Modeling crowd evacuation of a building based on seven methodological approaches

Zheng, Xiaoping; Zhong, Tingkuan; Liu, Mengting

doi:10.1016/j.buildenv.2008.04.002

Cited by 502 publications

(214 citation statements)

References 65 publications

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“…Gwynne et al (1999) recognized a trend towards implementing more and more behavioral characteristics to match the real human reaction in case of emergencies. More recently, Zheng et al (2009) confirmed this trend by proposing combinations of various approaches to study crowd evacuation, employing rules from one approach on the basic principles of the other approach. However, no evacuation model already fully addresses all behavioral aspects involved in emergency situations and evacuations.…”

Section: State-of-the-art In Evacuation Modelingmentioning

confidence: 76%

Measuring the exitability of buildings: A new perspective on indoor accessibility

et al. 2012

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In the last decades, geographers' attention has been drawn to the vertical dimension of space and indoor environments due to population growth and concomitant city expansion. While traditional geography has long studied merely horizontal relationships of spatial processes and phenomena, recent years have also witnessed a growing number of studies that have sought to extend traditional spatial analysis tools to three-dimensional and indoor environments. In line with these developments, this paper proposes a new indoor accessibility measure which quantifies the quality of access to exits, called exitability. In this, the movement of people with respect to its three-dimensional environment, the user characteristics and the surrounding occupant interactions is considered key. Since the accessibility of exits is most important during evacuations, the calculation of exitability uses existing evacuation flow models. In a case study, we demonstrate the usefulness of exitability measurements through an application on existing building data.

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Section: State-of-the-art In Evacuation Modelingmentioning

confidence: 76%

Measuring the exitability of buildings: A new perspective on indoor accessibility

et al. 2012

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“…The detailed assessments of the existing modeling approaches and simulation models can be found in the literature [21][22][23][24].…”

Section: Evacuation Models and Crowd Dynamicsmentioning

confidence: 99%

“…In microscopic models, the evacuating population is considered to be discrete individuals, and collective phenomena emerge from the interactions between individuals. Macroscopic models capture the evacuation situation from a global perspective and represent collective phenomena directly [21,22].…”

Section: Evacuation Models and Crowd Dynamicsmentioning

confidence: 99%

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Zhao

Winter

Tomko

2017

IJGI

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Abstract:The lonelier evacuees find themselves, the riskier become their wayfinding decisions. This research supports single evacuees in a dynamically changing environment with risk-aware guidance. It deploys the concept of decentralized evacuation, where evacuees are guided by smartphones acquiring environmental knowledge and risk information via exploration and knowledge sharing by peer-to-peer communication. Peer-to-peer communication, however, relies on the chance that people come into communication range with each other. This chance can be low. To bridge between people being not at the same time at the same places, this paper suggests information depositories at strategic locations to improve information sharing. Information depositories collect the knowledge acquired by the smartphones of evacuees passing by, maintain this information, and convey it to other passing-by evacuees. Multi-agent simulation implementing these depositories in an indoor environment shows that integrating depositories improves evacuation performance: It enhances the risk awareness and consequently increases the chance that people survive and reduces their evacuation time. For evacuating dynamic events, deploying depositories at staircases has been shown more effective than deploying them in corridors.

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“…Due to interest in understanding human spatial behaviour, pedestrian mobility has long been an active research area in location based services [3], emergency management [4], determining infrastructural requirements [5] and urban planning [6]. Within urban planning and design, the vitality of a city is not generally measured using spatial analysis but by quantifying the number of people visiting the city and the economic value that brings.…”

Section: Introductionmentioning

confidence: 99%

Interpreting Pedestrian Behaviour by Visualising and Clustering Movement Data

McArdle

Demšar

Spek

et al. 2013

Web and Wireless Geographical Information Systems

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Abstract. Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This paper introduces such a geovisual analytics environment for exploring movement trajectories, which provides visualisation interfaces, based on the classic space-time cube. Additionally, a new approach, using the mathematical description of motion within a space-time cube, is used to determine the similarity of trajectories and forms the basis for clustering them. These techniques were used to analyse pedestrian movement. The results reveal interesting and useful spatiotemporal patterns and clusters of pedestrians exhibiting similar behaviour.

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Modeling crowd evacuation of a building based on seven methodological approaches

Cited by 502 publications

References 65 publications

Measuring the exitability of buildings: A new perspective on indoor accessibility

Measuring the exitability of buildings: A new perspective on indoor accessibility

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Interpreting Pedestrian Behaviour by Visualising and Clustering Movement Data

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