A Method for Joint Estimation of Homogeneous Model Parameters and Heterogeneous Desired Speeds

Fredrik Johansson

doi:10.17815/CD.2020.63

Authors

Fredrik Johansson Swedish National Road and Transport Research Institute (VTI), Gothenburg, Sweden

DOI:

https://doi.org/10.17815/CD.2020.63

Keywords:

pedestrian simulation, desired speed, social force model, calibration, estimation

Abstract

One of the main strengths of microscopic pedestrian simulation models is the ability to explicitly represent the heterogeneity of the pedestrian population. Most pedestrian populations are heterogeneous with respect to the desired speed, and the outputs of microscopic models are naturally sensitive to the desired speed; it has a direct effect on the flow and travel time, thus strongly affecting results that are of interest when applying pedestrian simulation models in practice. An inaccurate desired speed distribution will in most cases lead to inaccurate simulation results. In this paper we propose a method to estimate the desired speed distribution by treating the desired speeds as model parameters to be adjusted in the calibration together with other model parameters. This leads to an optimization problem that is computationally costly to solve for large data sets. We propose a heuristic method to solve this optimization problem by decomposing the original problem in simpler parts that are solved separately. We demonstrate the method on trajectory data from Stockholm central station and analyze the results to conclude that the method is able to produce a plausible desired speed distribution under slightly congested conditions.

References

B. Hankin and R. Wright, “Passenger flow in subways,” OR, vol. 9, no. 2, pp. 81–88, 1958.

W. H. Lam and C. Cheung, “Pedestrian speed/flow relationships for walking facilities in Hong Kong,” Journal of transportation engineering, vol. 126, no. 4, pp. 343–349, 2000.

W. Daamen, “Modelling Passenger Flows in Public Transport Facilities,” Ph.D. dissertation, TU Delft, 2004.

U. Weidmann, “Transporttechnik der fußgänger,” IVT, Institut für Verkehrsplanung, Transporttechnik, Strassen-und Eisenbahnbau, 1992.

L. Henderson, “The statistics of crowd fluids,” Nature, vol. 229, pp. 381–383, 1971.

W. Daamen and S. P. Hoogendoorn, “Controlled experiments to derive walking behaviour,” European journal of transport and infrastructure research EJTIR, 3 (1), 2003.

W. Daamen and S. P. Hoogendoorn, “Experimental research of pedestrian walking behavior,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1828, no. 1, pp. 20–30, 2003.

S. Hoogendoorn, “Unified approach to estimating free speed distributions,” Transportation Research Part B: Methodological, vol. 39, no. 8, pp. 709–727, Sep. 2005.

A. Johansson, D. Helbing, and P. K. Shukla, “Specification of the social force pedestrian model by evolutionary adjustment to video tracking data,” Advances in Complex Systems, vol. 10, no. SUPPL. 2, pp. 271–288, 2007.

A. Johansson, “Data-Driven Modeling of Pedestrian Crowds,” Ph.D. dissertation, Technische Universität Dresden, 2009.

F. Zanlungo, T. Ikeda, and T. Kanda, “Social force model with explicit collision prediction,” Europhysics Letters, vol. 93, no. 6, p. 68005, 2011.

D. Helbing and P. Molnár, “Social force model for pedestrian dynamics,” Physical Review E: Statistical, nonlinear and soft matter physics, vol. 51, pp. 4282–4286, 1995.

S. J. Wright, “Coordinate descent algorithms,” Mathematical Programming, vol. 151, no. 1, pp. 3–34, Jun. 2015.

M. Lagervall and S. Samuelsson, “Microscopic Simulation of Pedestrian Traffic in a Station Environment: A Study of Actual and Desired Walking Speeds,” Master’s Thesis, Linköping University, Communications and Transport Systems, The Institute of Technology, 2014.