基于拓扑的有限理性日常流量分配模型

IF 12.5 Q1 TRANSPORTATION
Enrico Siri, Silvia Siri, Simona Sacone
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引用次数: 7

摘要

本文分析了运输网络中用户行为的日常调整过程,该过程受到相关变化的影响,例如由于关键事件导致的中断,导致一个或多个链路无法使用。为了表示网络上流量的渐进调整以达到新的均衡,基于人们在选择中是有限理性的思想,即人们通常不会按照最优解行事,而是接受他们认为满意的解,提出了一个日常离散时间模型。用户在选择过程中,会受到当前使用的路由与其他路由拓扑相似性的影响。这意味着他们倾向于选择与他们正在使用的解决方案更相似的解决方案。与此同时,用户也会表现出一种短视的行为,即,当他们使用一条路线时,如果他们突然体验到与他们习惯的路线相比,旅行时间大幅减少,他们往往会高估路线的优点。本文证明了这种路径选择行为意味着系统的稳态对应于有界理性用户均衡,即当给定拓扑相似性的相对重要性增加时,系统的稳态不会偏离用户均衡超过某一值。该模型还假设,在足够长的时间后,这些偏差会消失,至少对于那些用户最常使用的路线来说是这样。在一定条件下,稳态最终会崩溃为用户平衡。通过仿真结果评估了所提出模型的有效性,其中详细分析了两个测试网络,以显示中断后运输网络中用户行为的演变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A topology-based bounded rationality day-to-day traffic assignment model

This paper analyzes the day-to-day adjustment process of users’ behaviors in a transport network which is affected by relevant alterations such as disruptions due to critical events which cause the impossibility to use one or more links. For representing the progressive adjustment of the flows on the network to reach a new equilibrium, a day-to-day discrete-time model is proposed, based on the idea that people are bounded rational in their choices, i.e. they often do not behave according to the optimal solution but they accept solutions they consider satisfying. Users, in their choice process, are influenced by the topological similarity between the route they are currently using and others. This means that they tend to prefer the solutions that are more similar to the one they are already using. In parallel, users exhibit a myopic behavior, i.e., they tend to overestimate the goodness of a route if, when using it, they suddenly experience a significant reduction in travel time compared to what they are used to. In the paper it is shown that such route choice behaviour implies that the steady state of the system corresponds to a Bounded Rational User Equilibrium, i.e., a state that does not diverge from the user equilibrium more than a certain value which increases when the relative importance given to the topological similarity grows. The model also assumes that these biases vanish, at least with respect to those routes that are most frequently used by users, after a sufficient amount of time. Under certain conditions, it is then shown that the steady state can eventually collapse into a User Equilibrium. The effectiveness of the proposed model is assessed via simulation results in which two test networks are analyzed in detail to show the evolution of the users’ behaviour in a transport network after a disruption.

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CiteScore
15.20
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