Thèses en ligne de l'université 8 Mai 1945 Guelma

Conception d’un modèle de contrôle adaptatif du trafic

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dc.contributor.author BEN TADJINE, AMEL
dc.date.accessioned 2022-10-16T09:27:56Z
dc.date.available 2022-10-16T09:27:56Z
dc.date.issued 2022
dc.identifier.uri http://dspace.univ-guelma.dz/jspui/handle/123456789/13285
dc.description.abstract Nowadays, transport has become an essential element for the modern societies. So the management of networks has become also important. Among the most used tools for the management of these networks, we find traffic lights. These lights do not adapt to the amount of traffic (fixed time for each traffic light). The evolution of new technologies has made it possible to solve this problem and to make traffic lights smart. The objective of this work is to propose a new dynamic control solution l for intelligent traffic lights using reinforcement learning combined with deep learning. The main advantage of our system is to provide adaptation between traffic lights and smooth traffic flow in different conditions. en_US
dc.language.iso fr en_US
dc.publisher université de guelma en_US
dc.subject Signalisation intelligente, Contrôle de trafic, Apprentissage par renforcement, Apprentissage profond. en_US
dc.title Conception d’un modèle de contrôle adaptatif du trafic en_US
dc.type Working Paper en_US


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