|Title||Automated sidewalk assessment method for americans with disabilities act compliance using three-dimensional mobile lidar|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Ai C, Tsai Y|
|Journal||Journal of Transportation Research Record|
Sidewalk is an indispensable infrastructure for pedestrians, especially wheelchair users. Wheelchair users rely on quality sidewalks to facilitate safe and uninterrupted trips in their everyday lives. Transportation agencies are required to evaluate the regulatory compliance of the Americans with Disabilities Act (ADA), and are responsible for timely maintenance of inadequate sidewalks. However, these timely evaluation and maintenance activities are usually lacking due to the labor-intensive and cost-prohibitive data collection process in the current practice. There is an urgent need for an efficient and reliable sidewalk assessment method for the ADA compliance. This paper aims at addressing such a need by proposing an automated sidewalk assessment method using 3-D mobile light detection and ranging (LiDAR) and image processing. The presences of sidewalks and curb ramps are extracted first using video log image and LiDAR point cloud. Then, the corresponding key features regulated by the ADA, including sidewalk width, cross slope, grade, and curb ramp slope, are automatically measured. Comparing with the manual ground truth from field survey, the experimental tests conducted on Georgia Tech campus at Atlanta, Georgia show accurate measurement results of the key features for sidewalk and curb ramps. A case study is then conducted to demonstrate that the proposed method can support transportation agencies a convenient and cost-effective means for ADA compliance assessment by integrating the accurately extracted sidewalk location and measurement information.