Automated Localization and ADA Functional Condition Assessment of Curb Ramps using Mobile Lidar

PI: Yelda Turkan (OSU), yelda.turkan@oregonstate.edu, ORCID: 0000-0002-3224-5462

Co PIs: none

AMOUNT & MATCH: $40,000 from PacTrans; $40,000 Match

PERFORMANCE PERIOD: 8/16/2020 – 8/15/2022

STATUS: Active

CATEGORIES: ADA, Curb Ramps, Lidar

RESEARCH PROJECT HOT SHEET:

UTC PROJECT DOCUMENTATION:

FINAL PROJECT REPORT: will be available once completed

PROJECT DATA: will be available once completed

DESCRIPTION: This project will create a novel framework for curb ramp ADA compliance assessment using 3D point cloud data to extract curb ramps and sidewalks in addition to the road surface. Curb ramps will be extracted from at least 100 intersections from mobile lidar datasets to produce both training and validation dataset identifying their key geometric characteristics. The curb ramp detection and assessment results obtained will be added to a geodatabase in GIS for easier access to the results and improved data management. The corresponding field survey data will be used as ground truth to compare against for further evaluating the effectiveness and accuracy of the proposed methods. The anticipated outcomes of this research will be to A) develop an algorithm that enables to automatically identify curb ramps and assess their ADA compliance in mobile lidar data; B) provide a guideline on the accuracy and reliability for utilizing mobile lidar data in curb ramp assessment; C) increase the adoption of mobile lidar technology for transportation projects. All of these factors should help assist in maintaining U.S. transportation network in a state of good repair, thus help ensure its safety, mobility and inclusiveness for persons with disabilities.

DELIVERABLE DUE DATE DATE RECEIVED
Research Project Progress Report #1 4/10/2021
Research Project Progress Report #2 10/10/2021
Research Project Progress Report #3 4/10/2022
Draft Report 6/15/2022
Final Project Report 8/15/2022