian-jia4   

  1. 1. School of Transportation, Nantong University, Nantongi 226019, Jiangsu, China;2. School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China;3. School of Mathematics and Quantitative Economics, Hubei University of Education, Wuhan 430205, China;4. Institute of Systems Engineering, Wuhan University, Wuhan 430072, China
  • Received:2013-03-29 Revised:2013-05-19 Online:2013-12-24 Published:2014-01-14

摘要:

本文研究了先进交通信息系统下城市网络交通流的动态演化行为.网络交通流的演化过程中,出行者不断调整自己的出行行为.在存在交通信息系统的路网中,出行者通过接受交通信息系统的路网信息和自己的出行经验选择出行路径. 考虑在交通需求为弹性的情况下,按照出行者对交通信息的接受程度,将出行者分为保守和乐观两种类型.通过引入刻画交通流演化的Logit动态方程,得到对应的弹性需求随机用户均衡交通流演化模型.并分析了模型中保守型出行者所占比例对交通流演化的影响,得出保守型出行者所占比例越大,均衡状态下的路径费用越高,路径流量越小.最后通过数值仿真进一步验证了分析结论.

关键词: 城市交通, 演化模型, Logit动态, 网络交通流, 交通信息系统, 随机用户均衡

Abstract:

The paper investigates the dynamic behavior of urban network traffic flow. In the evolution process of traffic flow in the urban network, travelers adjust the day-to-day route choice. In a traffic network served by advanced traveler information systems (ATIS), travelers always choose their routes based on experiments on traffic condition and current network information provided by the ATIS. With different attitudes toward ATIS service, the paper divides all the travelers into two types, namely optimism and conservatism, and then examine their travel time determination. Integrateing the Logit dynamics with the above work, this study further develops the network traffic flow evolutionary model considering stochastic user equilibrium with elastic demand with ATIS. In the last section, a numerical example is given to illustrate the evolution process of the model. Simulation results indicate the proportion of conservative travelers exerts effects on the final state of traffic flow.

Key words: urban traffic, evolutionary model, Logit dynamics, network traffic flow, advanced traveler information systems, stochastic user equilibrium

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