路网规模对出行者路径选择转换的影响

王文颖,郭仁拥,孙悦朋

交通运输研究 ›› 2020, Vol. 6 ›› Issue (2) : 48-59.

PDF(2017 KB)
PDF(2017 KB)
交通运输研究 ›› 2020, Vol. 6 ›› Issue (2) : 48-59.

路网规模对出行者路径选择转换的影响

  • 王文颖,郭仁拥,孙悦朋
作者信息 +

Impact of Road Network Scale on Travelers′ Route Choice Switching

  • Wang Wen-ying, Guo Ren-yong, Sun Yue-peng
Author information +
文章历史 +

摘要

为预测交通流的演化动态,提高交通系统运行效率,需研究路网规模与出行者路径选择转换行为间的关系。首先设计并实施实验室行为实验,收集出行者实际路径选择相关数据。行为实验涉及4个不同规模的虚拟道路网络,30名参与者基于以往的出行信息(即出行时间)在虚拟路网上进行路径选择。然后利用假设检验、回归分析等统计方法对收集到的实验数据进行分析。分析结果表明:随着路网规模的增大,路网达到用户均衡(User Equilibrium, UE)状态的次数减少。对各路网用户均衡状态与系统最优(System Optimum, SO)状态的对比表明:各路径流量的平均值都很接近于UE值,而与SO值相差较大。从逐日路径流量演化和个体选择可变性两方面分析了路网规模与路径选择转换间的关系,发现逐日路径选择转换人数(或个体路径选择转换数量)与路网规模呈正线性相关。此外,个体路径选择转换频率与平均经验出行时间显著相关。由此得出结论:单方面扩大路网规模并不总能促进路网交通流演化到用户均衡状态,且出行时间与个体路径选择转换数量存在幂函数关系。

Abstract

To predict the evolution of traffic flow and improve the efficiency of a transport system, the relation between travelers′ route choice switching and road network scale needs studying. First, a laboratory behavioral experiment was designed and conducted to collect data associated with travelers′ route choice decisions. In the laboratory experiment, four virtual networks with different scales were involved. 30 participants were asked to make route choices on these networks based on previous travel information (i.e. travel cost). Then, statistical methods, such as hypothesis test and regression analysis, were used to analyze the collected data. Analysis results showed that the network was less likely to achieve user equilibrium (UE) with its scale expanding. The UE state and system optimum (SO) state were compared. It was found that the average flow on each path was closed to the corresponding UE value; however, it showed a higher deviation from the corresponding SO value. Further, the relationship between travelers′ route choice switching and road network scale was explored from two aspects, i.e. the day-to-day evolution of path flows and the choice variability of individuals. Both the numbers of people making daily path switch and individuals′ route choice switching were positively correlated with the road network scale. The frequency of individuals′ route choice switching was significantly correlated to the average of individuals′ travel time. Therefore, it can be concluded that increasing the scale of the road network doesn’t necessarily lead to the evolution of flows to UE state. Moreover, for individual travelers, a power function relationship exists between travel time and the number of route choice switching.

关键词

城市交通 / 路径选择转换 / 路网规模 / 用户均衡 / 系统最优

Key words

urban traffic / route choice switching / road network scale / user equilibrium / system optimum

引用本文

导出引用
王文颖,郭仁拥,孙悦朋. 路网规模对出行者路径选择转换的影响[J]. 交通运输研究. 2020, 6(2): 48-59
Wang Wen-ying, Guo Ren-yong, Sun Yue-peng. Impact of Road Network Scale on Travelers′ Route Choice Switching[J]. Transport Research. 2020, 6(2): 48-59

参考文献

[1]何晶. 道路网结构复杂性定量测度方法研究[D]. 成都:西南交通大学,2016.
[2]刘玉印. 出行者有限理性条件下的网络均衡分析及其应用研究[D]. 广州:华南理工大学,2011.
[3]刘玉印,刘伟铭,田世艳. 出行者有限理性条件下混合策略网络均衡模型[J]. 公路交通科技,2011,28(7):136-141.
[4]徐红利,周晶,徐薇. 考虑参考点依赖的随机网络用户均衡与系统演化[J]. 系统工程理论与实践,2010,30(12):2283-2289.
[5]赵传林,黄海军. 基于满意准则的有限理性用户均衡流量分配性质研究[J]. 系统工程理论与实践,2014,34(12):3073-3078.
[6]黄海军,吴文祥. 交通信息对交通行为影响的评价模型[J]. 系统工程理论与实践,2002,22(10):81-83,104.
[7]王昕,黄海军. 多用户弹性需求网络的双准则系统最优交通分配[J]. 系统工程理论与实践,2011,31(S1):94-102.
[8]Selten R, Chmura T, Pitz T, et al. Commuters Rou-te Choice Behavior[J]. Games and Economic Behavior, 2007, 58(2): 394-406.
[9]Iida Y, Akiyama T, Uchida T. Experimental Analysis of Dynamic Route Choice Behavior[J]. Transportation Research Part B: Methodological, 1992, 26(1): 17-32.
[10]Albert G, Toledo T, Ben-Zion U. The Role of Personality Factors in Repeated Route Choice Behavior: Behavioral Economics Perspective[J]. European Transport, 2011, 48: 47-59.
[11]Mahmassani H S, Liu Y H. Dynamics of Commuting Decision Behaviour under Advanced Traveller Information Systems[J]. Transportation Research Part C: Emerging Technologies, 1999, 7(2-3): 91-107.
[12]Tawfik A M, Rakha H A, Miller S D. An Experimental Exploration of Route Choice: Identifying Drivers Choices and Choice Patterns, and Capturing Network Evolution[C]// 13th International IEEE Conference on Intelligent Transportation Systems. Madeira Island, Portugal: IEEE, 2010: 1005-1012.
[13]Tawfik A M, Szarka J, House L, et al. Disaggregate Route Choice Models Based on Driver Learning Patterns and Network Experience[C]// 14th International IEEE Conference on Intelligent Transportation Systems. Washington DC: IEEE, 2011: 445-450.
[14]李傲宁. 路径选择实验数据收集系统的设计实现与应用[D]. 呼和浩特:内蒙古大学,2019.
[15]黄海军. 城市交通网络平衡分析——理论与实践[M]. 北京:人民交通出版社,1994.
[16]李乐园,张小宁,张红军. 基于交通瓶颈的动态交通分配模型[J]. 系统工程理论与实践,2006,26(4):125-129.
[17]Meneguzzer C, Olivieri A. Day-to-Day Traffic Dynamics: Laboratory-Like Experiment on Route Choice and Route Switching in a Simple Network with Limited Feedback Information[J]. Procedia-Social and Behavioral Sciences, 2013, 87: 44-59.

基金

国家自然科学基金项目(71622005)

PDF(2017 KB)

Accesses

Citation

Detail

段落导航
相关文章

/