27 March 2015 Implementation of a multi-modal mobile sensor system for surface and subsurface assessment of roadways
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Abstract
There are more than 4 million miles of roads and 600,000 bridges in the United States alone. On-going investments are required to maintain the physical and operational quality of these assets to ensure public’s safety and prosperity of the economy. Planning efficient maintenance and repair (M&R) operations must be armed with a meticulous pavement inspection method that is non-disruptive, is affordable and requires minimum manual effort. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project developed a technology able to cost- effectively monitor the condition of roadway systems to plan for the right repairs, in the right place, at the right time. VOTERS technology consists of an affordable, lightweight package of multi-modal sensor systems including acoustic, optical, electromagnetic, and GPS sensors. Vehicles outfitted with this technology would be capable of collecting information on a variety of pavement-related characteristics at both surface and subsurface levels as they are driven. By correlating the sensors’ outputs with the positioning data collected in tight time synchronization, a GIS-based control center attaches a spatial component to all the sensors’ measurements and delivers multiple ratings of the pavement every meter. These spatially indexed ratings are then leveraged by VOTERS decision making modules to plan the optimum M&R operations and predict the future budget needs. In 2014, VOTERS inspection results were validated by comparing them to the outputs of recent professionally done condition surveys of a local engineering firm for 300 miles of Massachusetts roads. Success of the VOTERS project portrays rapid, intelligent, and comprehensive evaluation of tomorrow’s transportation infrastructure to increase public’s safety, vitalize the economy, and deter catastrophic failures.
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Ming Wang, Ralf Birken, Salar Shahini Shamsabadi, "Implementation of a multi-modal mobile sensor system for surface and subsurface assessment of roadways", Proc. SPIE 9436, Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2015, 943607 (27 March 2015); doi: 10.1117/12.2084852; https://doi.org/10.1117/12.2084852
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