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Towards Microscopic Calibration of Pedestrian Simulation Models Using Open Trajectory Datasets: The Case Study of the Edinburgh Informatics Forum

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Abstract

The investigation of crowd behaviours in normal and emergency situations has been greatly facilitated by various agent-based pedestrian models. Those models are built upon different assumptions in order to represent or mimic reality. One of the key challenges in pedestrian modelling is the verification of those assumptions or the best model specification by using existing datasets and suitable calibration approaches.

This paper illustrates a case study where we calibrate different pedestrian model specifications with an open pedestrian trajectory dataset from Edinburgh Informatics Forum and select the best model according to various model selection criteria. Two floor field cellular automaton models with Euclidean and modified Euclidean distance metrics are presented for the static floor field. Our study shows that the modified Euclidean distance metrics can provide better fitting for the navigation environments without obstacles.

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Author information

Authors and Affiliations

  1. School of Built Environment, Massey University, Auckland, New Zealand

    Ruggiero Lovreglio

  2. Institute of Industrial Science, University of Tokyo, Tokyo, Japan

    Charitha Dias

  3. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Xiang Song

  4. Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK

    Lucia Ballerini

Authors
  1. Ruggiero Lovreglio
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  2. Charitha Dias
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  3. Xiang Song
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  4. Lucia Ballerini
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Corresponding author

Correspondence to Ruggiero Lovreglio .

Editor information

Editors and Affiliations

  1. Dept. of Civil & Environ. Engineering, George Washington University, Washington, DC, USA

    Samer H. Hamdar

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Lovreglio, R., Dias, C., Song, X., Ballerini, L. (2019). Towards Microscopic Calibration of Pedestrian Simulation Models Using Open Trajectory Datasets: The Case Study of the Edinburgh Informatics Forum. In: Hamdar, S. (eds) Traffic and Granular Flow '17. TGF 2017. Springer, Cham. https://doi.org/10.1007/978-3-030-11440-4_25

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