Multiday User Equilibrium with Strategic Commuters

TL;DR

This paper models multiday traffic patterns with strategic commuters using a mean-field Markov game, revealing how user inertia influences network flows and connecting to Wardrop equilibrium.

Contribution

It introduces a novel multiday user equilibrium concept for strategic, connected commuters, extending traditional traffic equilibrium models.

Findings

User inertia causes between-day flow variations.

Multiday equilibrium relates to Wardrop equilibrium.

Model applies to route and departure time choices.

Abstract

In the era of connected and automated mobility, commuters will possess strong computation power, enabling them to strategically make sequential travel choices over a planning horizon. This paper investigates the multiday traffic patterns that arise from such decision-making behavior. In doing so, we frame the commute problem as a mean-field Markov game and introduce a novel concept of multiday user equilibrium to capture the steady state of commuters' interactions. The proposed model is general and can be tailored to various travel choices such as route or departure time. We explore a range of properties of the multiday user equilibrium under mild conditions. The study reveals the fingerprint of user inertia on network flow patterns, causing between-day variations even at a steady state. Furthermore, our analysis establishes critical connections between the multiday user equilibrium and conventional Wardrop equilibrium.