基于TPI数据的居民出行路径选择行为研究

doi:10.3969/j.issn.1674-0696.2021.12.10

摘要/Abstract

摘要： 考虑出行者的未知出行环境风险，基于前景理论，引入出行偏好等特征构建路径选择模型。基于实测数据，考虑路径行驶时间、红绿灯的等待时间等设置出行时间参考点，推导价值函数和决策权重函数；作备选路径的前景值与参考点的变化关系图，并将调查问卷数据与模型的结果进行对比检验。研究结果表明：前景理论能有效描述出行者的路径选择行为，参考点设定的大小对出行者的路径选择具有重要影响；参考点越大，两条备选路径的前景值越接近。因此，交通管理决策者应当根据路径的属性特点优化OD间网络结构，实现OD间的交通流状态达到平衡。

关键词: 交通运输工程；城市交通；路径选择；前景理论；出行环境风险；TPI数据

Abstract: Considering the travelers unknown travel environment risk, based on the prospect theory, the characteristics of travel preferences were introduced to construct the route choice model. Based on the measured data, the travel time reference point was set by considering the travel time and the waiting time of traffic lights, etc., and the value function and decision weight function were derived. The change relationship diagram between the prospect value of the alternative path and the reference point was made, and the questionnaire data was compared with the results of the model. The research results show that: the prospect theory can effectively describe the route choice behavior of the traveler. The size of the reference point has an important influence on the route choice of the traveler. The larger the reference point, the closer the prospect values of the two alternative routes. Therefore, the traffic management decision-maker should optimize the network structure between OD according to the attribute characteristics of the route, so as to achieve the balance of the traffic flow state between OD.

Key words: traffic and transportation engineering; urban traffic; route choice; prospect theory; travel environmental risk; TPI data

中图分类号:

U491.4

孙秋霞，张玉，赵术兰. 基于TPI数据的居民出行路径选择行为研究[J]. 重庆交通大学学报（自然科学版）, 2021, 40(12): 62-68.

SUN Qiuxia, ZHANG Yu, ZHAO Shulan. Residents Route Choice Behavior Based on TPI Data[J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(12): 62-68.

参考文献

［1］ NEUMAN J V, MORGENSTERN O.The Theory of Games and Economic Behavior［M］. New Jersey: Princeton University Press, 1944.
［2］ SAVAGE L J.The Foundations of Statistics［M］. New York: Wiley, 1954.
［3］ MANSKI C F. The structure of random utility models［J］.Theory and Decision, 1977, 8(3):229-254.
［4］ COLIN C. Bounded rationality in individual decision making［J］.Experimental Economics, 1998, 1(2):163-183.
［5］ FUJII S, KITAMURA R. Fra ming uncertain travel times: a re-exa mination of departure time choice［C］∥Proceedings of the 8th International Conference on Travel
Behavior Research. Queensland, Australia, 2000.
［6］ KAHNEMAYN D, TVERSKY A. Prospect theory: An analysis of decisions under risk［J］. Econometrica, 1979, 47(2):263-291.
［7］ TVERSKY A, KAHNEMAN D. Rational choice and the fra ming of decisions［J］. Journal of Business, 1986, 59(4):251-278.
［8］ TVERSKY A, KAHNEMAN D. Advances in prospect theory: Cumulative representation of uncertainty［J］.Journal of Risk and Uncertainty, 1992, 5(4):297-323.
［9］赵凛，张星臣. 基于“前景理论”的先验信息下出行者路径选择模型［J］.交通运输系统工程与信息，2006，6(2)：42-46.
ZHAO Lin, ZHANG Xingchen. Traveler route selection model based on a priori information of “prospect theory”［J］. Transportation System Engineering and
Information, 2006, 6(2):42-46.
［10］赵凛，张星臣.基于“前景理论”的路径选择行为建模及实例分析［J］.土木工程学报，2007，40(7)：82-86.
ZHAO Lin, ZHANG Xingchen. Path selection behavior modeling and case analysis based on “foreground theory”［J］.Journal of Civil Engineering, 2007, 40(7):82-86.
［11］田丽君，吕成锐，黄海军.基于出行时间区间数和参考点的择路行为研究［J］.系统科学与数学，2018，38(4)：395-405.
TIAN Lijun, LYU Chengrui, HUANG Haijun. Research on route selection behavior based on travel time interval numbers and reference points［J］. Systems Science and
Mathematics, 2018, 38(4):395-405.
［12］黄中祥，王任映，况爱武.基于预算时间的路径选择模型参照点设定方法［J］.交通科学与工程，2009，25(3)：75-79.
HUANG Zhongxiang, WANG Renying, KUANG Aiwu. Reference point setting method of route selection model based on budget time［J］.Transportation Science and
Engineering, 2009, 25(3):75-79.
［13］史国琪.基于前景理论的出行路径选择模型研究［D］.兰州：兰州交通大学，2017.
SHI Guoqi.Research on Travel Route Selection Model Based on Prospect Theory［D］. Lanzhou: Lanzhou Jiaotong University, 2017.
［14］ FAN Z P, ZHANG X, CHEN F D, et al. Multiple attribute decision making considering aspiration-levels: A method based on prospect theory［J］.Computers and
Industrial Engineering, 2013, 65(2):341-350.
［15］徐爱庆，陈欣，朱金福.基于累积前景理论的机场群旅客出行决策行为分析［J］.交通运输系统工程与信息，2018，18(6)：14-21.
XU Aiqing, CHEN Xin, ZHU Jinfu. Analysis of travel decision behavior of airport group passengers based on cumulative prospect theory［J］.Transportation System
Engineering and Information, 2018, 18(6):14-21.
［16］夏金娇，隽志才.基于前景理论的出行者路径选择行为［J］.公路交通科技，2012，29(4)：126-131.
XIA Jinjiao, JUN Zhicai. Traveler routing behavior based on prospect theory［J］.Highway Transportation Science and Technology, 2012, 29(4):126-131.
［17］杨志勇，颜贵云.基于前景理论的动态路径选择模型［J］.大连交通大学学报，2010，31(1)：53-58.
YANG Zhiyong, YAN Guiyun. Dynamic path selection model based on prospect theory［J］.Journal of Dalian Jiaotong University, 2010, 31(1):53-58.
［18］闫乃帅，曹凯.风险路网环境下出行者路径选择决策建模对比分析［J］.山东理工大学学报，2010，24(5)：77-81,85.
YAN Naishuai, CAO Kai. Comparative analysis of decision-making modeling of travelers path selection under risk road network environment［J］.Journal of Shandong
University of Technology, 2010, 24(5):77-81,85.
［19］ XU H L, ZHOU J, XU W. A decision- making rule for modeling travelers route choice behavior based on cumulative prospect theory［J］. Transportation Research
Part C, 2011, 19(2):218-228.
［20］青岛公安交通信息服务网［EB/OL］.［2014-09-22］. http:∥www.qdznjt.com/trafficIndex/realTimeIndex.html.
Qingdao PublicSecurity Traffic Information Service Network［EB/OL］.［2014-09-22］.http:∥www.qdznjt.com/trafficIndex/realTimeIndex. html. 
［21］孙军霞.出行者路径选择行为研究［D］.兰州：兰州交通大学，2017.
SUN Junxia.Research on TravelerS Route Choice Behavior［D］. Lanzhou: Lanzhou Jiaotong University, 2017.

