用车载传感器与摄像头实时检测路面坑洼，助力道路智能管理
Real-time pothole detection with onboard sensors and camera on vehicles
- 融合车载传感器与摄像头数据，用SVM模型实现实时坑洼识别
- 在2公里路段上检测到26个坑洼，准确率达98.1%
- 适合交通运维、智慧公路系统开发者参考
道路状况对日常通勤至关重要。随着车辆数量逐年增加，需频繁获取道路状态信息以保障交通顺畅。微小裂缝可能因温差和车辆碾压演变为大坑洼。本文提出利用车辆车载传感器与摄像头实现实时坑洼检测，为大规模道路管理提供数据支持。采用SVM分类器，在一条长约2公里、含26个坑洼的本地道路上取得98.1%的检测准确率。代码已开源：https://github.com/aswathselvam/Potholes。
原文摘要 · Abstract (English)
Road conditions play an important role in our everyday commute. With the proliferating number of vehicles on the road each year, it has become necessary to access the road conditions very frequently, this would ensure that the traffic also flows smoothly. Even the smallest crack in the road could be easily be chipped into a large pothole due to changing surface temperatures of the road and from the force of vehicles riding over it. In this paper, we have addressed how we could better identify these potholes in realtime with the help of onboard sensors in vehicles so that the data could be useful for analysis and better management of potholes on a large scale. For the implementation, we used an SVM classifier to detect potholes, we achieved 98.1% accuracy based on data collected from a local road for about 2 km which had 26 potholes distributed along the road. Code is available at: https://github.com/aswathselvam/Potholes
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