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On Decision Principles for Routing Strategies Under Various Types of Risks

  • Jan-Dirk Schmöcker
Conference paper
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Abstract

Individual travellers as well as freight operators face several sources of risk and uncertainty while choosing their path. This chapter looks at the case when the decision maker is uncertain about how many incidents could disrupt the trip and compares different levels of information regarding the incident likelihood on each link. The first part of the paper looks at the route choice as a game against nature in which route choice and incident probability are independent. The second part of the paper considers cases where incident probability depends on the link use. The solution to a game against an intelligent entity (worst case, no information) is compared with the case when the information about incident likelihood is available. A simple solution algorithm is proposed to find the optimal routing strategy when incident probability is a function of link use probability, and the results are illustrated on a small network. The results show that using multiple routes reduces the potential exposure to loss not only when the worst case scenario is assumed, but also can bring potential benefits when information about incident likelihood is available.

Keywords

Path selection Risks game theory incident probability information 

References

  1. 1.
    Bell, M.G.H., 2000. A game theory approach to measuring the performance reliability of transport networks, Transportation Research B, 34, pp. 533–545.CrossRefGoogle Scholar
  2. 2.
    Bell, M.G.H., 2007. Mixed routing strategies for hazardous materials: Decision-making under complete uncertainty. International Journal of Sustainable Transport, 1(2), pp. 133–142.CrossRefGoogle Scholar
  3. 3.
    Wald, A., 1950. Statistical Decision Functions. Wiley, New York.Google Scholar
  4. 4.
    Berdica, K., 2002. An introduction to road vulnerability: what has been done, is done and should be done. Transport Policy 9, pp. 117–127.CrossRefGoogle Scholar
  5. 5.
    D’Este, G.M. and Taylor, M.A.P., 2003. Network vulnerability: an approach to reliability analysis at the level of national strategic transport networks. In Iida, Y. and Bell, M.G.H. (eds.) The Network Reliability of Transport. Elsevier, Oxford, pp. 23–44.CrossRefGoogle Scholar
  6. 6.
    Taylor, M.A.P. and D’Este, G.M., 2007. Transport network vulnerability: A method for diagnosis of critical locations in transport infrastructure systems. In Murray, A.T. and Grubesic, T.H. (eds.) Critical Infrastructure: Reliability and Vulnerability. Springer-Verlag, New York, pp. 9–30.CrossRefGoogle Scholar
  7. 7.
    Savage, L.J., 1954. The Foundations of Statistics, Wiley, New York.Google Scholar
  8. 8.
    Straffin, P.D., 1993. Game Theory and Strategy. The Mathematical Association of America. New Mathematical Library, pp. 56–61.Google Scholar
  9. 9.
    Szeto, W.Y., O’Brien, L. and O’Mahony, M., 2007. Generalisation of the risk-averse traffic assignment, Proceedings of the 17th International Symposium on Transportation and Traffic Theory (ISTTT), Elsevier: Oxford, 127–155.Google Scholar
  10. 10.
    Bell, M.G.H., 2009. Hyperstar: A multi-path Astar algorithm for risk averse vehicle navigation. Transportation Research B, 43, 97–107.CrossRefGoogle Scholar
  11. 11.
    Schmöcker, J-D., Bell, M.G.H., Kurauchi, F. and Shimamoto, H., 2009. A game theoretic approach to the determination of hyperpaths in transportation networks. Accepted for Selected Proceedings of the 18 th International Symposium on Transportation and Traffic Theory (ISTTT), Hong Kong, July 2009.Google Scholar
  12. 12.
    Batta, R. and Chiu, S.S., 1988. Optimal obnoxious paths on a network – transportation of hazardous materials. Operations Research 36(1), pp. 84–92.CrossRefGoogle Scholar
  13. 13.
    Erkut, E. and Ingolfsson, A., 2000. Catastophe avoidance models for hazardous materials route planning. Transportation Science 34(2), pp. 165–179.CrossRefGoogle Scholar
  14. 14.
    Glickman, T.S., Erkut, E. and Zschocke, M.S., 2007. The cost and risk impacts of re-routing railroad shipments of hazardous materials. Accident Analysis and Prevention 39, pp. 1015–1025.CrossRefGoogle Scholar
  15. 15.
    Akgün, V., Erkut, E. and Batta, R., 2000. On finding dissimilar paths. European Journal of Operational Research, 121, 232–246.CrossRefGoogle Scholar
  16. 16.
    Kurauchi, F., Uno, N., Sumalee, A. and Seto, Y., 2009. Network Evaluation Based On Connectivity Reliability. Accepted for Selected Proceedings of the 18 th International Symposium on Transportation and Traffic Theory (ISTTT), Hong Kong, July 2009.Google Scholar
  17. 17.
    Frank, W. C., Thill, J.-C. and Batta, R., 2000. A Decision Support System for hazardous material truck routing. Transportation Research Part C 8, pp. 337–359.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringTokyo Institute of TechnologyTokyoJapan

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