Please use this identifier to cite or link to this item: https://doi.org/10.1109/TITS.2010.2050688
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dc.titleDistributed geometric fuzzy multiagent urban traffic signal control
dc.contributor.authorGokulan, B.P.
dc.contributor.authorSrinivasan, D.
dc.date.accessioned2014-06-17T02:45:52Z
dc.date.available2014-06-17T02:45:52Z
dc.date.issued2010-09
dc.identifier.citationGokulan, B.P., Srinivasan, D. (2010-09). Distributed geometric fuzzy multiagent urban traffic signal control. IEEE Transactions on Intelligent Transportation Systems 11 (3) : 714-727. ScholarBank@NUS Repository. https://doi.org/10.1109/TITS.2010.2050688
dc.identifier.issn15249050
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/55678
dc.description.abstractRapid urbanization and the growing demand for faster transportation has led to heavy congestion in road traffic networks, necessitating the need for traffic-responsive intelligent signal control systems. The developed signal control system must be capable of determining the green time that minimizes the network-wide travel time delay based on limited information of the environment. This paper adopts a distributed multiagent-based approach to develop a traffic-responsive signal control system, i.e., the geometric fuzzy multiagent system (GFMAS), which is based on a geometric type-2 fuzzy inference system. GFMAS is capable of handling the various levels of uncertainty found in the inputs and rule base of the traffic signal controller. Simulation models of the agents designed in PARAMICS were tested on virtual road network replicating a section of the central business district in Singapore. A comprehensive analysis and comparison was performed against the existing traffic-control algorithms green link determining (GLIDE) and hierarchical multiagent system (HMS). The proposed GFMAS signal control outperformed both the benchmarks when tested for typical traffic-flow scenarios. Further tests show the superior performance of the proposed GFMAS in handling unplanned and planned incidents and obstructions. The promising results demonstrate the efficiency of the proposed multiagent architecture and scope for future development. © 2006 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TITS.2010.2050688
dc.sourceScopus
dc.subjectGeometric type-2 fuzzy set
dc.subjectmultiagent system
dc.subjectPARAMICS
dc.subjecturban traffic signal control
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TITS.2010.2050688
dc.description.sourcetitleIEEE Transactions on Intelligent Transportation Systems
dc.description.volume11
dc.description.issue3
dc.description.page714-727
dc.identifier.isiut000283233800019
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