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This study used terrestrial laser scanner and open source processing algorithms to develop an approach to automate the evaluation of transportation infrastructure in public rights of way. We estimated compliance or noncompliance of specific roadway features with the design standards adopted by the US Access Board and required under the Americans with Disabilities Act (ADA) such as minimum sidewalk width, maximum cross slopes and presence/absence of pedestrian connectivity automatically with extracting roadway features from point cloud data (PCD). We then compared the accuracy and cost efficiency of the automated with more conventional evaluative techniques to identify the potential risks, gains and the overall efficacy of these approaches. The collected raw data were processed through a sequential process including simplification, optimization, segmentation, and road feature categorization. Finally, the road elements were detected as the road feature objects. By developing a more thorough assessment process, this research provided communities with the information necessary to strategically plan transportation infrastructure improvements for people with limited mobility.

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TRCLC 16-01