Open AccessSimulation framework for pedestrian dynamics: modelling and calibration
Author(s) -
Liberto Carlo,
Nigro Marialisa,
Carrese Stefano,
Mannini Livia,
Valenti Gaetano,
Zarelli Cristiano
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0677
Subject(s) - pedestrian , context (archaeology) , computer science , calibration , variety (cybernetics) , key (lock) , simulation , focus (optics) , quality (philosophy) , mode (computer interface) , transport engineering , systems engineering , human–computer interaction , engineering , artificial intelligence , computer security , physics , paleontology , philosophy , statistics , mathematics , optics , epistemology , biology
Pedestrian flow efficiency and safety are primary requirements in the effective configuration and management of urban gathering spaces, such as railway stations, stadiums, or shopping malls. Moreover, the quality and comfort level of available walking environments play a key role in the challenge of sustainable mobility. As a consequence, there has been growing interest in developing methodologies for analysing the walking transport mode. In this context, the authors deem crucial to build a pedestrian dynamics simulation framework that they can completely control, from the modelling and calibration under different flow conditions to the implementation of a user‐friendly tool that allows testing the model in a variety of case studies. In this study, they focus on the implementation and calibration of an agent‐based model that microscopically simulates the interactions between individuals and with the environment. They calibrate the model parameters with a behavioural‐based approach that relies on observed motion behaviours. Additionally, they present preliminary findings from pedestrian flow experiments performed and monitored with dedicated video recording systems. The collected data are meant to improve the calibration and validate the simulator, but they also provide insights into the emergence of collective behaviours, which can have significant upshots on the theoretical framework.