交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (3): 15-20.

• 综合交通运输体系论坛 • 上一篇    下一篇

后悔视角下的运量分布与均衡配流组合模型

李梦,黄海军*   

  1. 北京航空航天大学经济管理学院,北京100191
  • 收稿日期:2015-09-30 修回日期:2016-04-16 出版日期:2016-06-25 发布日期:2016-06-27
  • 作者简介:李梦(1990-), 女, 新疆伊犁人, 博士生.
  • 基金资助:

    国家重点基础研究发展计划“ 973 ”项目/ National Key Basic Research Project of China(973 Program) (2012CB725401);中央高校基本科研业务费/Fundamental Research Funds for the Central Universities(YWF-16-JCTD-A-07)

A Combined Trip Distribution and Traffic Assignment Model under Regret Theory View

LI Meng,HUANG Hai-jun   

  1. School of Economics and Management,Beihang University,Beijing 100191,China
  • Received:2015-09-30 Revised:2016-04-16 Online:2016-06-25 Published:2016-06-27

摘要:

拓展交通行为的研究视角具有重要的学术价值和实践指导意义.出行路径选 择模型广泛假设出行者是完全理性的,总是选择其所认知到的期望效用最大或期望出行 成本最小的路径,这与现实生活中的有限理性行为之间出现了冲突.为了克服随机效用最 大原则下行为模型的缺陷,学者们发展了随机后悔最小模型.本文基于随机后悔最小原 则,构建了运量分布与均衡配流的组合后悔模型,并通过数值算例比较和解释了随机后 悔最小模型和随机效用最大模型的异同.算例结果表明,本文所提出的组合后悔模型从后 悔角度刻画了现实生活中出行者的出行行为特征.

关键词: 城市交通, 随机后悔最小, 后悔厌恶, 随机效用最大, 运量分布, 均衡配流

Abstract:

It is important to develop newly theoretical and practical approaches of studying various travel behaviors. The majority of route choice models assume that travelers are completely rational and always choose paths with the maximum expected utility or the minimum expected cost, which comes into conflict with bounded rational behavior in reality. Random regret minimization model has attracted scholars’ attention for overcoming the drawbacks inherent in random utility maximization model. This paper proposes a combined trip distribution and traffic assignment model under the principle of random regret minimization. Numerical results from an example are presented to compare and explain the similarities and differences between the two models governed by random regret minimization and random utility maximization, respectively. It is shown that the proposed model under regret theory view could more realistically depict travelers’route choice behavior.

Key words: urban traffic, random regret minimization, regret aversion, random utility maximization, trip distribution, equilibrium assignment

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