2026-06-01T15:46:50Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/56302026-02-03T11:24:21Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Stolfi, Daniel H.
author
Alba-Torres, Enrique
2013-07-16T11:28:04Z
2013-07-16T11:28:04Z
2013
Proceedings of the Genetic and Evolutionary Computation Conference, 1373-1380
http://hdl.handle.net/10630/5630
This work presents an original approach to regulate traffic by using an on-line system controlled by an EA. Our proposal uses computational spots with WiFi connectivity located at traffic lights (the Red Swarm), which are used to suggest alternative individual routes to vehicles. An evolutionary algorithm is also proposed in order to find a configuration for the Red Swarm spots which reduces the travel time of the vehicles and also prevents traffic jams. We solve real scenarios in the city of Malaga (Spain), thus enriching the OpenStreetMap info by adding traffic lights, sensors, routes and vehicle flows. The result is then imported into the SUMO traffic simulator to be used as a method for calculating the fitness of solutions. Our results are competitive compared to the common solutions from experts in terms of travel and stop time, and also with respect to other similar proposals but with the added value of solving a real, big instance.
eng
Computación evolutiva
Algoritmos genéticos
Red Swarm: Smart Mobility in Cities with EAs
journal article
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URL
https://riuma.uma.es/bitstreams/cfc2cae7-e4f5-4fe7-84f7-e5c51f4c9414/download
File
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rs.pdf
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https://riuma.uma.es/bitstreams/c0c5d3b3-71cb-4a6c-a27b-9e226fd438df/download
File
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rs.pdf.txt