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A probabilistic stationary speed–density relation based on Newell’s simplified car-following model

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  • Jabari, Saif Eddin
  • Zheng, Jianfeng
  • Liu, Henry X.

Abstract

Probabilistic models describing macroscopic traffic flow have proven useful both in practice and in theory. In theoretical investigations of wide-scatter in flow–density data, the statistical features of flow density relations have played a central role. In real-time estimation and traffic forecasting applications, probabilistic extensions of macroscopic relations are widely used. However, how to obtain such relations, in a manner that results in physically reasonable behavior has not been addressed. This paper presents the derivation of probabilistic macroscopic traffic flow relations from Newell’s simplified car-following model. The probabilistic nature of the model allows for investigating the impact of driver heterogeneity on macroscopic relations of traffic flow. The physical features of the model are verified analytically and shown to produce behavior which is consistent with well-established traffic flow principles. An empirical investigation is carried out using trajectory data from the New Generation SIMulation (NGSIM) program and the model’s ability to reproduce real-world traffic data is validated.

Suggested Citation

  • Jabari, Saif Eddin & Zheng, Jianfeng & Liu, Henry X., 2014. "A probabilistic stationary speed–density relation based on Newell’s simplified car-following model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 205-223.
    • Handle: RePEc:eee:transb:v:68:y:2014:i:c:p:205-223
    DOI: 10.1016/j.trb.2014.06.006
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    1. Anonymous, 1963. "Organization for Economic Cooperation and Development," International Organization, Cambridge University Press, vol. 17(1), pages 300-302, January.
    2. Jabari, Saif Eddin & Liu, Henry X., 2013. "A stochastic model of traffic flow: Gaussian approximation and estimation," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 15-41.
    3. Anonymous, 1965. "Organization for Economic Cooperation and Development," International Organization, Cambridge University Press, vol. 19(1), pages 150-153, January.
    4. Ahn, Soyoung & Cassidy, Michael J. & Laval, Jorge, 2004. "Verification of a simplified car-following theory," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 431-440, June.
    5. Boel, René & Mihaylova, Lyudmila, 2006. "A compositional stochastic model for real time freeway traffic simulation," Transportation Research Part B: Methodological, Elsevier, vol. 40(4), pages 319-334, May.
    6. Zhang, H.M. & Kim, T., 2005. "A car-following theory for multiphase vehicular traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 39(5), pages 385-399, June.
    7. Paul I. Richards, 1956. "Shock Waves on the Highway," Operations Research, INFORMS, vol. 4(1), pages 42-51, February.
    8. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    9. Daganzo, Carlos F., 2002. "A behavioral theory of multi-lane traffic flow. Part II: Merges and the onset of congestion," Transportation Research Part B: Methodological, Elsevier, vol. 36(2), pages 159-169, February.
    10. Harold Greenberg, 1959. "An Analysis of Traffic Flow," Operations Research, INFORMS, vol. 7(1), pages 79-85, February.
    11. Stewart, T. & Strijbosch, L.W.G. & Moors, J.J.A. & van Batenburg, P., 2007. "A Simple Approximation to the Convolution of Gamma Distributions (Revision of DP 2006-27)," Discussion Paper 2007-70, Tilburg University, Center for Economic Research.
    12. David Branston, 1976. "Models of Single Lane Time Headway Distributions," Transportation Science, INFORMS, vol. 10(2), pages 125-148, May.
    13. Osorio, Carolina & Flötteröd, Gunnar & Bierlaire, Michel, 2011. "Dynamic network loading: A stochastic differentiable model that derives link state distributions," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1410-1423.
    14. Daganzo, Carlos F., 2002. "A behavioral theory of multi-lane traffic flow. Part I: Long homogeneous freeway sections," Transportation Research Part B: Methodological, Elsevier, vol. 36(2), pages 131-158, February.
    15. Leslie C. Edie, 1961. "Car-Following and Steady-State Theory for Noncongested Traffic," Operations Research, INFORMS, vol. 9(1), pages 66-76, February.
    16. Kim, T. & Zhang, H.M., 2008. "A stochastic wave propagation model," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 619-634, August.
    17. Kerner, Boris S., 2004. "Three-phase traffic theory and highway capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 379-440.
    18. Carolina Osorio & Michel Bierlaire, 2013. "A Simulation-Based Optimization Framework for Urban Transportation Problems," Operations Research, INFORMS, vol. 61(6), pages 1333-1345, December.
    19. Chiabaut, Nicolas & Leclercq, Ludovic & Buisson, Christine, 2010. "From heterogeneous drivers to macroscopic patterns in congestion," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 299-308, February.
    20. G. F. Newell, 1961. "Nonlinear Effects in the Dynamics of Car Following," Operations Research, INFORMS, vol. 9(2), pages 209-229, April.
    21. Denos C. Gazis & Robert Herman & Renfrey B. Potts, 1959. "Car-Following Theory of Steady-State Traffic Flow," Operations Research, INFORMS, vol. 7(4), pages 499-505, August.
    22. Zhang, H. M., 1998. "A theory of nonequilibrium traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 485-498, September.
    23. Tordeux, Antoine & Lassarre, Sylvain & Roussignol, Michel, 2010. "An adaptive time gap car-following model," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1115-1131, September.
    24. Newell, G. F., 2002. "A simplified car-following theory: a lower order model," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 195-205, March.
    25. 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.
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