In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with the network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of transportation factors. This paper proposes new centrality measures that incorporate travel time delay and commuter flow volume. We apply the proposed measures on the Singapore’s subway network involving 89 stations and about 2 million commuter trips per day, and compare them with traditional topology based centrality measures. Several interesting insights about the network are derived from the new measures. We further develop a visual analytics tool to explore the different centrality measures and their changes over time.
Network centrality Commuter flow centrality Delay flow centrality Visual analytics Transportation network
Computer and Systems Architecture | OS and Networks | Systems Architecture
Data Management and Analytics
Applications of Social Media and Social Network Analysis
P. Kazienko and N. Chawla
Springer International Publishing
CHENG, Yew-Yih; LEE KA WEI, ROY; Ee-peng LIM; and ZHU, Feida.
Measuring centralities for transportation networks beyond structures. (2015). Applications of Social Media and Social Network Analysis. 23-39. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3640
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