Centrality Measures to Identify Traffic Congestion on Road Networks: A Case Study of Sri Lanka.

dc.contributor.authorJayaweera, I.M.L.N.
dc.contributor.authorPerera, K.K.K.R.
dc.contributor.authorMunasinghe, J.
dc.date.accessioned2017-12-13T04:24:38Z
dc.date.available2017-12-13T04:24:38Z
dc.date.issued2017
dc.description.abstractThis study presents a graph theoretical approach to identify the traffic congestion on a road network. Problem address on a city called Kiribathgoda situated in the western province of Sri Lanka. In the analysis of social networks, centrality measures played a vital role to identify the central nodes in a given network. We look at the applicability of centrality and betweenness measures in order to identify the most important locations which directly affect to the traffic congestion in road networks in Sri Lanka. Using the graph theoretical approach a traffic network for a selected area was constructed and several centrality measures were calculated. According to our simulation results, it was noted that the practically identified locations could be identified from the simulations carried out using the centrality measures.en_US
dc.identifier.citationJayaweera,I.M.L.N., Perera, K.K.K.R.,and Munasinghe, J. (2017). Centrality Measures to Identify Traffic Congestion on Road Networks: A Case Study of Sri Lanka. IOSR Journal of Mathematics (IOSR-JM), Department of Mathematics, Faculty of Science, University of Kelaniya, Sri Lanka.p.13.en_US
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/18523
dc.language.isoenen_US
dc.publisherIOSR Journal of Mathematics (IOSR-JM), Department of Mathematics, Faculty of Science, University of Kelaniya, Sri Lanka.en_US
dc.subjectCentrality Measuresen_US
dc.subjectBetweenness Measuresen_US
dc.subjectRoad Networken_US
dc.subjectGraphen_US
dc.subjectTrafficen_US
dc.titleCentrality Measures to Identify Traffic Congestion on Road Networks: A Case Study of Sri Lanka.en_US
dc.typeArticleen_US

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