Document - One-shot traffic assignment with forward-looking penalization

2023

Conference article Open Access

One-shot traffic assignment with forward-looking penalization

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 systems and consists in efficiently assigning routes to a collection of trips. Existing TA algorithms often do not adequately consider realtime traffic conditions, resulting in inefficient route assignments. This paper introduces Metis, a coordinated, one-shot TA algorithm that combines alternative routing with edge penalization and informed route scoring. We conduct experiments in several cities to evaluate the performance of Metis against state-of-the-art oneshot methods. Compared to the best baseline, Metis significantly reduces CO2 emissions by 18% in Milan, 28% in Florence, and 46% in Rome, improving trip distribution considerably while still having low computational time. Our study proposes Metis as a promising solution for optimizing TA and urban transportation systems.

Source: SIGSPATIAL '23 - 31st ACM International Conference on Advances in Geographic Information Systems, Hamburg, Germany, 13-16/11/2023

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@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},
	booktitle = {SIGSPATIAL '23 - 31st ACM International Conference on Advances in Geographic Information Systems, Hamburg, Germany, 13-16/11/2023},
	year = {2023}
}