Abstract On-time maintenance of deteriorated pavement is a crucial step toward minimizing its life cycle costs. Maintenance and rehabilitation actions are planned based on pavement condition data including road roughness. The condition of low volume roads is not monitored frequently due to the high cost of data collection and their less priority. However, road users traverse them widely. The objective of this study is to develop an inexpensive data acquisition system based on the use of a Sharp IR-based sensor and an accelerometer to capture pavement profile and estimate its roughness index with adequate accuracy for low volume roads. Design of study, data management, data acquisition, and data analysis are the steps of this research. The results demonstrate that the developed system is able to measure pavement roughness of uneven roads with 87.4% accuracy at 30 km/h speed. Therefore, it can be a good alternative for expensive data collection vehicles.

中文翻译：

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低流量道路的低成本红外路面粗糙度数据采集

摘要 老化路面的按时养护是降低其生命周期成本的关键步骤。根据路面状况数据（包括路面粗糙度）来计划维护和修复行动。由于数据收集成本高且优先级较低，因此不经常监测低流量道路的状况。然而，道路使用者广泛地穿越它们。本研究的目的是开发一种廉价的数据采集系统，该系统基于使用基于 Sharp IR 的传感器和加速度计来捕获路面轮廓并以足够的精度估计其粗糙度指数，适用于低流量道路。研究设计、数据管理、数据采集和数据分析是本研究的步骤。结果表明，开发的系统能够测量不平坦道路的路面粗糙度为 87。在 30 公里/小时的速度下精度为 4%。因此，它可以成为昂贵的数据收集工具的良好替代品。