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JRM Vol.36 No.3 pp. 746-757
doi: 10.20965/jrm.2024.p0746
(2024)

Paper:

Vehicle Self-Position Estimation Using Lighting Recognition in Expressway Tunnel for Visual Inspection Flow

Yushi Moko* ORCID Icon, Yuka Hiruma**, Tomohiko Hayakawa*,** ORCID Icon, Yushan Ke*, Yoshimasa Onishi***, and Masatoshi Ishikawa* ORCID Icon

*Tokyo University of Science
1-3 Kagurazaka, Shinjuku-ku, Tokyo 113-8601, Japan

**Information Technology Center, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

***Central Nippon Expressway Company Limited
2-18-19 Nishiki, Naka-ku, Nagoya, Aichi 460-0003, Japan

Received:
November 19, 2023
Accepted:
February 20, 2024
Published:
June 20, 2024
Keywords:
self-position estimation, infrastructure inspection, tunnel, lighting facilities, high-speed camera
Abstract

In this study, a stable and high-speed vision-based self-position estimation method was proposed that improves upon the existing method of lane detection by recognizing the lighting facilities that are installed in tunnels on Japanese expressways where GNSS cannot be used. In addition, we proposed a method for inspecting multiple cracks at once by estimating the self-position with the successful rate 75% in the traveling direction by counting the lighting with the successful rate 99.85%. The effectiveness of the method was verified by capturing images of cracks in an actual tunnel. The proposed method will enable more frequent inspections for tunnel cracks that lead to flaking while maintaining infrastructure safety, reducing costs, and improving tunnel visual inspection flow efficiency.

Results of lighting recognition in the tunnel

Results of lighting recognition in the tunnel

Cite this article as:
Y. Moko, Y. Hiruma, T. Hayakawa, Y. Ke, Y. Onishi, and M. Ishikawa, “Vehicle Self-Position Estimation Using Lighting Recognition in Expressway Tunnel for Visual Inspection Flow,” J. Robot. Mechatron., Vol.36 No.3, pp. 746-757, 2024.
Data files:
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