A Collaborative Emergency Drill System for Urban Tunnels Using BIM and an Agent-Based Model

Gang Yu, Lihua Shi, Yan Wang (), Jing Xiong () and Yucong Jin
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Gang Yu: SILC Business School, Shanghai University, Shanghai 201800, China
Lihua Shi: SILC Business School, Shanghai University, Shanghai 201800, China
Yan Wang: Department of Engineering Management, Sichuan College of Architectural Technology, Deyang 610399, China
Jing Xiong: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Yucong Jin: SILC Business School, Shanghai University, Shanghai 201800, China

Sustainability, 2023, vol. 15, issue 18, 1-19

Abstract: With the rapid development of smart cities, the refined management of urban highway tunnels has put forward higher requirements for the emergency disposal ability of operation and maintenance personnel. This paper proposed a collaborative emergency drill system for urban tunnels using building information modeling (BIM) and an agent-based model. The objectives of this paper are as follows: (1) To help address the challenge of multi-person collaborative intelligent drills in complex emergency scenarios, this system constructed an emergency collaborative drill model and a virtual emergency scenario description method based on trait-based objects (TBOs). (2) To help address the challenge of the organization and integration of multi-source heterogeneous data in complex emergency scenarios, the system established an emergency scenario generation method through lightweight BIM data, standard emergency plan documents, and virtual emergency scenario data. The system was successfully applied to the Hongmei South Road Tunnel in Shanghai, China. The feasibility of the proposed system provided practical help for tunnel emergency management and was extended to other urban tunnels in Shanghai.

Keywords: emergency management of underground space; building information modeling; tunnel emergency drill; agent-based model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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