Cognitive Hierarchy in Day-to-day Network Flow Dynamics

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. Calibration of the virtual experiment is performed using the extended Network Tatonnement Process dynamic, which fits the experimental data reasonably well. We show that the two extended dynamics have multiple equilibria, one of which is the classical user equilibrium. While analyzing global stability is intractable due to the presence of multiple equilibria, local stabilities near equilibria are developed analytically and verified by numerical experiments. General insights on how key parameters affect the stability of user equilibria are unveiled.