Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

The Potential of Agent Based Models for Testing City Evacuation Strategies Under a Flood Event

AbstractThis paper explores the uses of Agent Based Models (ABM) and its potential to test large scale evacuation strategies in coastal cities under threat of an imminent flooding due to extreme hydro-meteorological events. The first part of the paper is an introduction to the field of complex adaptive systems (CAS) and the principles and uses of ABM in this field. It is also presented the benefits and limitations of such models. The second part of the paper focuses on the theory used to build the ABM. For this study, theories and frameworks of human behaviour and disaster psychology were used. To feed the ABM model qualitative and quantitative attributes or characteristics of human beings are abstracted from literature review, fieldwork and expert's knowledge. The third part of the paper shows the methodology used to build and implement the ABM model using Repast Symphony, a Java based modelling system. The results of the initial experiments implemented in a region of the city of Marbella, southern Spain, are presented and discussed. The preliminary results are promising to further enhance the development of the model and its implementation and testing at full city scale

The Potential of Agent Based Models for Testing City Evacuation Strategies Under a Flood Event

AbstractThis paper explores the uses of Agent Based Models (ABM) and its potential to test large scale evacuation strategies in coastal cities under threat of an imminent flooding due to extreme hydro-meteorological events. The first part of the paper is an introduction to the field of complex adaptive systems (CAS) and the principles and uses of ABM in this field. It is also presented the benefits and limitations of such models. The second part of the paper focuses on the theory used to build the ABM. For this study, theories and frameworks of human behaviour and disaster psychology were used. To feed the ABM model qualitative and quantitative attributes or characteristics of human beings are abstracted from literature review, fieldwork and expert's knowledge. The third part of the paper shows the methodology used to build and implement the ABM model using Repast Symphony, a Java based modelling system. The results of the initial experiments implemented in a region of the city of Marbella, southern Spain, are presented and discussed. The preliminary results are promising to further enhance the development of the model and its implementation and testing at full city scale

Scalable context-dependent analysis of emergency egress models

Pervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person's mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem. We present results on a novel usage of a scalable analysis technique in this context. We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress. The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint, when classes of homogeneous individuals are considered for a (continuous)approximation of overall system behaviour

Key challenges in agent-based modelling for geo-spatial simulation

Agent-based modelling (ABM) is fast becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and space, generates emergent order, often at higher levels than those at which such agents operate. ABM however raises as many challenges as it seeks to resolve. It is the purpose of this paper to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems. The seven challenges we pose involve: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the ways the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. Once catalogued, we then illustrate these challenges with a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation tuned to London data which elaborates the standard Schelling (1971) model, and an agent-based residential location built according to spatial interactions principles, calibrated to trip data for Greater London. The ambiguities posed by this new style of modelling are drawn out as conclusions

A holistic model of emergency evacuations in large, complex, public occupancy buildings

Evacuations are crucial for ensuring the safety of building occupants in the event of an emergency. In large, complex, public occupancy buildings (LCPOBs) these procedures are significantly more complex than the simple withdrawal of people from a building. This thesis has developed a novel, holistic, theoretical model of emergency evacuations in LCPOBs inspired by systems safety theory. LCPOBs are integral components of complex socio-technical systems, and therefore the model describes emergency evacuations as control actions initiated in order to return the building from an unsafe state to a safe state where occupants are not at risk of harm. The emergency evacuation process itself is comprised of four aspects - the movement (of building occupants), planning and management, environmental features, and evacuee behaviour. To demonstrate its utility and applicability, the model has been employed to examine various aspects of evacuation procedures in two example LCPOBs - airport terminals, and sports stadiums. The types of emergency events initiating evacuations in these buildings were identified through a novel hazard analysis procedure, which utilised online news articles to create events databases of previous evacuations. Security and terrorism events, false alarms, and fires were found to be the most common cause of evacuations in these buildings. The management of evacuations was explored through model-based systems engineering techniques, which identified the communication methods and responsibilities of staff members managing these events. Social media posts for an active shooting event were analysed using qualitative and machine learning methods to determine their utility for situational awareness. This data source is likely not informative for this purpose, as few posts detail occupant behaviours. Finally, an experimental study on pedestrian dynamics with movement devices was conducted, which determined that walking speeds during evacuations were unaffected by evacuees dragging luggage, but those pushing pushchairs and wheelchairs will walk significantly slower.Open Acces

Developing a model of evacuation after an earthquake in Lebanon

This article describes the development of an agent-based model (AMEL, Agent-based Model for Earthquake evacuation in Lebanon) that aims at simulating the movement of pedestrians shortly after an earthquake. The GAMA platform was chosen to implement the model. AMEL is applied to a real case study, a district of the city of Beirut, Lebanon, which potentially could be stricken by a M7 earthquake. The objective of the model is to reproduce real life mobility behaviours that have been gathered through a survey in Beirut and to test different future scenarios, which may help the local authorities to target information campaigns.Comment: 8 pages, 11 figures, ISCRAM Vietnam Conference, November 201