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  1. Pubblicazioni

Traffic Flow Modelling When Autonomous Vehicles Coexist with Human Driven Vehicles: Perspectives and Challenges

Contributo in Atti di convegno
Data di Pubblicazione:
2022
Citazione:
Traffic Flow Modelling When Autonomous Vehicles Coexist with Human Driven Vehicles: Perspectives and Challenges / Cabri, G.; Crisci, S.; Montangero, M.. - 1026:(2022), pp. 169-177. ( 14th International Symposium on Intelligent Distributed Computing, IDC 2021 Online 2021) [10.1007/978-3-030-96627-0_16].
Abstract:
The problem of mathematically modeling traffic flows has been tackled, with different approaches, since the first decades of the last century. The classic framework that accounts only for human-driven cars is bound to change due to the rise of autonomous driving technologies, which will deeply transform mobility, as well as general driving rules and infrastructures. It is therefore urgent to design novel approaches for modeling the transition phase, where autonomous vehicles and human-driven vehicles will have to coexist, and to devise appropriate solutions for their coordination. In this paper, we provide a brief overview of the most recent studies on the transition scenario, and outline the main challenges and perspectives that are likely to appear in the near future for this case.
Tipologia CRIS:
Relazione in Atti di Convegno
Elenco autori:
Cabri, G.; Crisci, S.; Montangero, M.
Autori di Ateneo:
CABRI Giacomo
MONTANGERO Manuela
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1278357
Titolo del libro:
Studies in Computational Intelligence
Pubblicato in:
STUDIES IN COMPUTATIONAL INTELLIGENCE
Journal
STUDIES IN COMPUTATIONAL INTELLIGENCE
Series
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URL

https://link.springer.com/chapter/10.1007/978-3-030-96627-0_16
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