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TIME-ANTS: An innovative temporal and spatial ant-based vehicular routing mechanism

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dc.contributor.author Doolan, Ronan
dc.contributor.author Muntean, Gabriel-Miro
dc.date.accessioned 2015-03-19T18:22:25Z
dc.date.available 2015-03-19T18:22:25Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/10344/4379
dc.description peer-reviewed en_US
dc.description.abstract Increasing amounts of time is wasted due to traffic congestion in both developed and developing countries. This has severe negative effects, including drivers stress due to increased time pressure, reduced usage efficiency of trucks and other commercial vehicles, and increased gas emissions--responsible for climate change and air pollution affecting population health in densely populated areas. As existing centralized approaches were neither efficient, nor scalable, there is a need for alternative approaches. Social insects provide many solutions for dealing with decentralized problems. For instance ants choose their routes based on pheromones left by previous ants. However, Ant Colony Optimization is not directly applicable to vehicle routing, as routing the vehicles to the same road would cause traffic congestion. Yet, the traffic is broadly similar from work- to work-day. This paper introduces an ant-colony optimization-based algorithm called Time-Ants. Time-Ants considers that an amount of “pheromone” or a traffic rating is assigned to each road at any given time in the day. Using an innovative algorithm the vehicle’s routes are chosen based on these traffic ratings, aggregated in time. After several iterations this results in a global optimum for the traffic system. Bottlenecks are identified and avoided by machine learning. Time-Ants outperforms another leading algorithm by up to 19% in terms of percentage of vehicles to reach the destination within a given time-frame. en_US
dc.language.iso eng en_US
dc.publisher IEEE Computer Society en_US
dc.relation.ispartofseries 2014 IEEE Intelligent Vehicles Symposium (IV);pp. 951-956
dc.relation.uri http://dx.doi.org/10.1109/IVS.2014.6856444
dc.rights “© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. en_US
dc.subject traffic congestion en_US
dc.subject machine learning en_US
dc.subject vehicle routing en_US
dc.subject VANET en_US
dc.title TIME-ANTS: An innovative temporal and spatial ant-based vehicular routing mechanism en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.contributor.sponsor SFI en_US
dc.relation.projectid 10/CE/I1855 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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