Modelling Context Effects in Exit Choice for Building Evacuations
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| Udgivet i: | Fire vol. 7, no. 5 (2024), p. 169 |
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| Andre forfattere: | , , , |
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MDPI AG
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| Online adgang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3059398497 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2571-6255 | ||
| 024 | 7 | |a 10.3390/fire7050169 |2 doi | |
| 035 | |a 3059398497 | ||
| 045 | 2 | |b d20240101 |b d20241231 | |
| 100 | 1 | |a Gao, Dongli | |
| 245 | 1 | |a Modelling Context Effects in Exit Choice for Building Evacuations | |
| 260 | |b MDPI AG |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Understanding exit choice behaviour is essential for optimising safety management strategies in building evacuations. Previous research focused on contextual attributes, such as spatial information, influencing exit choice, often using utility models based on monotonic functions of attributes. However, during emergencies, evacuees typically make rapid, less calculated decisions. The choice of context can significantly impact the evaluation of attributes, leading to preference reversals within the same choice set but under varying context conditions. This cognitive psychological phenomenon, known as context effects, encompasses the compromise effect, the similarity effect, and the attraction effect. While researchers have long recognised the pivotal role of context effects in human decision making, their incorporation into computer-aided evacuation management remains limited. To address this gap, we introduce context effects (CE) in a social force (SF) model, CE-SF. Evaluating CE-SF’s performance against the UF-SF model, which considers only the utility function (UF), we find that CE-SF better replicates exit choice behaviour across urgency levels, highlighting its potential to enhance evacuation strategies. Notably, our study identifies three distinct context effects during evacuations, emphasising their importance in advancing safety measures. | |
| 653 | |a Spatial data | ||
| 653 | |a Performance evaluation | ||
| 653 | |a Computer aided decision processes | ||
| 653 | |a Evacuations & rescues | ||
| 653 | |a Decision making | ||
| 653 | |a Preferences | ||
| 653 | |a Probability | ||
| 653 | |a Safety measures | ||
| 653 | |a Crowds | ||
| 653 | |a Evacuation | ||
| 653 | |a Efficiency | ||
| 653 | |a Safety management | ||
| 653 | |a Social | ||
| 700 | 1 | |a Liang, Xuanwen | |
| 700 | 1 | |a Chen, Qian | |
| 700 | 1 | |a Qiu, Hongpeng | |
| 700 | 1 | |a Lee, Eric Wai Ming | |
| 773 | 0 | |t Fire |g vol. 7, no. 5 (2024), p. 169 | |
| 786 | 0 | |d ProQuest |t Agriculture Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3059398497/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3059398497/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3059398497/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |