High-Speed Localization Estimation Method Using Lighting Recognition in Tunnels

Abstract

This study proposes a vision-based high-speed localization estimation method for location based visual inspection of specific cracks in tunnels on Japanese expressways where global navigation satellite systems are not applicable. The method relies on recognizing lighting facilities installed in tunnels by using random sample consensus (RANSAC), enabling stable and accurate localization estimation in the horizontal direction. To correspond with traveling at high speed, single instruction/multiple data (SIMD) conversion realized 8 times faster than conventional image processing. The evaluation experimental results on expressway demonstrate that the proposed method achieves a maximum error of 31 mm in estimating lighting facilities position with an average error of 16 mm. The theoretical value derived from tunnel completion drawings has a maximum difference of 177 mm from the total value by this method, indicating that the results of accurate on-site measurements should be prioritized over completion drawings. In conclusion, the proposed method has considerable potential for practical application in tunnel inspection and maintenance.