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A Stochastic α-reliable Mean-excess Traffic Equilibrium Model with Probabilistic Travel Times and Perception Errors

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Transportation and Traffic Theory 2009: Golden Jubilee

Abstract

This paper proposes a novel stochastic mean-excess traffic equilibrium model that considers both reliability and unreliability aspects of travel time variability and perception errors within the travelers’ route choice decision processes. In the model, each traveler not only considers a travel time budget for ensuring on-time arrival at a confidence level α, but also accounts for the impact of encountering worst travel times in the (1-α) quantile of the distribution tail. Furthermore, due to the imperfect knowledge of the travel time variability, the travelers’ route choice decisions are based on the perceived travel time distribution rather than the actual travel time distribution. In order to compute the perceived mean-excess travel time, an approximation method based on moment analysis is developed. The proposed model is formulated as a variational inequality (VI) problem, and solved by a route-based solution algorithm with the use of the modified alternating direction method. Numerical examples are also provided to illustrate the application of the proposed model and solution method.

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References

  • Abdel-Aty, M., Kitamura, R. and Jovanis, P. (1995). Exploring route choice behavior using geographical information system-based alternative routes and hypothetical travel time information input. Transportation Research Record, 1493, 74-80.

    Google Scholar 

  • Acerbi, C. and Tasche, D. (2002). On the coherence of expected shortfall. Journal of Banking and Finance, 26(7), 1487-1503.

    Article  Google Scholar 

  • Bernstein, D. and Gabriel, S.A. (1997). Solving the nonadditive traffic equilibrium problem. Network Optimization, 72-102.

    Google Scholar 

  • Brownstone, D., Ghosh, A., Golob, T.F., Kazimi, C. and Amelsfort, D.V. (2003). Drivers' willingness-to-pay to reduce travel time: evidence from the San Diego I-15 congestion pricing project. Transportation Research Part A, 37(4), 373-387.

    Google Scholar 

  • Cambridge Systematics (2003). Providing a Highway System with Reliable Travel Times. NCHRP Report20-58[3], Transportation Research Board, National Research Council, U.S.A.

    Google Scholar 

  • Chen, A. and Ji, Z. (2005). Path finding under uncertainty. Journal of Advanced Transportation, 39(1), 19-37.

    Google Scholar 

  • Chen, A., Lo, H.K. and Yang, H. (2001). A self-adaptive projection and contraction algorithm for the traffic assignment problem with path-specific costs. European Journal of Operational Research, 135, 27-41.

    Article  Google Scholar 

  • Chen, A. and Zhou, Z. (2009). The α-reliable mean-excess traffic equilibrium model with stochastic travel times. Transportation Research Part B, Tentatively Accepted.

    Google Scholar 

  • Clark, S.D. and Watling, D. (2005). Modeling network travel time reliability under stochastic demand.Transportation Research Part B, 39(2), 119-140.

    Article  Google Scholar 

  • Cornish, E.A. and Fisher, R.A. (1937). Moments and cumulants in the specification of distributions. Extrait de la Revue de l'Institute International de Statistique, 4, 1-14.

    Google Scholar 

  • de Palma, A. and Picard, N. (2005). Route choice decision under travel time uncertainty. Transportation Research Part A, 39, 295-324.

    Google Scholar 

  • Dial, R.B. (1971). A probabilistic multipath traffic assignment algorithm which obviates path enumeration. Transportation Research, 5, 83-111.

    Article  Google Scholar 

  • Facchinei, F. and Pang, J.S. (2003). Finite-Dimensional Variational Inequalities and Complementarity Problems. Springer-Verlag, New York.

    Google Scholar 

  • Fisk, C. (1980). Some developments in equilibrium traffic assignment. Transportation Research Part B, 14, 243-255.

    Article  Google Scholar 

  • Fan, Y.Y. and Nie, Y. (2006). Optimal Routing for Maximizing the Travel Time Reliability. Networks and Spatial Economics, 6(3), 333-344.

    Article  Google Scholar 

  • FHWA. (2006). Travel Time Reliability: Making it there on Time, all the Time. FHWA-HOP-06-070, Federal Highway Administration.

    Google Scholar 

  • Gabriel, S.A. and Bernstein, D. (1997). The traffic equilibrium problem with nonadditive path costs. Transportation Science, 31(4), 337-348.

    Article  Google Scholar 

  • Han, D. (2002). A modified alternating direction method for variational inequality problems. Applied Mathematics and Optimization, 45, 63-74.

    Article  Google Scholar 

  • Liu, H., Recker, W. and Chen, A. (2004). Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data. Transportation Research Part A, 38, 435-453.

    Google Scholar 

  • Lo, H.K. and Chen, A. (2000). Traffic equilibrium problem with route-specific costs: formulation and algorithms. Transportation Research Part B, 34, 493-513.

    Article  Google Scholar 

  • Lo, H.K., Luo, X.W. and Siu, B.W.Y. (2006). Degradable transport network: travel time budget of travelers with heterogeneous risk aversion. Transportation Research Part B, 40, 792-806.

