Smart City Gnosys

Smart city article details

Title Combined Optimisation Of Traffic Light Control Parameters And Autonomous Vehicle Routes
ID_Doc 14821
Authors Gallo M.
Year 2024
Published Smart Cities, 7, 3
DOI http://dx.doi.org/10.3390/smartcities7030045
Abstract In the near future, fully autonomous vehicles may revolutionise mobility and contribute to the development of the smart city concept. In this work, we assume that vehicles are not only fully autonomous but also centrally controlled by a single operator, who can also define the traffic light control parameters at intersections. With the aim of optimising the system to achieve a global optimum, the operator can define both the routes of the fleet of vehicles and the traffic light control parameters. This paper proposes a model for the joint optimisation of traffic light control parameters and autonomous vehicle routes to achieve the system optimum. The model, which is solved using a gradient algorithm, is tested on networks of different sizes. The results obtained show the validity of the proposed approach and the advantages of centralised management of vehicles and intersection control parameters. © 2024 by the author.
Author Keywords autonomous vehicles; optimisation; signal settings; smart mobility; traffic lights


Similar Articles


Id Similarity Authors Title Published
58645 View0.883Haddad A.G.; Takiddeen A.; Obeid A.; Sleptchenko A.Traffic Optimization By Simultaneous Control Of Vehicles Speeds And Routes2019 IEEE 6th International Conference on Industrial Engineering and Applications, ICIEA 2019 (2019)
40615 View0.881Chuprov S.; Viksnin I.; Kim I.; Nedosekin G.Optimization Of Autonomous Vehicles Movement In Urban Intersection Management SystemConference of Open Innovation Association, FRUCT, 2019-April (2019)
14984 View0.88Małecki K.; Pietruszka P.Comparative Analysis Of Chosen Adaptive Traffic Control AlgorithmsLecture Notes in Networks and Systems, 21 (2018)
6221 View0.879Akopov A.S.; Zaripov E.A.; Melnikov A.M.Adaptive Control Of Transportation Infrastructure In An Urban Environment Using A Real-Coded Genetic AlgorithmBusiness Informatics, 18, 2 (2024)
57625 View0.868Ait Ouallane A.; Bahnasse A.; Bakali A.; Talea M.Toward A Smart City: Reinforcement Learning For Traffic Light ControlLecture Notes in Networks and Systems, 629 LNNS (2023)
39186 View0.862Cassandras C.G.New Transportation Systems For Smart CitiesHandbook of Research on Social, Economic, and Environmental Sustainability in the Development of Smart Cities (2015)
39185 View0.862Cassandras C.G.New Transportation Systems For Smart CitiesCivil and Environmental Engineering: Concepts, Methodologies, Tools, and Applications, 3 (2016)
58612 View0.858Yuloskov A.; Bahrami M.R.; Mazzara M.; Imbugwa G.B.; Ndukwe I.; Kotorov I.Traffic Light Algorithms In Smart Cities: Simulation And AnalysisLecture Notes in Networks and Systems, 661 LNNS (2023)
11495 View0.857Suresh Kumar S.; Rajesh Babu M.; Vineeth R.; Varun S.; Sahil A.N.; Sharanraj S.Autonomous Traffic Light Control System For Smart CitiesLecture Notes in Networks and Systems, 75 (2019)
60044 View0.856Chuprov S.; Viksnin I.; Kim I.Urban Intersection Management With Connected Infrastructure Objects And Autonomous Vehicles2019 8th IEEE International Conference on Connected Vehicles and Expo, ICCVE 2019 - Proceedings (2019)