Agent-Based Simulation of Heterogeneous Crowd Flows in Critical Infrastructures During Emergencies

Agent-Based Simulation of Heterogeneous Crowd Flows in Critical Infrastructures During Emergencies

Umberto Battista, Pietro De Vito, Davide Ottonello, Deborah Hugon
Copyright: © 2022 |Pages: 18
DOI: 10.4018/IJCWT.305861
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Abstract

Scope of this work was the development of a model able to simulate the flows and behaviours of heterogeneous crowds in a large transport hub, both in normal conditions and during an emergency, like a terrorist attack. These places are indeed also so-called “soft targets”, public spaces which are preferred targets of terrorists because they provide them with the opportunity to maximize casualties and publicity. Different modelling approaches were investigated and finally agent-based modelling and the BDI (belief-desire-intention) architecture were selected. Several scenarios were also identified to simulate the crowd behaviour. Flowcharts were developed to model users’ actions and interactions; while statecharts to model emergency conditions and behavioural changes. Simulations were then used to identify weak points in the infrastructure and to analyse the evacuation times for each user category investigated. Finally, various solutions were proposed and simulated, to improve crowd flows and reduce evacuation times.
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Introduction

The European Union recognizes the crucial importance of protecting critical infrastructures and their users. During recent years, many projects have been executed and concrete actions implemented according to the European Programme for Critical Infrastructure Protection (EPCIP). These initiatives are due to the significant increase in the number of critical infrastructures and soft targets hit by terrorist attacks (e.g., airports, railway stations, arenas, etc.). This is confirmed by attack records, that include airports, train, and metro stations as the main objectives. Indeed they are always very crowded, and the potential death toll of an attack is very high. Istanbul (Ataturk airport, 2016), Brussels (Zaventem airport and Maalbeek metro station, 2016), London (Liverpool Street, Edgware Road and King's Cross St Pancras metro stations and a bus in Tavistock Square, 2005), Madrid (Atocha, El Pozo and Santa Eugenia railway stations), Paris (Stade de France and Saint-Denis, 2015) are just some recent examples.

The European Commission defines a critical infrastructure as: “[…] an asset or system which is essential for the maintenance of vital societal functions. The damage to a critical infrastructure, its destruction or disruption by natural disasters, terrorism, criminal activity or malicious behaviour, may have a significant negative impact for the security of the EU and the well-being of its citizens.” (Critical infrastructure protection | EU Science Hub, n.d.).

In order to avoid catastrophic events, security measures and protection standards for critical infrastructure have been increased by every Member State. In addition, new technologies to study different scenarios exist with the purpose of identifying weaknesses and vulnerabilities in the infrastructure investigated. Through this analysis, the people behaviour during normal and emergency conditions is simulated in order to identify critical areas and operations assign and to establish action plan for possible interventions.

This study is focused in particular on the large transportation hubs, since these are used every day to reach several places in the shortest time possible by thousands of people. In particular, roads and rail tracks are the primary infrastructures for land transport; bridges and tunnels are infrastructures that allow either to dam or to cross an obstacle; while stations, airports and terminals are the hubs that allow the basic interaction between users and the means of transport.

This paper presents the activities carried out within two European collaborative projects: FAIR Stations (2017-2019) and EUProtect (2019-ongoing). In both projects crowd simulations in railway infrastructures during ordinary and emergency situations requiring an evacuation were developed. The use cases are two stations in Madrid: Chamartín, the second major railway station of the Spanish capital, hosting high-speed trains, urban trains, and the Aluche metro station, a station connecting the metro to regional train line.

The aim of this paper is to summarize the studies carried out in both projects using agent-based modelling to simulate heterogeneous crowd flows in critical infrastructures. The approach used to develop the agent-based models, set up scenarios, run a simulation campaign and gather results is therefore described. The simulations have been developed with a software tool able to create virtual models of the environment for discrete, continuous and hybrid systems.

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