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The impact of network density, travel and location patterns on regional road network vulnerability

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  • Erik Jenelius
  • Lars-Göran Mattsson

Abstract

Disruptions in the road transport system can have severe consequences for accessibility and transport costs. These impacts vary depending on in which regions they occur (regional importance), and users may be affected differently depending on where they travel (regional exposure). Some disruptions (caused by, e.g., car crashes, minor landslides and floods) affect only single road links, whereas others (e.g., heavy snowfall, storms and wildfires) disable extended areas of the road network. In this paper we systematically analyze the vulnerability of road networks under both kinds of disruptions. We apply the analysis approach to the Swedish road network using travel demand and network data from the Swedish transport modeling system Sampers. We investigate to what extent regional disparities in vulnerability depend on the network structure and travel and location patterns. For single link failures, we find that the total impacts (measured as travel time increases) depend strongly on the network density and the average traffic load in the region, whereas the average impact per traveler in a region is largely determined by the network density and the average user travel time. For area-covering disruptions, the study shows that the impacts depend strongly on the amount of internal, outbound and inbound travel demand of the affected area itself. As a result, the worst-case impact per traveler in a region is largely determined by the concentration of the population to one central location. Our findings, which should be universal for most road networks of similar scale, reveal that the vulnerability to single link failures and spatially spread events display markedly different regional distributions. Furthermore, these regional disparities stem from fundamental properties of the transport system and the population distribution. Hence, we believe that resource allocation for reducing vulnerability is more an issue of preparedness and mitigation than redundancy-providing infrastructure investments.

Suggested Citation

  • Erik Jenelius & Lars-Göran Mattsson, 2011. "The impact of network density, travel and location patterns on regional road network vulnerability," ERSA conference papers ersa10p448, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa10p448
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    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa10/ERSA2010finalpaper448.pdf
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    References listed on IDEAS

    as
    1. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    2. Zhu, Shanjiang & Levinson, David & Liu, Henry X. & Harder, Kathleen, 2010. "The traffic and behavioral effects of the I-35W Mississippi River bridge collapse," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 771-784, December.
    3. Jenelius, Erik, 2009. "Network structure and travel patterns: explaining the geographical disparities of road network vulnerability," Journal of Transport Geography, Elsevier, vol. 17(3), pages 234-244.
    4. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    5. Jenelius, Erik, 2010. "User inequity implications of road network vulnerability," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 57-73.
    6. Michael A. P. Taylor, 2008. "Critical Transport Infrastructure in Urban Areas: Impacts of Traffic Incidents Assessed Using Accessibility‐Based Network Vulnerability Analysis," Growth and Change, Wiley Blackwell, vol. 39(4), pages 593-616, December.
    7. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
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