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Estimation of Pedestrian Origin-Destination Demand in Train Stations

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  • Flurin S. Hänseler

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

  • Nicholas A. Molyneaux

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

  • Michel Bierlaire

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

Abstract

We present a framework for estimating pedestrian demand within a train station. It takes into account ridership data, and various direct and indirect indicators of demand. Such indicators may include link flow counts, density measurements, survey data, historical, or other information. The problem is considered in discrete time and at the aggregate level, i.e., for groups of pedestrians associated with the same origin-destination pair and departure time interval. The formulation is probabilistic, allowing to consider the stochasticity of demand. A key element is the use of the train timetable, and in particular of train arrival times, to capture demand peaks. A case study analysis of a Swiss train station underlines the practical applicability of the proposed framework. Compared to a classical estimator that ignores the notion of a train timetable, the gain in accuracy in terms of root-mean-square error is between 20% and 50%. More importantly, the incorporation of the train schedule allows for prediction when little or no data besides the timetable and ridership information is available.

Suggested Citation

  • Flurin S. Hänseler & Nicholas A. Molyneaux & Michel Bierlaire, 2017. "Estimation of Pedestrian Origin-Destination Demand in Train Stations," Transportation Science, INFORMS, vol. 51(3), pages 981-997, August.
    • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:3:p:981-997
    DOI: 10.287/trsc.2016.0723
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    References listed on IDEAS

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    1. Yang, Hai, 1995. "Heuristic algorithms for the bilevel origin-destination matrix estimation problem," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 231-242, August.
    2. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    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. 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.
    5. Bierlaire, M. & Toint, Ph. L., 1995. "Meuse: An origin-destination matrix estimator that exploits structure," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 47-60, February.
    6. Fisk, C. S., 1988. "On combining maximum entropy trip matrix estimation with user optimal assignment," Transportation Research Part B: Methodological, Elsevier, vol. 22(1), pages 69-73, February.
    7. Goverde, Rob M.P., 2007. "Railway timetable stability analysis using max-plus system theory," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 179-201, February.
    8. Blue, Victor J. & Adler, Jeffrey L., 2001. "Cellular automata microsimulation for modeling bi-directional pedestrian walkways," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 293-312, March.
    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. Nguyen, S. & Morello, E. & Pallottino, S., 1988. "Discrete time dynamic estimation model for passenger origin/destination matrices on transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 22(4), pages 251-260, August.
    11. Zhou, Xuesong & Mahmassani, Hani S., 2007. "A structural state space model for real-time traffic origin-destination demand estimation and prediction in a day-to-day learning framework," Transportation Research Part B: Methodological, Elsevier, vol. 41(8), pages 823-840, October.
    12. Wong, S. C. & Tong, C. O., 1998. "Estimation of time-dependent origin-destination matrices for transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 35-48, January.
    13. Hazelton, Martin L., 2003. "Some comments on origin-destination matrix estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 811-822, December.
    14. Antonini, Gianluca & Bierlaire, Michel & Weber, Mats, 2006. "Discrete choice models of pedestrian walking behavior," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 667-687, September.
    15. Cascetta, Ennio, 1984. "Estimation of trip matrices from traffic counts and survey data: A generalized least squares estimator," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 289-299.
    16. Ennio Cascetta & Maria Nadia Postorino, 2001. "Fixed Point Approaches to the Estimation of O/D Matrices Using Traffic Counts on Congested Networks," Transportation Science, INFORMS, vol. 35(2), pages 134-147, May.
    17. A. Higgins & E. Kozan, 1998. "Modeling Train Delays in Urban Networks," Transportation Science, INFORMS, vol. 32(4), pages 346-357, November.
    18. Ennio Cascetta & Domenico Inaudi & Gérald Marquis, 1993. "Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts," Transportation Science, INFORMS, vol. 27(4), pages 363-373, November.
    19. 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.
    20. M. Bierlaire & F. Crittin, 2004. "An Efficient Algorithm for Real-Time Estimation and Prediction of Dynamic OD Tables," Operations Research, INFORMS, vol. 52(1), pages 116-127, February.
    21. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    22. Yang, Yudi & Fan, Yueyue, 2015. "Data dependent input control for origin–destination demand estimation using observability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 385-403.
    23. Hazelton, Martin L., 2000. "Estimation of origin-destination matrices from link flows on uncongested networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(7), pages 549-566, September.
    24. Cascetta, Ennio & Nguyen, Sang, 1988. "A unified framework for estimating or updating origin/destination matrices from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 22(6), pages 437-455, December.
    25. Michel Bierlaire & Frank Crittin, 2006. "Solving Noisy, Large-Scale Fixed-Point Problems and Systems of Nonlinear Equations," Transportation Science, INFORMS, vol. 40(1), pages 44-63, February.
    26. K. Ashok & M. E. Ben-Akiva, 2000. "Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin–Destination Flows," Transportation Science, INFORMS, vol. 34(1), pages 21-36, February.
    27. Van Zuylen, Henk J. & Willumsen, Luis G., 1980. "The most likely trip matrix estimated from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 14(3), pages 281-293, September.
    28. Yuan, Jianxin & Hansen, Ingo A., 2007. "Optimizing capacity utilization of stations by estimating knock-on train delays," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 202-217, February.
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