Please use this identifier to cite or link to this item: https://doi.org/10.1061/(ASCE)0733-947X(2008)134:1(41)
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dc.titleMicroscopic traffic simulation model-based optimization approach for the contraflow lane configuration problem
dc.contributor.authorMeng, Q.
dc.contributor.authorKhoo, H.L.
dc.contributor.authorCheu, R.L.
dc.date.accessioned2014-06-17T08:20:52Z
dc.date.available2014-06-17T08:20:52Z
dc.date.issued2008-01
dc.identifier.citationMeng, Q., Khoo, H.L., Cheu, R.L. (2008-01). Microscopic traffic simulation model-based optimization approach for the contraflow lane configuration problem. Journal of Transportation Engineering 134 (1) : 41-49. ScholarBank@NUS Repository. https://doi.org/10.1061/(ASCE)0733-947X(2008)134:1(41)
dc.identifier.issn0733947X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/65807
dc.description.abstractThis paper addresses the optimal contraflow lane configuration problem arising in the contraflow lane control strategy that has been implemented successfully in practice. The problem is formulated as a bilevel programming model in which the upper level problem is a binary integer programming formulation that aims to minimize the total travel time of a study area, while the lower level problem is a microscopic traffic simulation model that can simulate the dynamic reaction of the drivers resulting from a contraflow lane configuration scheme. A microscopic traffic simulation model is adopted in this study because it is easily handled by traffic engineers. Such an adoption results in inexistence of analytical expression of the objective function in the upper level problem. Accordingly, some conventional analytical solution methods for solving integer programming problems are no longer available for the proposed model. Therefore, this paper develops a variation of genetic algorithm that embeds with the microscopic traffic simulation model as well as a chromosome repairing procedure to find an optimal contraflow lane configuration solution. A case study in Singapore is carried out to evaluate the proposed methodology, in which PARAMICS as the microscopic traffic simulation model is applied. © 2008 ASCE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1061/(ASCE)0733-947X(2008)134:1(41)
dc.sourceScopus
dc.subjectAlgorithms
dc.subjectOptimization
dc.subjectSimulation models
dc.subjectTraffic management
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1061/(ASCE)0733-947X(2008)134:1(41)
dc.description.sourcetitleJournal of Transportation Engineering
dc.description.volume134
dc.description.issue1
dc.description.page41-49
dc.identifier.isiut000251847400006
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