Human centric VR system development supporting fire emergency evacuation: A novel knowledge-data dual driven approach

Ling, Jiaxin, Li, Xiaojun, Shen, Yi, Chen, Chao, Yan, Zhiguo, Zhu, Hehua and Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133 2025. Human centric VR system development supporting fire emergency evacuation: A novel knowledge-data dual driven approach. Expert Systems with Applications 273 , 126895. 10.1016/j.eswa.2025.126895

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Abstract

Catastrophic fire accidents happened inside the tunnel have made it evident that human factors, especially misconduct, should be taken into account when it comes to fire emergency evacuation. However, conventional approaches separate fire safety education from evacuation training, failing to account for individual capabilities and behavioral dynamics, resulting in less intuitive and ineffective preparedness. A human-centric and more adaptive training for tunnel fire evacuation which takes both knowledge learning and behavior training into account is in urgent need. Motivated by such need, this study proposes a knowledge-data dual driven (KD3) framework, to seamlessly combine tunnel fire knowledge transfer and evacuation training into a unified system. A Virtual Reality (VR) system is developed based on KD3, which is composed of interactive fire-knowledge transfer module and immersive fire training module. To verify the applicability and effectiveness of the established system, the interactive fire-knowledge transfer module was open to public for different tunnel users to learn, and a total of 50 participants were recruited to conduct VR training. Results verify the rationale of the developed system, as well as the proposed KD3 framework, demonstrating that the integration of knowledge learning and VR training significantly improves individuals’ evacuation decision-making and escape behavior during tunnel fires. These findings contribute to a paradigm shift in fire evacuation training by bridging the gap between theoretical learning and practical application. The study provides critical insights into human-centric emergency preparedness and offers practical guidance for future adaptive training systems in emergency.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Elsevier
ISSN:	0957-4174
Date of Acceptance:	12 February 2025
Last Modified:	10 Dec 2025 15:00
URI:	https://orca.cardiff.ac.uk/id/eprint/183103

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