The social infrastructure, including roads and bridges built during period of rapid economic growth in Japan, is now aging, and there is a need to strategically maintain and renew the social infrastructure that is aging. On the other hand, road maintenance in rural areas is facing serious problems such as reduced budgets for maintenance and a shortage of engineers due to the declining birthrate and aging population. Therefore, it is difficult to visually inspect all roads in rural areas by maintenance engineers, and a system to automatically detect road damage is required. This paper reports practical improvements to the road damage model using YOLOv5, an object detection model capable of real-time operation, focusing on road image features.

In order to detect snow and ice on a road surface, the microwave measurement method of dielectric constants are presented. And some examples of measurements for artificial and natural snow and ice using the method are introduced. The results show reasonable estimations of the dielectric constants, and they indicate that the method could be utilized for the snow and ice detection.