Abstract
Identifying critical locations in road networks assists in reducing the risks of intermittent services and increases the quality of life . Complex network applications are used in transportation networks to identify critical locations from a topological point of view. However, critical locations change when there are disruptions and people move towards a specific service inside its catchment area. In this chapter, a modified betweenness centrality is used to identify critical locations when moving towards a single service . This index, the origin-destination betweenness centrality , is used to identify important locations in the baseline scenario for a case study from Kathmandu, Nepal . Furthermore, random disruptions with increasing magnitude are simulated to understand a network’s behavior and to identify the changes in those critical locations under extreme conditions. The results demonstrated that the origin-destination betweenness centrality is an effective index. Furthermore, random disruption simulations can assist decision-makers in preparing recovery plans .
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Acknowledgements
This work was funded by a grant to N.Y.A., Y.C., and H.R.H. from the National Research Foundation of Singapore (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) program (FI 370074011) for the Future Resilient Systems project at the Singapore-ETH Centre (SEC) and by an Alexander von Humboldt Foundation Georg Forster Experienced Researcher Fellowship Grant to H.S.D.
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Aydin, N.Y., Casali, Y., Sebnem Duzgun, H., Heinimann, H.R. (2019). Identifying Changes in Critical Locations for Transportation Networks Using Centrality. In: Geertman, S., Zhan, Q., Allan, A., Pettit, C. (eds) Computational Urban Planning and Management for Smart Cities. CUPUM 2019. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-19424-6_22
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