Cornacchia G, Nanni M, Pappalardo L
Traffic assignment Alternative routing Route planning Path diversification CO2 emissions Urban sustainability
Traffic assignment (TA) is crucial in optimizing transportation systemsand consists in efficiently assigning routes to a collection oftrips. Existing TA algorithms often do not adequately consider realtimetraffic conditions, resulting in inefficient route assignments.This paper introduces Metis, a coordinated, one-shot TA algorithmthat combines alternative routing with edge penalization and informedroute scoring. We conduct experiments in several cities toevaluate the performance of Metis against state-of-the-art oneshotmethods. Compared to the best baseline, Metis significantlyreduces CO2 emissions by 18% in Milan, 28% in Florence, and 46%in Rome, improving trip distribution considerably while still havinglow computational time. Our study proposes Metis as a promisingsolution for optimizing TA and urban transportation systems.
@inproceedings{oai:it.cnr:prodotti:492091,
title = {One-shot traffic assignment with forward-looking penalization},
author = {Cornacchia G and Nanni M and Pappalardo L},
doi = {10.1145/3589132.3625637},
year = {2023}
}HumanE-AI-Net
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