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Risk Analysis of Safety Service Patrol (SSP) Systems in Virginia

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  • Brett D. Dickey
  • Joost R. Santos

Abstract

The transportation infrastructure is a vital backbone of any regional economy as it supports workforce mobility, tourism, and a host of socioeconomic activities. In this article, we specifically examine the incident management function of the transportation infrastructure. In many metropolitan regions, incident management is handled primarily by safety service patrols (SSPs), which monitor and resolve roadway incidents. In Virginia, SSP allocation across highway networks is based typically on average vehicle speeds and incident volumes. This article implements a probabilistic network model that partitions “business as usual” traffic flow with extreme‐event scenarios. Results of simulated network scenarios reveal that flexible SSP configurations can improve incident resolution times relative to predetermined SSP assignments.

Suggested Citation

  • Brett D. Dickey & Joost R. Santos, 2011. "Risk Analysis of Safety Service Patrol (SSP) Systems in Virginia," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1859-1871, December.
    • Handle: RePEc:wly:riskan:v:31:y:2011:i:12:p:1859-1871
    DOI: 10.1111/j.1539-6924.2011.01631.x
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    1. Grabisch, Michel & Kojadinovic, Ivan & Meyer, Patrick, 2008. "A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package," European Journal of Operational Research, Elsevier, vol. 186(2), pages 766-785, April.
    2. Stanley Kaplan & B. John Garrick, 1981. "On The Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 11-27, March.
    3. Clark, Stephen & Watling, David, 2005. "Modelling network travel time reliability under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 119-140, February.
    4. Lo, Hong K. & Luo, X.W. & Siu, Barbara W.Y., 2006. "Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 792-806, November.
    5. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834.
    6. Dias, Luis C. & Climaco, Joao N., 2000. "Shortest path problems with partial information: Models and algorithms for detecting dominance," European Journal of Operational Research, Elsevier, vol. 121(1), pages 16-31, February.
    7. Siu, Barbara W.Y. & Lo, Hong K., 2008. "Doubly uncertain transportation network: Degradable capacity and stochastic demand," European Journal of Operational Research, Elsevier, vol. 191(1), pages 166-181, November.
    8. Barker, Kash & Santos, Joost R., 2010. "Measuring the efficacy of inventory with a dynamic input-output model," International Journal of Production Economics, Elsevier, vol. 126(1), pages 130-143, July.
    9. Lo, Hong K. & Tung, Yeou-Koung, 2003. "Network with degradable links: capacity analysis and design," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 345-363, May.
    10. M. F. Leung & J. R. Santos & Y. Y. Haimes, 2003. "Risk Modeling, Assessment, and Management of Lahar Flow Threat," Risk Analysis, John Wiley & Sons, vol. 23(6), pages 1323-1335, December.
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