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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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