IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v89y2016icp58-81.html
   My bibliography  Save this article

Probabilistic speed–density relationship for pedestrian traffic

Author

Listed:
  • Nikolić, Marija
  • Bierlaire, Michel
  • Farooq, Bilal
  • de Lapparent, Matthieu

Abstract

We propose a probabilistic modeling approach to represent the speed–density relationship of pedestrian traffic. The approach is data-driven, and it is motivated by the presence of high scatter in the raw data that we have analyzed. We show the validity of the proposed approach, and its superiority compared to deterministic approaches from the literature using a dataset collected from a real scene and another from a controlled experiment.

Suggested Citation

  • Nikolić, Marija & Bierlaire, Michel & Farooq, Bilal & de Lapparent, Matthieu, 2016. "Probabilistic speed–density relationship for pedestrian traffic," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 58-81.
  • Handle: RePEc:eee:transb:v:89:y:2016:i:c:p:58-81
    DOI: 10.1016/j.trb.2016.04.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261516301655
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2016.04.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    2. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    3. Hughes, Roger L., 2002. "A continuum theory for the flow of pedestrians," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 507-535, July.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Alain Trognon, 1987. "Les méthodes du pseudo-maximum de vraisemblance," Annals of Economics and Statistics, GENES, issue 8, pages 117-134.
    10. repec:adr:anecst:y:1987:i:8:p:06 is not listed on IDEAS
    11. Steffen, B. & Seyfried, A., 2010. "Methods for measuring pedestrian density, flow, speed and direction with minimal scatter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1902-1910.
    12. G. F. Newell, 1961. "Nonlinear Effects in the Dynamics of Car Following," Operations Research, INFORMS, vol. 9(2), pages 209-229, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Bosina, Ernst & Weidmann, Ulrich, 2017. "Estimating pedestrian speed using aggregated literature data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 1-29.
    3. Hänseler, Flurin S. & van den Heuvel, Jeroen P.A. & Cats, Oded & Daamen, Winnie & Hoogendoorn, Serge P., 2020. "A passenger-pedestrian model to assess platform and train usage from automated data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 948-968.
    4. Wang, Shuaian & Zhang, Wei & Qu, Xiaobo, 2018. "Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 318-335.
    5. Ji, Jingwei & Lu, Ligang & Jin, Zihao & Wei, Shoupeng & Ni, Lu, 2018. "A cellular automata model for high-density crowd evacuation using triangle grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1034-1045.
    6. Andrea Gemma & Orlando Giannattasio & Livia Mannini, 2023. "Motorway Traffic Emissions Estimation through Stochastic Fundamental Diagram," Sustainability, MDPI, vol. 15(13), pages 1-16, June.
    7. Huang, Shenshi & Zhang, Teng & Lo, Siuming & Lu, Shouxiang & Li, Changhai, 2018. "Experimental study of individual and single-file pedestrian movement in narrow seat aisle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1023-1033.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. van Wageningen-Kessels, Femke & Leclercq, Ludovic & Daamen, Winnie & Hoogendoorn, Serge P., 2016. "The Lagrangian coordinate system and what it means for two-dimensional crowd flow models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 272-285.
    4. 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.
    5. Saberi, Meead & Aghabayk, Kayvan & Sobhani, Amir, 2015. "Spatial fluctuations of pedestrian velocities in bidirectional streams: Exploring the effects of self-organization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 120-128.
    6. Qingyan Ning & Maosheng Li, 2022. "Modeling Pedestrian Detour Behavior By-Passing Conflict Areas," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    7. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Data-driven framework for the adaptive exit selection problem in pedestrian flow: Visual information based heuristics approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    8. Li, Maosheng & Shu, Panpan & Xiao, Yao & Wang, Pu, 2021. "Modeling detour decision combined the tactical and operational layer based on perceived density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    9. Hänseler, Flurin S. & Bierlaire, Michel & Scarinci, Riccardo, 2016. "Assessing the usage and level-of-service of pedestrian facilities in train stations: A Swiss case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 106-123.
    10. Giuliani, Elisa & Martinelli, Arianna & Rabellotti, Roberta, 2016. "Is Co-Invention Expediting Technological Catch Up? A Study of Collaboration between Emerging Country Firms and EU Inventors," World Development, Elsevier, vol. 77(C), pages 192-205.
    11. Bettina Becker & Martin Theuringer, 2000. "Macroeconomic Determinants of Contingent Protection: The Case of the European Union," IWP Discussion Paper Series 02/2000, Institute for Economic Policy, Cologne, Germany.
    12. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    13. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    14. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 29-46, January.
    15. Dionne, Georges, 1998. "La mesure empirique des problèmes d’information," L'Actualité Economique, Société Canadienne de Science Economique, vol. 74(4), pages 585-606, décembre.
    16. de Rassenfosse, Gaétan & Schoen, Anja & Wastyn, Annelies, 2014. "Selection bias in innovation studies: A simple test," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 287-299.
    17. Gary King, 1989. "A Seemingly Unrelated Poisson Regression Model," Sociological Methods & Research, , vol. 17(3), pages 235-255, February.
    18. Emilie Alberola & Julien Chevallier & Benoît Chèze, 2008. "The EU Emissions Trading Scheme : Disentangling the Effects of Industrial Production and CO2 Emissions on Carbon Prices," Working Papers hal-04140795, HAL.
    19. Czarnitzki, Dirk & Doherr, Thorsten & Hussinger, Katrin & Schliessler, Paula & Toole, Andrew A., 2016. "Knowledge Creates Markets: The influence of entrepreneurial support and patent rights on academic entrepreneurship," European Economic Review, Elsevier, vol. 86(C), pages 131-146.
    20. Alvarez, Javier & Arellano, Manuel, 2022. "Robust likelihood estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 21-61.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:89:y:2016:i:c:p:58-81. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.