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Bibliographic Details
Main Authors:	Cardoso, Isolda, Venturato, Lucas, Walpen, Jorgelina
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control Machine Learning 90B20, 68T20, 90C33
Online Access:	https://arxiv.org/abs/2508.14804
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Table of Contents:

The traffic assignment problem (TAP) aims to predict how traffic flows distribute themselves across a road network, traditionally requiring computationally expensive iterative simulations to reach a user equilibrium (UE) where no driver can unilaterally reduce their travel time. Recent developments in machine learning (ML), particularly Graph Neural Networks (GNNs) and hybrid approaches, aim to solve this faster while maintaining accuracy