Cognitive Hierarchy in Day-to-day Network Flow Dynamics
Minyu Shen, Feng Xiao, Weihua Gu, and Hongbo Ye

TL;DR
This paper introduces a new day-to-day traffic flow model based on Cognitive Hierarchy theory, capturing travelers' strategic reasoning and better matching experimental data than previous models.
Contribution
It extends existing traffic dynamics models with a cognitive hierarchy framework, revealing multiple equilibria and analyzing their local stability.
Findings
The extended models fit experimental data reasonably well.
Multiple equilibria, including classical user equilibrium, are identified.
Local stability analysis provides insights into parameter effects.
Abstract
When making route decisions, travelers may engage in a certain degree of reasoning about what the others will do in the upcoming day, rendering yesterday's shortest routes less attractive. This phenomenon was manifested in a recent virtual experiment that mimicked travelers' repeated daily trip-making process. Unfortunately, prevailing day-to-day traffic dynamical models failed to faithfully reproduce the collected flow evolution data therein. To this end, we propose a day-to-day traffic behavior modeling framework based on the Cognitive Hierarchy theory, in which travelers with different levels of strategic-reasoning capabilities form their own beliefs about lower-step travelers' capabilities when choosing their routes. Two widely-studied day-to-day models, the Network Tatonnement Process dynamic and the Logit dynamic, are extended into the framework and studied as examples.…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Complex Network Analysis Techniques · Mental Health Research Topics
