基于前景值的多类型出行者逐日路径选择模型

计算机工程与科学

基于前景值的多类型出行者逐日路径选择模型

陈玲娟1,2，代炯1，王殿海2

(1.武汉科技大学汽车与交通工程学院,湖北武汉 430081;2.浙江大学建筑工程学院,浙江杭州 310058)

收稿日期:2015-11-24 修回日期:2016-03-28 出版日期:2017-07-25 发布日期:2017-07-25
基金资助:
国家自然科学基金（51308425）；博士后基金（2014M561762）；湖北省厅教育中青年人才项目（Q20161102）

A multi-type travelers’ day-to-day route

choice model based on prospect theory

CHEN Ling-juan1，2，DAI Jiong1,WANG Dian-hai2

（1.School of Automobile and Traffic Engineering,Wuhan University of Science and Technology,Wuhan 430081;

2.College of Civil Engineering and Architecture,Zhejiang University,Hangzhou 310058,China）

Received:2015-11-24 Revised:2016-03-28 Online:2017-07-25 Published:2017-07-25

摘要/Abstract

摘要：

为研究非平衡态下的出行者逐日路径选择行为，以前景理论为基础，综合考虑出行者对路网随机性和逐日路径调整行为中的有限理性，基于出行经验数据逐日更新预留出行时间参考点，根据有限记忆规则和理解行程时间更新计算逐日路径前景值，并构建基于转移系数的逐日流量更新规则。最后结合算例分析了有限理性、完全理性、完全历史信息和非完全历史信息出行者所占比例及预留行程时间可靠度值对路网达到平衡态的演化时间及最终流量分布状态的影响。

关键词: 逐日路径选择, 前景理论, 有限理性

Abstract:

In order to study the travel behavior of day-to-day path choice under the state of non-equilibrium, based on the prospect theory, we take the randomness of network and limited rationality of path choice into consideration. Based on daily travel experience data, reserved travel time reference points are updated. According to the finite memory rule and travel time updating mechanism, the day-to-day path prospect is calculated. Then, the day-to-day path flow updating rule based on transfer coefficients is established. Finally, we analyze the influence of the proportion of four kinds of travelers (limited rationality, total rationality, total historical information and limited historical information) and the reserved travel time reliability on the evolutionary time of the network to reach the equilibrium state and the final path flow distribution state.

Key words: day-to-day route choice, prospect theory, limited rationality

陈玲娟1,2，代炯1，王殿海2. 基于前景值的多类型出行者逐日路径选择模型[J]. 计算机工程与科学.

CHEN Ling-juan1，2，DAI Jiong1,WANG Dian-hai2.

A multi-type travelers’ day-to-day route

choice model based on prospect theory

[J]. Computer Engineering & Science.