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dc.contributor.authorWitheridge, S.en
dc.contributor.authorPassow, Benjamin N.en
dc.contributor.authorShell, Jethroen
dc.date.accessioned2017-03-17T11:21:10Z
dc.date.available2017-03-17T11:21:10Z
dc.date.issued2014-07-06
dc.identifier.citationWitheridge, S., Passow, B.N. and Shell, J., (2014). Logan's run: Lane optimisation using genetic algorithms based on nsga-ii. In Neural Networks (IJCNN), 2014 International Joint Conference on (pp. 63-68). IEEE.en
dc.identifier.urihttp://hdl.handle.net/2086/13707
dc.description.abstractWhilst bus lanes are an important tool to ensure bus time reliability their presence can be detrimental to urban traffic. In this paper a Non-dominated Sorting Genetic Algorithm (NSGA-II) has been adopted to study the effect of bus lanes on urban traffic in terms of location and time of operation. Due to the complex nature of this problem traditional search would not be feasible. An artificial arterial route has been modelled from real data to evaluate candidate solutions. The results confirm this methodology for the purpose of studying and identifying bus lane locations and times of operation. Additionally it is shown that bus lanes can exist on an arterial link without exclusively occupying a continuous lane for large periods of time. Furthermore results indicate a use for this methodology over a larger scale and potential near real-time operation.en
dc.publisherIEEEen
dc.subjectGenetic Algorithmen
dc.subjectIntelligent Mobilityen
dc.subjectVehiclesen
dc.subjectOptimisationen
dc.titleLogan's run: Lane optimisation using genetic algorithms based on nsga-iien
dc.typeConferenceen
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceN/Aen
dc.date.acceptance2014-7-6en


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