Bilevel Optimization for Traffic Mitigation in Optimal Transport Networks

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 reveal that our method results in an effective strategy to lower car-produced carbon emissions.

Publication
Submitted
Alessandro Lonardi
Alessandro Lonardi
PhD student

The main focus of my current research is studying routing problems combining approaches stemming from optimal transport and belief propagation. In particular, I am interested in understanding how different route selection mechanisms affect traffic and total path length of networks. The applications of my work span from urban to biological networks. Previously I was a Master’s Student in Mathematical Engineering at UniPd (Padua, Italy), where I also obtained my Bachelor’s degree in Physics.

Caterina De Bacco
Caterina De Bacco
CyberValley Research Group Leader

My research focuses on understanding, optimizing and predicting relations between the microscopic and macroscopic properties of complex large-scale interacting systems.

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