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User inequity implications of road network vulnerability

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  • Jenelius, Erik

    (Royal Institute of Technology (KTH), Stockholm, Sweden)

Abstract

An important purpose of the road transport system is to allow people to commute in efficient and reliable ways. For various undesired reasons, however, link capacities are sometimes reduced or links are closed completely. To assess and reduce the risk of such events, a key issue is to identify road links that are particularly important, i.e. roads where disruptions would have particularly severe consequences. This paper presents a method for incorporating user equity considerations into a road link importance measure. As a complement to measuring the total increase in vehicle travel time, we also measure the disparity in the distribution among individual users. These two components are combined to form an equity-weighted importance measure. We study the properties of this measure both analytically and in a full-scale case study of the Swedish road network. A main result is that increasing the weight put on the equity aspect transfers importance from the main roads to smaller local roads. The use of the measure in transport policy and planning is discussed.

Suggested Citation

  • 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.
  • Handle: RePEc:ris:jtralu:0039
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    References listed on IDEAS

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    1. Langmyhr, Tore, 1997. "Managing equity : The case of road pricing," Transport Policy, Elsevier, vol. 4(1), pages 25-39, January.
    2. 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.
    3. Ram Gopalan & Krishna S. Kolluri & Rajan Batta & Mark H. Karwan, 1990. "Modeling Equity of Risk in the Transportation of Hazardous Materials," Operations Research, INFORMS, vol. 38(6), pages 961-973, December.
    4. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    5. Sohn, Jungyul, 2006. "Evaluating the significance of highway network links under the flood damage: An accessibility approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 491-506, July.
    6. Eliasson, Jonas & Mattsson, Lars-Göran, 2006. "Equity effects of congestion pricing: Quantitative methodology and a case study for Stockholm," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 602-620, August.
    7. Katja Berdica & Lars-Göran Mattsson, 2007. "Vulnerability: A Model-Based Case Study of the Road Network in Stockholm," Advances in Spatial Science, in: Alan T. Murray & Tony H. Grubesic (ed.), Critical Infrastructure, chapter 5, pages 81-106, Springer.
    8. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    9. 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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    Cited by:

    1. Khademi, Navid & Babaei, Mohsen & Schmöcker, Jan-Dirk & Fani, Amirhossein, 2018. "Analysis of incident costs in a vulnerable sparse rail network – Description and Iran case study," Research in Transportation Economics, Elsevier, vol. 70(C), pages 9-27.
    2. 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.
    3. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    4. 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.
    5. Jafino, Bramka Arga, 2021. "An equity-based transport network criticality analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 204-221.
    6. Monfared, M.A.S. & Rezazadeh, Masoumeh & Alipour, Zohreh, 2022. "Road networks reliability estimations and optimizations: A Bi-directional bottom-up, top-down approach," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. Chan, Ho-Yin & Chen, Anthony & Li, Guoyuan & Xu, Xiangdong & Lam, William, 2021. "Evaluating the value of new metro lines using route diversity measures: The case of Hong Kong's Mass Transit Railway system," Journal of Transport Geography, Elsevier, vol. 91(C).

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    More about this item

    Keywords

    Transport; Networks; Efficiency; Equity; Vulnerability; Reliability;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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