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Confidence interval estimation for path flow estimator

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  • Chootinan, Piya
  • Chen, Anthony
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    Abstract

    The uncertainty of an origin–destination (O–D) trip table estimate is affected by two factors: (i) the multiplicity of solutions due to the underspecified nature of the problem, and (ii) the errors of traffic counts. In this paper, a confidence interval estimation procedure for path flow estimator (PFE) is developed for assessing the quality of O–D trip tables estimated from traffic counts. The confidence interval estimation consists of two parts: (i) a generalized demand scale (GDS) measure for quantifying the intrinsic underspecified nature of the O–D estimation problem at various spatial levels, and (ii) an error bound to quantify the contribution of input errors (traffic counts) to the estimation results. Numerical results using PFE as the O–D estimator show that the proposed confidence interval estimation procedure is able to separate the two sources of uncertainty in constructing the confidence intervals at various spatial levels. Simulation results also confirm that the proposed quality measure indeed contain the true estimates within the defined confidence intervals.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 45 (2011)
    Issue (Month): 10 ()
    Pages: 1680-1698

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    Handle: RePEc:eee:transb:v:45:y:2011:i:10:p:1680-1698

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    Related research

    Keywords: Origin–destination estimation; Path flow estimator; Stochastic user equilibrium; Sensitivity analysis; Confidence interval;

    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Yang, Chao & Chen, Anthony, 2009. "Sensitivity analysis of the combined travel demand model with applications," European Journal of Operational Research, Elsevier, vol. 198(3), pages 909-921, November.
    2. Sherali, Hanif D. & Sivanandan, R. & Hobeika, Antoine G., 1994. "A linear programming approach for synthesizing origin-destination trip tables from link traffic volumes," Transportation Research Part B: Methodological, Elsevier, vol. 28(3), pages 213-233, June.
    3. Yang, Hai & Zhou, Jing, 1998. "Optimal traffic counting locations for origin-destination matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 109-126, February.
    4. Yang, Hai & Iida, Yasunori & Sasaki, Tsuna, 1991. "An analysis of the reliability of an origin-destination trip matrix estimated from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 25(5), pages 351-363, October.
    5. Fisk, Caroline, 1980. "Some developments in equilibrium traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 14(3), pages 243-255, September.
    6. Bierlaire, Michel, 2002. "The total demand scale: a new measure of quality for static and dynamic origin-destination trip tables," Transportation Research Part B: Methodological, Elsevier, vol. 36(9), pages 837-850, November.
    7. Chen, Anthony & Chootinan, Piya & Recker, Will, 2009. "Norm approximation method for handling traffic count inconsistencies in path flow estimator," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 852-872, September.
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    Cited by:
    1. Simonelli, Fulvio & Marzano, Vittorio & Papola, Andrea & Vitiello, Iolanda, 2012. "A network sensor location procedure accounting for o–d matrix estimate variability," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1624-1638.

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