    Article  Google Scholar 

  • Lo, H.K. and Tung, Y.K. (2003). Network with degradable links: capacity analysis and design. Transportation Research Part B, 37, 345-363.

    Article  Google Scholar 

  • Mirchandani, P. and Soroush, H. (1987). Generalized traffic equilibrium with probabilistic travel times and perceptions. Transportation Science, 21, 133-152.

    Article  Google Scholar 

  • Noland, R.B. (1999). Information in a two-route network with recurrent and non-recurrent congestion. Behavioral and Network Impacts of Driver Information Systems, 95-114.

    Google Scholar 

  • Noland, R. and Small, K.A. (1995). Travel time uncertainty, departure time choice, and the cost of morning commutes. Transportation Research Record, 1493, 150-158.

    Google Scholar 

  • Noland, R.B., Small, K.A., Koskenoja, P.M. and Chu, X. (1998). Simulating travel reliability. Regional Science & Urban Economics, 28, 535-564.

    Article  Google Scholar 

  • Oppenheim, N. (1995). Urban Travel Demand Modeling. John Wiley & Sons, New York.

    Google Scholar 

  • Shao, H., Lam, W.H.K., Meng, Q. and Tam, M.L. (2006a). Demand-driven traffic assignment problem based on travel time reliability. Transportation Research Record, 1985, 220 - 230.

    Google Scholar 

  • Shao, H., Lam, W.H.K. and Tam, M.L. (2006b). A reliability-based stochastic traffic assignment model for network with multiple user classes under uncertainty in demand. Network and Spatial Economics, 6, 173 - 204.

    Google Scholar 

  • Shao, H., Lam, W.H.K., Tam, M.L. and Yuan, X.M. (2008). Modeling rain effects on risk-taking behaviors of multi-user classes in road network with uncertainty. Journal of Advanced Transportation, 42(3), 265 - 290.

    Article  Google Scholar 

  • Sheffi, Y. (1985). Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods. Prentice-Hall, Incorporated, Englewood Cliffs, N.J.

    Google Scholar 

  • Small, K.A. (1982). The scheduling of consumer activities: work trips. American Economic Review, 72(3), 467-479.

    Google Scholar 

  • Small, K.A., Noland, R., Chu, X. and Lewis, D. (1999). Valuation of Travel-Time Savings and Predictability in Congested Conditions for Highway User-Cost Estimation. NCHRP Report 431, Transportation Research Board, National Research Council, U.S.A.

    Google Scholar 

  • Siu, B. and Lo, H. (2006). Doubly uncertain transport network: degradable link capacity and perception variations in traffic conditions. Transportation Research Record, 1964, 59-69.

    Article  Google Scholar 

  • Siu, B. and Lo, H. (2007). Travel time budget and schedule delay costs under uncertainty. Proceedings of the third international symposium on transportation network reliability (INSTR), The Netherlands.

    Google Scholar 

  • Stoer, J. and Bulirsch, R. (2002). Introduction to numerical analysis (3rd edition), Springer, New York.

    Google Scholar 

  • Uchida, T. and Iida, Y. (1993). Risk assignment: a new traffic assignment model considering the risk travel time variation. Proceedings of the the 12th International Symposium on Transportation and Traffic Theory, 89-105.

    Google Scholar 

  • Wardrop, J. (1952). Some theoretical aspects of road traffic research. Proceedings of the Institute of Civil Engineerings, II(1), 325-378.

    Google Scholar 

  • Watling, D. (2006). User equilibrium traffic network assignment with stochastic travel times and late arrival penalty. European Journal of Operational Research, 175, 1539-1556.

    Article  Google Scholar 

  • van Lint, J.W.C., van Zuylen, H.J. and Tu, H. (2008). Travel time unreliability on freeways: why measures based on variance tell only half the story. Transportation Research Part A, 42(1), 258-277.

    Google Scholar 

  • Zhou, Z., Chen, A. and Han, D. (2007). An extended alternating direction method for variational inequalities with linear equality and inequality constraints. Applied Mathematics and Computation, 184(2), 769-782.

    Article  Google Scholar 

  • Zhou, Z., and Chen, A. (2008a). Comparative analysis of three user equilibrium models under stochastic demand.Journal of Advanced Transportation, 42(3), 239-263.

    Google Scholar 

  • Zhou, Z., and Chen, A. (2008b). The α-reliable mean-excess path finding model in stochastic networks. Submitted.

    Google Scholar 

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Acknowledgments

The work described in this paper was jointly supported by a CAREER grant from the National Science Foundation (CMS-0134161) of the United States.

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Chen, A., Zhou, Z. (2009). A Stochastic α-reliable Mean-excess Traffic Equilibrium Model with Probabilistic Travel Times and Perception Errors. In: Lam, W., Wong, S., Lo, H. (eds) Transportation and Traffic Theory 2009: Golden Jubilee. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0820-9_7

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