Real-time micro-modelling of a million pedestrians. Issue 1 (7th March 2016)

• Record Type: Journal Article
• Authors: Lohner, R; Baqui, Muhammad; Haug, Eberhard; Muhamad, Britto
• Is Part Of: Engineering computations. Volume 33:Issue 1(2016)
• Page Start: 217
• Page End: 237
• Publication Date: 2016-03-07
• Subjects: Parallel computing -- Simulation -- Crowd dynamics -- Pedestrian flow -- Traffic modelling; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-02-2015-0036
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: – The purpose of this paper is to develop a first-principles model for the simulation of pedestrian flows and crowd dynamics capable of computing the movement of a million pedestrians in real-time in order to assess the potential safety hazards and operational performance at events where many individuals are gathered. Examples of such situations are sport and music events, cinemas and theatres, museums, conference centres, places of pilgrimage and worship, street demonstrations, emergency evacuation during natural disasters. Design/methodology/approach: – The model is based on a series of forces, such as: will forces (the desire to reach a place at a certain time), pedestrian collision avoidance forces, obstacle/wall avoidance forces; pedestrian contact forces, and obstacle/wall contact forces. In order to allow for general geometries a so-called background triangulation is used to carry all geographic information. At any given time the location of any given pedestrian is updated on this mesh. The model has been validated qualitatively and quantitavely on repeated occasions. The code has been ported to shared and distributed memory parallel machines. Findings: – The results obtained show that the stated aim of computing the movement of a million pedestrians in real-time has been achieved. This is an important milestone, as it enables faster-than-real-time simulations of large crowds (stadiums, airports, train and bus stations, concerts) as well as evacuation simulations for whole cities. Research limitations/implications: – All models are wrong, but some are useful. The same applies to any modelling of pedestrians. Pedestrians are not machines, so stochastic runs will be required in the future in order to obtain statistically relevant ensembles. Practical implications: – This opens the way to link real-time data gathering of crowds (i.e. via cameras) with predictive calculations done faster than real-time, so that security personnel can be alerted to potential future problems during large-scale events. Social implications: – This will allow much better predictions for large-scale events, improving security and comfort. Originality/value: – This is the first time such speeds have been achieved for a micro-modelling code for pedestrians.