Bilevel Optimization for Traffic Mitigation in Optimal Transport Networks

TL;DR

This paper introduces a bilevel optimization approach based on Optimal Transport theory to improve traffic routing, balancing individual passenger behavior with global network efficiency, and demonstrates potential environmental benefits.

Contribution

It develops a novel bilevel optimization framework that strategically tunes network weights to enhance traffic flow and reduce emissions, validated on synthetic and real-world data.

Findings

Effective routing schemes can lower carbon emissions.

The approach improves both global and local transport efficiency.

Validated on European highway data.

Abstract

Global infrastructure robustness and local transport efficiency are critical requirements for transportation networks. However, since passengers often travel greedily to maximize their own benefit and trigger traffic jams, overall transportation performance can be heavily disrupted. We develop adaptation rules that leverage Optimal Transport theory to effectively route passengers along their shortest paths while also strategically tuning edge weights to optimize traffic. As a result, we enforce both global and local optimality of transport. We prove the efficacy of our approach on synthetic networks and on real data. Our findings on the International European highways suggest that thoughtfully devised routing schemes might help to lower car-produced carbon emissions.