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Multimodal Sensor Fusion for Autonomous Data Acquisition of Road Surfaces

In this study the development, evaluation, calibration, and field application of a novel, relatively inexpensive, vision-based sensor system employing commercially available off-the- shelf devices, for enabling the autonomous data acquisition of road surface conditions are performed. It is shown that the proposed multi-sensor system, by capitalizing on powerful data-fusion approaches of the type developed in this study, can provide a robust cost-effective road surface monitoring system with sufficient accuracy to satisfy typical maintenance needs, in regard to the detection, localization and quantification of potholes and similar qualitative deterioration features where the measurements are acquired via a vehicle moving at normal speeds on typical city streets. The proposed system is ideal to be used for crowdsourcing where several vehicles would be equipped with this cost-effective system for more frequent data collection of road surfaces.

Related Publication

Yulu Chen, Mohammad R. Jahanshahi, Preetham A. Manjunatha, Mohamed Abdelbarr, WeiPhang Gan, John P. Caffrey, Sami F. Masri and Burcin Becerik-Gerber, (2016), "Inexpensive multimodal sensor fusion system for autonomous data acquisition of road surface conditions," IEEE Sensors Journal, in press, Vol. 16, No. 21, DOI: 10.1109/JSEN.2016.2602871.