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Multiclass Speed-Density Relationship for Pedestrian Traffic

Author

Listed:
  • Marija Nikolić

    (Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland)

  • Michel Bierlaire

    (Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland)

  • Matthieu de Lapparent

    (University of Applied Sciences and Arts Western Switzerland, School of Business and Engineering Vaud, CH-1401 Yverdon-les-Bains, Switzerland0)

  • Riccardo Scarinci

    (Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland)

Abstract

We introduce a probabilistic modeling approach for pedestrian speed-density relationship. It is motivated by a high scatter in real data that precludes the use of traditional equilibrium relationships. To characterize the observed pattern, we relax the homogeneity assumption of equilibrium relations and propose a multiclass model. In addition to the general modeling framework, we also present some concrete model specifications. Real data are utilized to test the performance of the approach. The approach is able to reveal fundamental properties causing the heterogeneity in population and describe their impact on pedestrian movement. We also show the advantages of the proposed approach compared with approaches from the literature. The proposed model is flexible, and it provides richer information than traditional models. The e-companion is available at https://doi.org/10.1287/trsc.2018.0849 .

Suggested Citation

  • Marija Nikolić & Michel Bierlaire & Matthieu de Lapparent & Riccardo Scarinci, 2019. "Multiclass Speed-Density Relationship for Pedestrian Traffic," Transportation Science, INFORMS, vol. 53(3), pages 642-664, May.
    • Handle: RePEc:inm:ortrsc:v:53:y:2019:i:3:p:642-664
    DOI: 10.1287/trsc.2018.0849
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    References listed on IDEAS

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    1. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    2. Anders Johansson & Dirk Helbing & Pradyumn K. Shukla, 2007. "Specification Of The Social Force Pedestrian Model By Evolutionary Adjustment To Video Tracking Data," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(supp0), pages 271-288.
    3. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    4. Hänseler, Flurin S. & Lam, William H.K. & Bierlaire, Michel & Lederrey, Gael & Nikolić, Marija, 2017. "A dynamic network loading model for anisotropic and congested pedestrian flows," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 149-168.
    5. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    6. William Lam & Jodie Lee & C. Cheung, 2002. "A study of the bi-directional pedestrian flow characteristics at Hong Kong signalized crosswalk facilities," Transportation, Springer, vol. 29(2), pages 169-192, May.
    7. Robin, Th. & Antonini, G. & Bierlaire, M. & Cruz, J., 2009. "Specification, estimation and validation of a pedestrian walking behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 36-56, January.
    8. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    9. Joan Walker & Jieping Li, 2007. "Latent lifestyle preferences and household location decisions," Journal of Geographical Systems, Springer, vol. 9(1), pages 77-101, April.
    10. Hoogendoorn, S. P. & Bovy, P. H. L., 2004. "Pedestrian route-choice and activity scheduling theory and models," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 169-190, February.
    11. Kenneth L. Judd & Ben Skrainka, 2011. "High performance quadrature rules: how numerical integration affects a popular model of product differentiation," CeMMAP working papers CWP03/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. 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.
    13. Hoogendoorn, Serge P. & van Wageningen-Kessels, Femke L.M. & Daamen, Winnie & Duives, Dorine C., 2014. "Continuum modelling of pedestrian flows: From microscopic principles to self-organised macroscopic phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 684-694.
    14. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    15. Rastogi, R. & Ilango, T. & Chandra, S., 2013. "Pedestrian flow characteristics for different pedestrian facilities and situations," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 53, pages 1-5.
    16. Mariano,Roberto & Schuermann,Til & Weeks,Melvyn J. (ed.), 2000. "Simulation-based Inference in Econometrics," Cambridge Books, Cambridge University Press, number 9780521591126, September.
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