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Testing communication strategies to save lives in emergency evacuation

Sector: Education • Location: United Kingdom

Source: EU Funding & Tenders Portal

Project
Ended

The EU urgently seeks to improve emergency evacuation preparedness. EU public spaces are getting more crowded. Fires and terrorist attacks require emergency evacuation. Faster evacuation from public buildings during emergencies saves more lives. Observations of actual emergencies show that people tend to be slow to respond to evacuation alarms (taking up to 10 minutes) and take the familiar route

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The project “Testing communication strategies to save lives in emergency evacuation” is an infrastructure initiative in the Education sector, located in United Kingdom. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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Description

Description

The EU urgently seeks to improve emergency evacuation preparedness. EU public spaces are getting more crowded. Fires and terrorist attacks require emergency evacuation. Faster evacuation from public buildings during emergencies saves more lives. Observations of actual emergencies show that people tend to be slow to respond to evacuation alarms (taking up to 10 minutes) and take the familiar route out instead of the nearest exit. The EU calls for evidence-based recommendations for evacuations, which are mostly non-existent. The state of the art uses computer models of evacuation speed, but more realism is needed. We take the novel approach of combining state of the art computer modeling with insights from risk communication to improve speed and survival in emergency evacuations. This project aims to: 1. Identify which risky behaviors occur in emergency evacuations and underlying causes (WP1). 2. Use models to identify communication strategies that improve evacuation time and survival (WP2). 3. Test communication strategies for improving evacuation time and survival in experiments (WP3). To ultimately save lives, Aim 1 involves (a) observing behavior in existing videos of actual evacuations, and (b) interviewing emergency service members about their experiences in actual evacuations. Aim 2 will use ‘agent-based’ computer modeling, with which the Fellow has experience, to assess the effect of reducing the riskiest behaviors on evacuation time and survival rates. Based on the Supervisor’s expertise in risk communication and input from emergency service members, this will result in recommendations that will be tested in Aim 3 in actual evacuation drills. Our unique team has the interdisciplinary and practical expertise needed to improve evacuations. Our proposed work will promote transfer between the Fellow and the team through hands-on collaborative work. The UK is an ideal testbed for our project aims, but we will inform evacuations worldwide.

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