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JRM Vol.34 No.5 pp. 997-1010
doi: 10.20965/jrm.2022.p0997
(2022)

Paper:

Tunnel Lining Surface Monitoring System Deployable at Maximum Vehicle Speed of 100 km/h Using View Angle Compensation Based on Self-Localization Using White Line Recognition

Tomohiko Hayakawa*, Yushi Moko*, Kenta Morishita**, Yuka Hiruma*, and Masatoshi Ishikawa*,***

*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-shi, Aichi 460-0003, Japan

***Tokyo University of Science
1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-8601, Japan

Received:
May 13, 2022
Accepted:
July 14, 2022
Published:
October 20, 2022
Keywords:
self-localization, white line recognition, view angle compensation, motion blur correction, in-vehicle monitoring system
Abstract
Tunnel Lining Surface Monitoring System Deployable at Maximum Vehicle Speed of 100 km/h Using View Angle Compensation Based on Self-Localization Using White Line Recognition

Results of white line recognition in the tunnel

Vehicle-mounted inspection systems have been developed to perform daily inspections of tunnel lining. However, it is difficult to continuously scan images at the desired target angle with the camera’s limited visual field because the vehicle does not always maintain the same position in the car lane while it runs. In this study, we propose a calibration-free optical self-localization method based on white line recognition, which can stabilize the scanning angle and thus enable the scanning of the entire tunnel lining surface. Self-localization based on the present method has a processing time of 27.3 ms, making it valid for real-time view angle compensation inside tunnels, where global positioning systems cannot operate. It is robust against changes in brightness at tunnel entrances and exits and capable of dealing with car lanes with dotted lines and regular white lines. We confirmed that it is possible to perform self-localization with 97.4% accuracy using the scanned data of white lines captured while the vehicle is running. When this self-localization was combined with an inspection system capable of motion blur correction, we were able to sequentially scan the tunnel lining surface at a stable camera angle at high speed, and it was shown that the acquired images could be stitched together to produce an expansion image that can be used for inspection.

Cite this article as:
T. Hayakawa, Y. Moko, K. Morishita, Y. Hiruma, and M. Ishikawa, “Tunnel Lining Surface Monitoring System Deployable at Maximum Vehicle Speed of 100 km/h Using View Angle Compensation Based on Self-Localization Using White Line Recognition,” J. Robot. Mechatron., Vol.34, No.5, pp. 997-1010, 2022.
Data files:
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Last updated on Dec. 01, 2022