Center for Transportation Studies, University of Minnesota
Collecting information about the roadway infrastructure is a task that DOTs at all governmental levels need to accomplish. One way to increase the operational efficiency of these efforts is to use a relatively inexpensive mobile data collection platform that acquires information that is general enough to serve multiple purposes. The design and evaluation of one such platform that costs roughly $40,000 is described. It primarily consists of a differential GPS receiver providing vehicle location, and a LIDAR scanner that generates geometric profiles of the area between the vehicle and just beyond the road’s edge. The vehicle collects data along the road by driving it in both directions. The system post-processes the data to automate feature extraction. For roads with simple geometry such as two-lane, undivided highways, the road’s
centerline can be calculated by finding the midline between the vehicle’s paths from each direction of travel. Algorithms process the LIDAR scans to automatically detect the presence of curbs and guardrails, which is then combined with location information to yield the position of these features in world coordinates. The centerline calculation was determined to be accurate to within 6 cm in areas where its use was applicable. Curbs and guardrails were generally detected with an accuracy of better than 10 cm. The results demonstrate that it is feasible to use a relatively inexpensive mobile data collection system to acquire road centerline and roadside features such as curbs and guardrails.
Davis, Brian; Donath, Max.
Development of a Sensor Platform for Roadway Mapping: Part A - Road Centerline and Asset Management.
Center for Transportation Studies, University of Minnesota.
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