[1]	秦雅琴1，郑号染1，2，李剑仕1. 基于视频的城市道路超车行为影响因素模型[J]. 重庆交通大学学报（自然科学版）, 2021, 40(01): 17-22.
[2]	Ayalew Mesfin Mitiku,邵毅明,张磊,王蓉,彭金栓. 某乘用车车道偏离预警系统测试与评价[J]. 重庆交通大学学报（自然科学版）, 2020, 39(11): 141-146.
[3]	邓明君，陈佳，姚宇. 基于公交优先与综合待行区的交叉口信号控制研究[J]. 重庆交通大学学报（自然科学版）, 2020, 39(08): 36-44.
[4]	吴文青1，夏杰2. Simpson改进的灰色神经网络在汽车保有量中的预测[J]. 重庆交通大学学报（自然科学版）, 2019, 38(09): 101-108.
[5]	孙祥龙1，冯树民2. 基于VISSIM仿真的公交停靠时间对交叉口延误影响研究[J]. 重庆交通大学学报（自然科学版）, 2019, 38(05): 97-101.
[6]	唐少虎1, 刘小明2, 朱伟1, 郑建春1, 郑国荣2. 基于硬件在环仿真的城市路网交通控制平台[J]. 重庆交通大学学报（自然科学版）, 2019, 38(04): 1-8.
[7]	徐建闽1, 2, 邹祥莉1, 马莹莹1. 拥堵条件下的快速路出口匝道交叉口与下游交叉口协同控制方法研究[J]. 重庆交通大学学报（自然科学版）, 2019, 38(04): 9-14.
[8]	丁恒1，朱良元1,2，蒋程镔1，郑小燕1. 基于宏观基本图的快速路网交通状态识别方法[J]. 重庆交通大学学报（自然科学版）, 2018, 37(12): 77-83.
[9]	成卫1，唐逸超1，郑佐雄2. 基于感应控制的过饱和交叉口流量转移方法研究[J]. 重庆交通大学学报（自然科学版）, 2018, 37(11): 83-90.
[10]	赵怀明1，谭宇2，李博威2. 在途交通信息对出行者路径选择的影响研究[J]. 重庆交通大学学报（自然科学版）, 2018, 37(08): 88-95.
[11]	慈玉生1，郑淑妮1，赵韩涛2. 基于过街人数分布的路段机动车延误经验模型[J]. 重庆交通大学学报（自然科学版）, 2018, 37(06): 76-80.
[12]	成卫1，王勇1，袁满荣2. 基于交通运行效益评价的综合待行区预信号控制研究[J]. 重庆交通大学学报（自然科学版）, 2017, 36(11): 78-84.
[13]	姜康,石章鹏,陈熹,张卫华. 基于服务水平的道路施工交通影响范围确定方法[J]. 重庆交通大学学报（自然科学版）, 2016, 35(4): 106-111.
[14]	冯忠祥，雷叶维，周穆雄，张卫华，刘晓峰，王锟. 修订版驾驶愤怒量表在中国驾驶人中的效信度分析[J]. 重庆交通大学学报（自然科学版）, 2016, 35(4): 141-145.
[15]	张卫华，韩高峰，颜冉，卫立阳. 城市道路路段可变车道设置效果评价方法[J]. 重庆交通大学学报（自然科学版）, 2014, 33(4): 128-133.