Speaking of road maintenance, the preventive maintenance strategy is preferable for most governments. Many governments possess special vehicles that can accurately detect and classify many types of road distresses. By running these vehicles frequently, small road distresses will be detected before growing into the big ones. However, because running these huge and expensive vehicles is not easy, in practical, it usually ends up with infrequent road inspection regardless of having automatic road inspection vehicles. In this paper, we focus on investigating and developing an automatic and nondestructive visual inspection system whose setup and usage are designed by considering the context of drivers, driving styles, and road conditions in Bangkok, the capital city of Thailand. Our proposal includes a workflow diagram of a vision-based road inspection system that is capable of detecting, classifying, tracking, measuring, and pricing road distresses. As for the proof-of-concept, our current system focuses on detecting one specific type of road distresses called pothole, using only one onboard in-car camera. Experimental results reveal that the context of Bangkok introduces many nontrivial challenges for vision-based analysis systems where maintaining both accuracy and ease of use altogether may not be easy.
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