Incentive Design for Large Congestion Games: Publicness-Specific Bayes Correlated Wardrop Equilibrium (Extended Abstract)

TL;DR

This paper explores how a planner can strategically inform travelers in congestion games with uncertain network states to influence their route choices and optimize overall traffic flow.

Contribution

It introduces a novel incentive design framework using publicness-specific Bayes correlated Wardrop equilibrium for incomplete-information congestion games.

Findings

Framework for incentivizing travelers under uncertainty

Analysis of information dissemination strategies

Potential improvements in traffic management efficiency

Abstract

The travel costs of the players (travelers) in anonymous congestion games depend on their choices of routes and also on the states of the transportation network such as incidents, weather, and road work. In this extended abstract, we consider an incomplete-information environment in which the realizations of the states are unobserved by the travelers. We study how a planner can incentivize the travelers to behave in her favor by strategically designing what and how the travelers get informed about the realizations of the states.