Optimization of Traffic Light Controllers Using Genetic Algorithms: A Case Study in the City of Cádiz

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URI: http://hdl.handle.net/10498/34127

DOI: 978-3-031-43461-7_11

URL: https://link.springer.com/chapter/10.1007/978-3-031-43461-7_11

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Author/s
Balderas Díaz, SaraAuthority UCA; Muñoz Ortega, AndrésAuthority UCA; Guerrero Contreras, Gabriel JoséAuthority UCA
Date
2023-09-26
Department
Ingeniería Informática
Source
Balderas-Díaz, S., Muñoz, A., Guerrero-Contreras, G. (2023). Optimization of Traffic Light Controllers Using Genetic Algorithms: A Case Study in the City of Cádiz. In: Novais, P., et al. Ambient Intelligence – Software and Applications – 14th International Symposium on Ambient Intelligence. ISAmI 2023. Lecture Notes in Networks and Systems, vol 770. Springer, Cham.
Abstract
Traffic congestion is a significant problem in many cities, leading to delays, increased fuel consumption, and environmental pollution. In recent years, optimization algorithms have been used to improve traffic control systems and reduce congestion. This paper proposes an optimization algorithm based on genetic algorithms to optimize traffic signal controllers in Cádiz, Spain, using the Simulation of Urban MObility (SUMO) traffic simulator. The proposed optimization algorithm is a promising solution for the optimization of traffic control systems, which can lead to more efficient traffic flow, reduced congestion, and improved environmental conditions.
Subjects
Genetic Algorithms; Traffic Light Controllers; Optimization; SUMO
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional