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Total Travel Cost in Stochastic Assignment Models

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Abstract

Deterministic assignment models are sometimes used to approximate properties of more complex stochastic models. One property that is of particular interest from a system optimization viewpoint is total travel cost. This paper looks at the approximation of mean total travel cost. It is shown that deterministic models will underestimate this quantity in many common situations. Furthermore, discrepancies between total travel cost under the different modelling frameworks can lead to situations in which network modifications which are detrimental according to a stochastic model appear beneficial when using the natural deterministic approximation. We conclude that estimation of mean travel cost in stochastic assignment is often best done using simulation. Some suggestions are made regarding the implementation of traffic assignment simulation.

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References

  • Brooks, S. (1998a).”MCMCConvergence Diagnosis via Multivariate Bounds on Log-Convcave Densities.” Annals of Statistics 26, 398–533.

    Google Scholar 

  • Brooks, S. (1998b). “Quantitative Convergence Assessment for MCMC via CUSUMS.” Statistics and Computing 8, 267–274.

    Google Scholar 

  • Bureau of Public Roads. (1964). “Traffic Assignment Manual.” US Department of Commerce: Washington, DC.

    Google Scholar 

  • Cantarella, G. and E. Cascetta. (1998). “Stochastic Assignment to Transportation Networks: Models and Algorithms.” In P. Marcotte and S. Nguyen (eds.), Equilibrium and Advanced Transportation Modelling. Boston, MA: Kluwer Academic Press, pp. 87–107.

    Google Scholar 

  • Cascetta, E. (1989). “A Stochastic Process Approach to the Analysis of Temporal Dynamics in Transportation Networks.” Transportation Research 23B, 1–17.

    Google Scholar 

  • Cascetta, E. and G. Cantarella. (1991). “A Day-to-Day and Within-Day Dynamic Assignment Model.” Transportation Research 25A, 277–292.

    Google Scholar 

  • Daganzo, C. and Y. Sheffi. (1977). “On Stochastic Models of Traffic Assignment.” Transportation Science 11, 253–274.

    Google Scholar 

  • Davis, G. and N. Nihan. (1993). “Large Population Approximations of a General Stochastic Traffic Assignment Model.” Operations Research 41, 169–178.

    Google Scholar 

  • Dial, R. (1971). “A Probabilistic Multipath Traffic Assignment Model which Obviates Path Enumeration.” Transportation Research 5, 83–111.

    Google Scholar 

  • Gamerman, D. (1997). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. Chapman & Hall, London.

    Google Scholar 

  • Gao, S. and I. Chabini. (2002). “Policy Based Stochastic Dynamic Traffic Assignment Models and Algorithms.” In R. Cheu, D. Srinivason, and D.-H. Lee (eds.), Proceedings of the 5th IEEE International Conference on Intelligent Transportation Systems. IEEE, pp. 445–453.

  • Ghali, M. and M. Smith. (1993). “Traffic Assignment, Traffic Control and Road Pricing.” In C. Daganzo (ed.), Transportation and Traffic Theory: Proceedings of the 12th International Symposium on the Theory of Traffic Flow and Transportation. Amsterdam: Elsevier, pp. 147–169.

    Google Scholar 

  • Han, S. (2003). “Dynamic Traffic Modelling and Dynamic Stochastic User Equilibrium Assignment for General Road Networks.” Transportation Research 37B: 225–249.

    Google Scholar 

  • Hazelton, M. (1998). “Some Remarks on Stochastic User Equilibrium.” Transportation Research 32B, 101–108.

    Google Scholar 

  • Hazelton, M., S. Lee, and J. Polak. (1996). “Stationary States in Stochastic Process Models of Traffic Assignment: AMarkov Chain Mote Carlo Approach.” In J.-P. Baptiste (ed.), Proceedings of the 13th International Symposium on Transportation and Traffic Theory, London: Pergamon Press, pp. 341–357.

    Google Scholar 

  • Hazelton, M. and D. Waltling. (2003). “Computation of Equilibrium Distributions of Markov Traffic Assignment Models.” Transportation Science, to appear.

  • Ran, B. and D. Boyce. (1996). Modelling Dynamic Transportation Networks: An Intelligent Transportation System Oriented Approach. Berlin: Springer.

    Google Scholar 

  • Sheffi, Y. and W. Powell. (1981). “A Comparison of Stochastic and Deterministic Traffic Assignment Over Congested Networks.” Transportation Research 15B, 53–64.

    Google Scholar 

  • Smith, M. (1979). “The Marginal Cost Taxation of a Transportation Network.” Transportation Research 13B, 237–242.

    Google Scholar 

  • Walters, A. (1961). “The Theory and Measurement of Private and Social Cost of Highway Congestion.” Econometrica 29, 676–699.

    Google Scholar 

  • Wardrop, J. (1952). “Some Theoretical Aspects of Road Traffic Research.” Proceedings of the Institute of Civil Engineering, Part II 1, 325–378.

    Google Scholar 

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Hazelton, M.L. Total Travel Cost in Stochastic Assignment Models. Networks and Spatial Economics 3, 457–466 (2003). https://doi.org/10.1023/A:1027362005154

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  • DOI: https://doi.org/10.1023/A:1027362005154

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