VEMI Lab researchers earn federal prize, invite to White House for software that makes self-driving cars more accessible - - University of Maine
Summary
To provide the functionality, researchers utilized GPS, LiDAR, Gyroscope and Accelerometer technology; real-time computer vision via the smartphone camera; machine learning; artificial intelligence and other software. When the vehicle arrives, AVA will guide the user to it using the camera and augmented reality (AR), which provides an overlay of the environment by superimposing high-contrast lines over the image on the smartphone screen to highlight the path, and verbal guidance such as compass directions, street names, addresses, nearby landmarks and other indicators. The software also will pinpoint environmental hazards, including low-contrast curbs, traffic cones and overhanging obstructions like branches and guy wires, by emphasizing them with contrasting lines and vibrations when users approach them. “Autonomous vehicles have the potential to be a truly game changing, disruptive technology for improving accessible, inclusive transportation for people with visual impairments and older adults,” says Giudice, also a UMaine professor of spatial computing and congenitally blind. Our initial research and development of AVA in the first IDC semi-finalist round has made significant progress in addressing current limitations, but I am most excited about our future development made possible by this finalist IDC prize, which will lead to a robust, end-to-end inclusive travel solution that integrates with other accessible apps and platforms.” The AVA project builds on a National Science Foundation grant led by Giudice and Corey on trust building and human-vehicle collaboration with autonomous vehicles, as well as a seed grant-funded, joint effort between UMaine and Northeastern University to improve accessibility, safety and situational awareness within self-driving vehicles.