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A Comparative Assessment of Stochastic Capacity Estimation Methods

In: Transportation and Traffic Theory 2009: Golden Jubilee

Author

Listed:
  • Justin Geistefeldt

    (Hessian Road and Traffic Authority)

  • Werner Brilon

    (Ruhr-University Bochum)

Abstract

The stochastic nature of highway capacity has gained increasing attention in recent times. For the empirical estimation of capacity distribution functions based on measured traffic data, two methodologies have received considerable application: The direct estimation of breakdown probabilities for groups of traffic volumes on the one hand and the estimation of capacity distribution functions based on statistical models for censored data on the other hand. The objective of the paper is to compare these methods in terms of estimation accuracy, applicability, and consistency of the results. The theoretical differences of both methods as well as the consequences for application are discussed and analyzed based on empirical traffic data as well as data from macroscopic simulation. The analysis yields that the capacity estimation based on models for censored data performs better than the direct breakdown probability estimation technique, particularly concerning the consistency of the estimated capacity distribution functions.

Suggested Citation

  • Justin Geistefeldt & Werner Brilon, 2009. "A Comparative Assessment of Stochastic Capacity Estimation Methods," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 583-602, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4419-0820-9_29
    DOI: 10.1007/978-1-4419-0820-9_29
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    Citations

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    Cited by:

    1. Shiomi, Yasuhiro & Yoshii, Toshio & Kitamura, Ryuichi, 2011. "Platoon-based traffic flow model for estimating breakdown probability at single-lane expressway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1314-1330.
    2. Sumalee, A. & Zhong, R.X. & Pan, T.L. & Szeto, W.Y., 2011. "Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 507-533, March.
    3. Andrea Pompigna & Raffaele Mauro, 2022. "A Statistical Simulation Model for the Analysis of the Traffic Flow Reliability and the Probabilistic Assessment of the Circulation Quality on a Freeway Segment," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
    4. Xiqun (Michael) Chen & Zhiheng Li & Li Li & Qixin Shi, 2014. "A Traffic Breakdown Model Based on Queueing Theory," Networks and Spatial Economics, Springer, vol. 14(3), pages 485-504, December.

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