Mean-Risk Traffic Assignment Under the Continuously Distributed Risk-Aversion Factor

• 成果类型: Article
• 署名作者: Xu, Zhandong; Li, Zhengyang; Xie, Jun; Chen, Anthony; Liu, Xiaobo
• 署名单位: Southwest Jiaotong University; Hong Kong Polytechnic University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2024.1027
• 发表日期: 2026
• 关键词: travel-time reliability; shortest-path problem; equilibrium-model; step-size; network; algorithm; multiclass; transport

摘要

This study generalizes the single-class traffic assignment problem of Nikolova and Stier-Moses [Nikolova and Stier-Moses (2014) A mean-risk model for the traffic assignment problem with stochastic travel times. Oper. Res. 62(2):366-382] by considering the continuously distributed risk-aversion factor, termed the continuous mean-risk traffic assignment (CMRTA) problem. In CMRTA, travelers categorized into infinitely many user classes play a congestion routing game based on their risk attitude toward the mean-standard deviation trade-off. We identify and verify the following finite-dimensional complementarity condition: All used paths must have an equal and minimum virtual cost, called the cumulative path cost, which enables the characterization of Wardrop's equilibrium for CMRTA. Based on this result, we present general formulations to model CMRTA problems with exogenous and endogenous variability sources. A tailored path-based column generation with the gradient projection algorithm is then proposed to solve large-scale problems. The results show that CMRTA is more computationally efficient and less memory intensive than the traditional discrete multiclass method.