考虑乘客心理的出租车合乘决策方法研究

交通运输系统工程与信息 ›› 2015, Vol. 15 ›› Issue (2): 17-23.

考虑乘客心理的出租车合乘决策方法研究

张薇，何瑞春*，肖强，马昌喜

兰州交通大学交通运输学院, 兰州730070

收稿日期:2014-10-23 修回日期:2014-12-24 出版日期:2015-04-25 发布日期:2015-04-27
作者简介:张薇（1980-），女，甘肃兰州人，讲师，博士生.
基金资助:
国家自然科学基金（61364026，51408288）.

A Method of Taxi Pooling Mode Decision-making with Passenger Psychology

ZHANGWei，HE Rui-chun，XIAO Qiang，MAChang-xi

School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China

Received:2014-10-23 Revised:2014-12-24 Online:2015-04-25 Published:2015-04-27

摘要/Abstract

摘要：

针对出租车合乘研究中缺少对乘客心理的考虑，基于前景理论构建出租车合乘模式决策模型，提出一种考虑乘客心理的合乘出行决策方法.考虑行程时间、费用、舒适度对乘客心理决策的影响，通过计算机模拟，分析不同付费比例和交通拥堵率在乘客心理因素影响下对乘客合乘决策的影响.研究结果表明，合乘付费比例对乘客合乘决策的影响较大，合乘比例随付费比例的降低而增加，0.7 的付费比例对多数乘客没有刺激作用；付费比例降至0.65 及其以下时，交通拥堵率对合乘比例的影响较小，合乘比例相对稳定. 所得结论对出租车合乘政策的制定与管理有一定的指导意义.

Abstract:

For the lack of considering passengers psychology in the taxi pooling research, a taxi mode choice model based on the prospect theory is established, and a taxi pooling decision method considering passengers psychology is proposed. Considering travel time, cost and comfort, the effects of different payment ratio and traffic congestion rate on passengers are analyzed through computer simulation. The results show that: the influence of taxi pooling payment ratio on the passengers decision is large, and taxi pooling proportion increases with the decrease of payment ratio. The payment ratio 0.7 cannot stimulate the most of the passengers. Traffic congestion rate has little effect on the taxi pooling proportion which is relatively stable when the payment ratio falls to 0.65 and below. These conclusions have a certain guiding significance to formulating taxi policy.

Key words: urban traffic, taxi pooling, prospect theory, passenger psychology

中图分类号:

U469.12

张薇，何瑞春，肖强，马昌喜. 考虑乘客心理的出租车合乘决策方法研究[J]. 交通运输系统工程与信息, 2015, 15(2): 17-23.

ZHANGWei，HE Rui-chun，XIAO Qiang，MAChang-xi. A Method of Taxi Pooling Mode Decision-making with Passenger Psychology[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(2): 17-23.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/abstract/abstract18952.shtml

http://www.tseit.org.cn/CN/Y2015/V15/I2/17

参考文献

[1] LIN Y, LI W, QIU F, et al. Research on optimization of vehicle routing problem for ride-sharing taxi[J]. Procedia-Social and Behavioral Sciences, 2012, 43: 494-502.

[2] Dimitrakopoulos G, Demestichas P, Koutra V. Intelligent management functionality for improving transportation efficiency by means of the car pooling concept[J]. Intelligent Transportation Systems, 2012, 13(2): 424- 436.

[3] Yan S Y, Chen C Y, Wu C C. Solution methods for the taxi pooling problem[J]. Transportation, 2012, 39(3): 723-748.

[4] Jiau M K, Huang S C, Lin C H. Optimizing the carpool service problem with genetic algorithm in service-based computing[C]// 2013 IEEE International Conference on Services Computing, 2013: 478-485.

[5] Manzini R, Pareschi A. A decision-support system for the car pooling problem[J]. Journal of Transportation Technologies, 2012, 2(2): 85-101.

[6] 邵增珍,王洪国,刘弘,等.车辆合乘匹配问题中服务需求分派算法研究[J].清华大学学报, 2013, 53 (2):252-258. [SHAO Z Z, WANG H G, LIU H, et al. Research on service requirement distribution algorithms in carpooling problems[J]. Journal of Tsinghua University, 2013, 53(2):252-258.]

[7] Chen Y T, Hsu C H. Improve the carpooling applications with using a social community based travel cost reduction mechanism[J]. International Journal of Social Science and Humanity, 2013, 3(2):87-91.

[8] Guo Y, Goncalves G, Hsu T. A clustering ant colony algorithm for the long-term car pooling problem[J]. International Journal of Swarm Intelligence Research, 2012, 3(2): 39-62.

[9] Galland S, Knapen L, Yasar A U H, et al. Multi-agent simulation of individual mobility behavior in carpooling[J]. Transportation Research Part C, 2014, 45: 83-98.

[10] Buliung R N, Soltys K, Bui R, et al. Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use[J]. Transportation, 2010, 37(6):849-873.

[11] Yan S, Chen C Y, Lin Y F. A model with a heuristic algorithm for solving the long-term many-to-many car pooling problem[J]. Intelligent Transportation Systems, 2011, 12(4): 1362-1373.

[12] De M R G, Daamen W, Hoogendoorn S. Expected utility theory, prospect theory, and regret theory compared for prediction of route choice behavior[J]. Transportation Research Record, 2011, 2230:19-28.

[13] 樊治平,陈发动,张晓.基于累积前景理论的混合型多属性决策方法[J].系统工程学报, 2012, 27(3): 295-301. [FAN Z P, CHEN F D, ZHANG X. Method for hybrid multiple attribute decision making based on cumulative prospect theory[J]. Journal of Systems Engineering, 2012, 27(3):295-301.]

[14] Jou R C, Chen K H. An application of cumulative prospect theory to freeway drivers’ route choice behaviours[J]. Transportation Research Part A: Policy and Practice, 2013,49:123-131.

[15] 潘晓锋, 左志, 赵胜川. 基于前景理论的改进多路径交通分配模型[J]. 交通运输系统工程与信息, 2014, 14(2): 162-167. [PAN X F, ZUO Z, ZHAO S C. Improved multi-path assignment model based on prospect theory[J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(2): 162-167.]

[16] Tversky A，Kahneman D. Advances in prospect theory: cumulative representation of uncertainty[J]. Journal of Risk and Uncertainty, 1992, 5(4):297-323.