Acoustic Signal-Based Tunnel Incident Detection System

• Published in: The Journal of The Korea Institute of Intelligent Transport Systems Vol. 18; no. 5; pp. 112 - 125
• Main Author: Jang, Jinhwan
• Format: Journal Article
• Language: English
• Published: 한국ITS학회 31.10.2019
• Subjects: 전자/정보통신공학
• ISSN: 1738-0774; 2384-1729
• DOI: 10.12815/kits.2019.18.5.112

An acoustic signal-based, tunnel-incident detection system was developed and evaluated. The system was comprised of three components: algorithm, acoustic signal collector, and server system. The algorithm, which was based on nonnegative tensor factorization and a hidden Markov model, processes the acoustic signals to attenuate noise and detect incident-related signals. The acoustic signal collector gathers the tunnel sounds, digitalizes them, and transmits the digitalized acoustic signals to the center server. The server system issues an alert once the algorithm identifies an incident. The performance of the system was evaluated thoroughly in two steps: first, in a controlled tunnel environment using the recorded incident sounds, and second, in an uncontrolled tunnel environment using real-world incident sounds. As a result, the detection rates ranged from 80 to 95% at distances from 50 to 10 m in the controlled environment, and 94 % in the uncontrolled environment. The superiority of the developed system to the existing video image and loop detector-based systems lies in its instantaneous detection capability with less than 2 s. KCI Citation Count: 0