One of the main issues facing today’s urban environments is traffic congestion, which is exacerbated by exponential population growth and the ensuing rise in vehicle traffic. This problem not only prolongs commutes but also has substantial impacts on environmental sustainability, public health, and total urban responsibility. To solve this problem, our idea proposes developing and putting into place an efficient traffic management system, the integration of PTV Vissim for dataset generation and the utilization of machine learning algorithms, combined with Dijkstra’s algorithm for route optimization, constitute comprehensive solution within our traffic congestion management system. By leveraging these advanced technologies, our system aims not only to alleviate current traffic congestion challenges but also to contribute to the creation of more sustainable and efficient urban transportation systems.
Traffic Congestion Management
Lect. Notes in Networks, Syst.
International Conference on ICT for Sustainable Development ; 2024 ; Goa, India August 08, 2024 - August 09, 2024
03.05.2025
7 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
PTV Vissim’s , Random forest algorithm , <italic>k</italic>-Nearest neighbors classifier , Gaussian , Naive Bayes , Support vector machines , Dijkstra’s algorithm Engineering , Computational Intelligence , Computer Systems Organization and Communication Networks , Cyber-physical systems, IoT , Professional Computing
Wiley | 2008
|Europäisches Patentamt | 2022
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