朋友圈信息交互对个体出行决策行为的影响研究

交通运输系统工程与信息 ›› 2013, Vol. 13 ›› Issue (6): 86-93.

朋友圈信息交互对个体出行决策行为的影响研究

刘天亮^*，张冲，王天歌，吴国寯

北京航空航天大学经济管理学院，北京 100191

收稿日期:2013-06-07 修回日期:2013-08-26 出版日期:2013-12-24 发布日期:2014-01-14
作者简介:刘天亮（1981-），男，山东济宁人，博士，副教授.
基金资助:
国家自然科学基金项目(71271001, 70901046)；国家重点基础研究发展计划项目(2012CB725401)；中央高校基本科研业务费(YWF-13-A02-005).

Effects of Friends’ Information Interaction on Travel Decisions

LIU Tian-liang,ZHANG Chong,WANG Tian-ge,WU Guo-jun

School of Economics and Management, Beihang University, Beijing 100191, China

Received:2013-06-07 Revised:2013-08-26 Online:2013-12-24 Published:2014-01-14

摘要/Abstract

摘要：

现有关于交通信息对出行决策影响的研究大多基于ATIS提供的交通信息，而探讨通过非正式的社交渠道即朋友圈获得的交通信息对出行决策的影响尚不多见.通过进行可控的交通行为实验，探讨了朋友圈的交通信息交互对个体出行决策行为的影响.实验结果表明：朋友圈交通信息交互率为33.3%时，系统整体达到最优；信息交互率为75%时，达到用户最优；当网络由系统最优移近用户最优时，人均出行时间与成本有所增加；相比用户最优，系统最优时的出发时刻调整情况比较分散，而路径选择情况则相对集中.

关键词: 城市交通；出行决策；实验研究；朋友圈信息交互, 系统最优

Abstract:

Many existing studies focus on the effects of traffic information from ATIS on travel choices. Research on the effect of friends’ travel information on people’s travel choice is uncommon, yet needed. In this paper, behavioral experiments are conducted to discuss what the effects of information interaction with friends can bring on individual travel decision behavior. The experimental results concluded that when the rate of friends’ information interaction reaches 33.3%, the whole system is at an optimal level. Furthermore, users reach an optimum when the rate of friends’ travel information interaction is 75%. The average time and cost per person is increasing when the whole system optimum transfers to the user optimum. Moreover, adjustments of departure time at the system optimum are more dispersed than at the user optimum, while travel choice changes are more concentrated.

Key words: urban traffic, travel decision, experimental study, information interaction with friends, system optimum

中图分类号:

U491

刘天亮，张冲，王天歌，吴国寯. 朋友圈信息交互对个体出行决策行为的影响研究[J]. 交通运输系统工程与信息, 2013, 13(6): 86-93.

LIU Tian-liang,ZHANG Chong,WANG Tian-ge,WU Guo-jun. Effects of Friends’ Information Interaction on Travel Decisions[J]. Journal of Transportation Systems Engineering and Information Technology, 2013, 13(6): 86-93.

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http://www.tseit.org.cn/CN/Y2013/V13/I6/86

参考文献

[1]吴文静,隽志才，罗清玉. 信息作用下出行者短期决策行为分析[J]. 交通运输系统工程与信息，2010，10(2)：100-105.[WU W J, JUAN Z C, LUO Q Y. Short-term choice of travelers with effect of traffic information[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(2): 100-105.]

[2]田丽君，黄海军，刘天亮. 基于动态信息反馈的日常出行决策模拟研究[J]. 交通运输系统工程与信息，2010，10(4)：79-85.[TIAN L J, HUANG H J, LIU T L. Day-to-day route choice decision simulation based on dynamic feedback information[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(4): 79-85.]

[3]赵凛.基于“前景理论”的出行决策模型及ATIS仿真实验研究[D]. 北京：北京交通大学,2006.[ZHAO L. Prospect theory-based models for traveler’s trip decision and simulation for ATIS[D]. Beijing: Beijing Jiaotong University, 2006.]

[4]李志纯，黄海军. 先进的旅行者信息系统对出行者选择行为的影响研究[J].公路交通科技，2005，22(2)：95-99.[LI Z C, HUANG H J. Modeling the impacts of advanced traveler information systems on travelers’ travel choice behaviors[J]. Journal of Highway and Transportation Research and Development, 2005, 22(2):95-99.]

[5]刘天亮，黄海军，陈剑. 考虑风险规避和认知更新的日常择路行为演进[J]. 交通运输工程学报，2008，8(4)：90-103.[LIU T L, HUANG H J, CHEN J. Evolution of day-to-day route choice behavior considering risk aversion and perception updating[J]. Journal of Traffic and Transportation Engineering, 2008, 8(4): 90-103.]

[6]刘天亮，黄海军.日常择路行为的多智能体模拟[J]. 物理学报，2007，56(11)：6321-6325.[LIU T L, HUANG H J. Multi agent simulation on day-to-day route choice behavior[J]. Acta Physica Sinica, 2007, 56(11):6321-6325.]

[7]Selten R, Chmura T, Pitz T, et al. Commuters route choice behavior [J]. Games and Economic Behavior,2007, 58: 394-406.

[8]Terry E Daniel, Eyran J Gisches, Amnon Rapoport. Departure times in Y-shaped traffic networks with multiple bottlenecks[J]. American Economic Review 2009, 99(5): 2149-2176.

[9]丁建勋，黄海军，唐铁桥. 一种考虑速度随机慢化概率动态演化的交通流元胞自动机模型[J]. 物理学报，2009，58(11)：7591-7595.[DING J X, HUANG H J, TANG T Q. A cellular automaton model of traffic considering the dynamic evolution of velocity randomization probability[J]. Acta Physica Sinica, 2009,58(11):7591-7595.]

[10]Kenneth A Small. The scheduling of consumer activities: Work trips[J].The American Economic Review,1982, 72(3):467-479.

[11]马寿峰，卜军峰，张安训. 交通诱导中系统最优与用户最优的博弈协调[J]. 系统工程学报，2005，20(1)：30-37.[ MA S F, BU J F, ZHANG A X. Game-based coordination method between system optimum and user equilibrium in route guidance system[J]. Journal of Systems Engineering, 2005, 20(1): 30-37.]