Journal of Central South University

, Volume 25, Issue 5, pp 1182–1194 | Cite as

A mixed stochastic user equilibrium model considering influence of advanced traveller information systems in degradable transport network

  • Lin Cheng (程琳)
  • Xiao-ming Lou (楼小明)
  • Jing Zhou (周静)
  • Jie Ma (马捷)
Article

Abstract

Advanced traveler information systems (ATIS) can not only improve drivers’ accessibility to the more accurate route travel time information, but also can improve drivers’ adaptability to the stochastic network capacity degradations. In this paper, a mixed stochastic user equilibrium model was proposed to describe the interactive route choice behaviors between ATIS equipped and unequipped drivers on a degradable transport network. In the proposed model, the information accessibility of equipped drivers was reflected by lower degree of uncertainty in their stochastic equilibrium flow distributions, and their behavioral adaptability was captured by multiple equilibrium behaviors over the stochastic network state set. The mixed equilibrium model was formulated as a fixed point problem defined in the mixed route flows, and its solution was achieved by executing an iterative algorithm. Numerical experiments were provided to verify the properties of the mixed network equilibrium model and the efficiency of the iterative algorithm.

Key words

mixed stochastic user equilibrium model degradable transport network advanced traveler information systems (ATIS) drivers’ behavioral adaptability multiple equilibrium behaviors fixed point problem 

通行能力退化路网中考虑ATIS 信息影响的混合随机用户均衡模型研究

摘要

先进的出行者信息系统(简写ATIS)不仅能帮助出行者获取更准确的交通时间信息,还能提 高出行者在面对路网通行能力下降等随机事件时的应急和实时调整能力。本文提出了一类新的混合随 机用户均衡模型,用以描述在通行能力随机退化的路网中,装备ATIS 和未装备ATIS 两类出行者各自 的路径选择行为和由此形成的路网交通流均衡状态。在提出的模型中,ATIS 向出行者提供交通信息 的优势体现在路网流量均衡分布状态的随机性更低,而ATIS 对出行者适应路网能力随机退化的强化 优势,则通过路网流量的多均衡态加以体现。论文将该混合随机用户均衡模型表示成一个关于混合路 径流量的不动点问题,并设计了一类迭代求解算法。通过数值算例,论文分析了模型的相关数学特性, 并验证了迭代算法的求解效率。

关键词

混合随机用户均衡模型 可退化交通网络 先进的出行者信息系统(ATIS) 出行者行为适应性 多均衡行为 不动点问题 

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Copyright information

© Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of TransportationSoutheast UniversityNanjingChina
  2. 2.Zhejiang Development & Planning Research InstituteHangzhouChina
  3. 3.Zhejiang Institute of CommunicationsHangzhouChina

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