Project: #296 Improving Mobility of Low Vision People with Super-Reality Glasses Progress Report - Reporting Period Ending: Sept. 30, 2019 Principal Investigator: Yang Cai Status: Active Start Date: July 1, 2019 End Date: June 30, 2020 Research Type: Advanced Grant Type: Research Grant Program: FAST Act - Mobility National (2016 - 2022) Grant Cycle: 2019 Mobility21 UTC Progress Report (Last Updated: Oct. 2, 2019, 7:13 a.m.) % Project Completed to Date: 25 % Grant Award Expended: 0 % Match Expended & Document: 0 USDOT Requirements Accomplishments The major goal of the project is to develop a super-reality glasses prototype for low-vision users to improve their mobility, including sign detection, edge enhancement, and pedestrian detection. During this period, we have surveyed literature about existing technology and potential XR development platforms. We have prototyped a LIDAR-based heads-up pavement bumper (uneven sidewalk) detection algorithm and conducted preliminary experiments in the lab space. We provided opportunities for training a professional engineer and an ECE student. We plan to submit two papers and a proposal for hosting the special session on IEEE I2MTC in 2020. For the next reporting period, we will develop computer vision algorithms for sign detection and edge enhancement. Impacts This project will have an impact on improving mobility of low-vision users in traversing urban environments to reach public transit systems. It will increase the body of scientific knowledge about aging vision, pattern recognition in mobile conditions, and sensory fusion models. Other We have developed a new method to fuse multi-sensor information for detecting user's activities and pavement bumpers. We will file the Invention Disclosure to CMU Technology Transfer office and follow up with Provisional Patent. Outcomes New Partners Nothing new to report Issues Nothing new to report