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

Ruggiero Lovreglio (), Charitha Dias (), Xiang Song () and Lucia Ballerini ()
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Ruggiero Lovreglio: Massey University, School of Built Environment
Charitha Dias: University of Tokyo, Institute of Industrial Science
Xiang Song: Massachusetts Institute of Technology, Department of Civil and Environmental Engineering
Lucia Ballerini: University of Edinburgh, Department of Neuroimaging Sciences

A chapter in Traffic and Granular Flow '17, 2019, pp 215-223 from Springer

Abstract: 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.

Date: 2019
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DOI: 10.1007/978-3-030-11440-4_25

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