Controlling traffic jams on urban roads modeled in Coloured Petri net using Genetic Algorithm

Luís Filipe dos Santos Gomes; DEE Group Author

doi:10.1109/IECON.2012.6389412

Controlling traffic jams on urban roads modeled in Coloured Petri net using Genetic Algorithm

Luís Filipe dos Santos Gomes, DEE Group Author

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

This paper presents an application to traffic lights control in congested urban traffic, in real time, taking as input the position and route of the vehicles in the involved areas. This data is obtained from the communication between vehicles and infrastructure (V2I). Due to the great complexity of the possible combination of traffic lights and the short time to get a response, Genetic Algorithm was used to optimize this control. According to test results, the application can reduce the number of vehicles in congested areas, even with the entry of vehicles that previously were not being considered in these roads, such as parked vehicles.

Original language	Unknown
Title of host publication	IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Pages	3043 - 3048
ISBN (Electronic)	978-1-4673-2420-5
DOIs	https://doi.org/10.1109/IECON.2012.6389412
Publication status	Published - 1 Jan 2012
Event	IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society - Duration: 1 Jan 2012 → …

Conference

Conference	IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Period	1/01/12 → …

Access to Document

10.1109/IECON.2012.6389412

Cite this

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title = "Controlling traffic jams on urban roads modeled in Coloured Petri net using Genetic Algorithm",

abstract = "This paper presents an application to traffic lights control in congested urban traffic, in real time, taking as input the position and route of the vehicles in the involved areas. This data is obtained from the communication between vehicles and infrastructure (V2I). Due to the great complexity of the possible combination of traffic lights and the short time to get a response, Genetic Algorithm was used to optimize this control. According to test results, the application can reduce the number of vehicles in congested areas, even with the entry of vehicles that previously were not being considered in these roads, such as parked vehicles.",

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year = "2012",

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N2 - This paper presents an application to traffic lights control in congested urban traffic, in real time, taking as input the position and route of the vehicles in the involved areas. This data is obtained from the communication between vehicles and infrastructure (V2I). Due to the great complexity of the possible combination of traffic lights and the short time to get a response, Genetic Algorithm was used to optimize this control. According to test results, the application can reduce the number of vehicles in congested areas, even with the entry of vehicles that previously were not being considered in these roads, such as parked vehicles.

AB - This paper presents an application to traffic lights control in congested urban traffic, in real time, taking as input the position and route of the vehicles in the involved areas. This data is obtained from the communication between vehicles and infrastructure (V2I). Due to the great complexity of the possible combination of traffic lights and the short time to get a response, Genetic Algorithm was used to optimize this control. According to test results, the application can reduce the number of vehicles in congested areas, even with the entry of vehicles that previously were not being considered in these roads, such as parked vehicles.

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