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Calibration of stochastic link-based fundamental diagram with explicit consideration of speed heterogeneity

Author

Listed:
  • Bai, Lu
  • Wong, S.C.
  • Xu, Pengpeng
  • Chow, Andy H.F.
  • Lam, William H.K.

Abstract

This study aims to establish a stochastic link-based fundamental diagram (FD) with explicit consideration of two available sources of uncertainty: speed heterogeneity, indicated by the speed variance within an interval, and rainfall intensity. A stochastic structure was proposed to incorporate the speed heterogeneity into the traffic stream model, and the random-parameter structures were applied to reveal the unobserved heterogeneity in the mean speeds at an identical density. The proposed stochastic link-based FD was calibrated and validated using real-world traffic data obtained from two selected road segments in Hong Kong. Traffic data were obtained from the Hong Kong Journey Time Indication System operated by the Hong Kong Transport Department during January 1 to December 31, 2017. The data related to rainfall intensity were obtained from the Hong Kong Observatory. A two-stage calibration based on Bayesian inference was proposed for estimating the stochastic link-based FD parameters. The predictive performances of the proposed model and three other models were compared using K-fold cross-validation. The results suggest that the random-parameter model considering the speed heterogeneity effect performs better in terms of both goodness-of-fit and predictive accuracy. The effect of speed heterogeneity accounts for 18%–24% of the total heterogeneity effects on the variance of FD. In addition, there exists unobserved heterogeneity across the mean speeds at an identical density, and the rainfall intensity negatively affects the mean speed and its effect on the variance of FD differs at different densities.

Suggested Citation

  • Bai, Lu & Wong, S.C. & Xu, Pengpeng & Chow, Andy H.F. & Lam, William H.K., 2021. "Calibration of stochastic link-based fundamental diagram with explicit consideration of speed heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 524-539.
  • Handle: RePEc:eee:transb:v:150:y:2021:i:c:p:524-539
    DOI: 10.1016/j.trb.2021.06.021
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    as
    1. 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.
    2. Coifman, Benjamin, 2015. "Empirical flow-density and speed-spacing relationships: Evidence of vehicle length dependency," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 54-65.
    3. Castillo, J. M. Del & Benítez, F. G., 1995. "On the functional form of the speed-density relationship--I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 29(5), pages 373-389, October.
    4. 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.
    5. Qian, Wei-Liang & F. Siqueira, Adriano & F. Machado, Romuel & Lin, Kai & Grant, Ted W., 2017. "Dynamical capacity drop in a nonlinear stochastic traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 328-339.
    6. Paul I. Richards, 1956. "Shock Waves on the Highway," Operations Research, INFORMS, vol. 4(1), pages 42-51, February.
    7. 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.
    8. Harold Greenberg, 1959. "An Analysis of Traffic Flow," Operations Research, INFORMS, vol. 7(1), pages 79-85, February.
    9. Ghiasi, Amir & Hussain, Omar & Qian, Zhen (Sean) & Li, Xiaopeng, 2017. "A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 266-292.
    10. Siqueira, Adriano F. & Peixoto, Carlos J.T. & Wu, Chen & Qian, Wei-Liang, 2016. "Effect of stochastic transition in the fundamental diagram of traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 1-13.
    11. Qu, Xiaobo & Zhang, Jin & Wang, Shuaian, 2017. "On the stochastic fundamental diagram for freeway traffic: Model development, analytical properties, validation, and extensive applications," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 256-271.
    12. Wang, Haizhong & Li, Jia & Chen, Qian-Yong & Ni, Daiheng, 2011. "Logistic modeling of the equilibrium speed-density relationship," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 554-566, July.
    13. 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.
    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. G. F. Newell, 1961. "Nonlinear Effects in the Dynamics of Car Following," Operations Research, INFORMS, vol. 9(2), pages 209-229, April.
    18. Windover, John R. & Cassidy, Michael J., 2001. "Some observed details of freeway traffic evolution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(10), pages 881-894, December.
    19. Wu, Ning, 2002. "A new approach for modeling of Fundamental Diagrams," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(10), pages 867-884, December.
    20. Castillo, J. M. Del & Benítez, F. G., 1995. "On the functional form of the speed-density relationship--II: Empirical investigation," Transportation Research Part B: Methodological, Elsevier, vol. 29(5), pages 391-406, October.
    21. Laval, Jorge A. & Daganzo, Carlos F., 2006. "Lane-changing in traffic streams," Transportation Research Part B: Methodological, Elsevier, vol. 40(3), pages 251-264, March.
    22. 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.
    23. 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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