Literature DB >> 28925727

The Effect of Person Order on Egress Time: A Simulation Model of Evacuation From a Neolithic Visitor Attraction.

Arthur Stewart, Eyad Elyan, John Isaacs, Leah McEwen1, Lyn Wilson2.   

Abstract

OBJECTIVE: The aim of this study was to model the egress of visitors from a Neolithic visitor attraction.
BACKGROUND: Tourism attracts increasing numbers of elderly and mobility-impaired visitors to our built-environment heritage sites. Some such sites have very limited and awkward access, were not designed for mass visitation, and may not be modifiable to facilitate disabled access. As a result, emergency evacuation planning must take cognizance of robust information, and in this study we aimed to establish the effect of visitor position on egress.
METHOD: Direct observation of three tours at Maeshowe, Orkney, informed typical time of able-bodied individuals and a mobility-impaired person through the 10-m access tunnel. This observation informed the design of egress and evacuation models running on the Unity gaming platform.
RESULTS: A slow-moving person at the observed speed typically increased time to safety of 20 people by 170% and reduced the advantage offered by closer tunnel separation by 26%. Using speeds for size-specific characters of 50th, 95th, and 99th percentiles increased time to safety in emergency evacuation by 51% compared with able-bodied individuals.
CONCLUSION: Larger individuals may slow egress times of a group; however, a single slow-moving mobility-impaired person exerts a greater influence on group egress, profoundly influencing those behind. APPLICATION: Unidirectional routes in historic buildings and other visitor attractions are vulnerable to slow-moving visitors during egress. The model presented in this study is scalable, is applicable to other buildings, and can be used as part of a risk assessment and emergency evacuation plan in future work.

Entities:  

Keywords:  architecture; designing for the elderly; discrete-event simulation; risk assessment; simulation

Mesh:

Year:  2017        PMID: 28925727     DOI: 10.1177/0018720817729608

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  1 in total

1.  Design of Key Technologies for Elderly Public Network Services Based on Intelligent Recommendations.

Authors:  Xinjia Zhang
Journal:  Comput Intell Neurosci       Date:  2022-10-04
  1 in total

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