A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists. - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Pré-Publication, Document De Travail (Preprint/Prepublication) Année : 2024

A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists.

Nicolas Chiabaut

Résumé

Cyclists prefer to use infrastructure that separates them from motorized traffic. Using a traffic light to segregate car and bike flows, with the addition of bike-specific green phases, is a lightweight and cheap solution that can be deployed dynamically to assess the opportunity of a heavier infrastructure such as a separate bike lane. To compensate for the increased waiting time induced by these new phases, we introduce in this paper a deep reinforcement learning solution that adapts the green phase cycle of a traffic light to the traffic. Vehicle counter data are used to compare the DRL approach with the actuated traffic light control algorithm over whole days. Results show that DRL achieves better minimization of vehicle waiting time at almost all hours. Our DRL approach is also robust to moderate changes in bike traffic. The code of this paper is available at https://github.com/LucasMagnana/A-DRL-solution-to-help-reduce-the-cost-in-waiting-time-of-securing-a-traffic-light-for-cyclists.
Fichier principal
Vignette du fichier
main.pdf (576.49 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04300866 , version 1 (22-11-2023)
hal-04300866 , version 2 (05-04-2024)

Licence

Paternité

Identifiants

Citer

Lucas Magnana, Hervé Rivano, Nicolas Chiabaut. A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists.. 2024. ⟨hal-04300866v2⟩
41 Consultations
14 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More