Multiclass Speed-Density Relationship for Pedestrian Traffic

Marija Nikolić (), Michel Bierlaire (), Matthieu de Lapparent () and Riccardo Scarinci ()
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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

Transportation Science, 2019, vol. 53, issue 3, 642-664

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 .

Keywords: pedestrian traffic; speed-density relationship; heterogeneity; latent class model; individual trajectories (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:53:y:2019:i:3:p:642-664

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