Toward a Swarm of Inexpensive Multimodal Sensor Systems for Autonomous and Quantitative Condition Assessment of Roads
Published in Transportation Research Board 97th Annual Meeting, 2018
Current manual road condition assessment procedures are time consuming and laborious. On the other hand, state-of-the-art commercial data collection approaches are expensive although the data analysis tasks are not fully automated. Due to these limitations, a section of a road is assessed once a year or once every two years. Since insufficient inspection is an important contributor to the poor condition of roads, this study presents the development, evaluation, and field application of a novel, relatively inexpensive, vision-based sensor system employing commercially available off-the-shelf devices that can be mounted on several vehicles and hence collect data from a section of the road more often. In addition, an approach is proposed to interpret the data, and detect, quantify and localize defects autonomously. The proposed hardware-software package system is ideal to be used for crowdsourcing as a complement to the existing commercial road assessment vehicles and reduce the operation cost.
Recommended citation: Chen, Yulu, Mohammad R. Jahanshahi, Preetham Manjunatha, Sami F. Masri, and Burcin Becerik-Gerber. Toward a Swarm of Inexpensive Multimodal Sensor Systems for Autonomous and Quantitative Condition Assessment of Roads. No. 18-03394. 2018.
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