Lin Wins U.S. DOT Inclusive Design Challenge
Assistant Professor Xue “Shelley” Lin, electrical and computer engineering, in collaboration with University of Maine Professor Nicholas Giudice, won the U.S. Department of Transportation’s (DOT) Inclusive Design Challenge for their project “Autonomous Vehicle Assistant (Ava): Ride-Hailing and Localization for the Future of Accessible Mobility” and received a $300K Stage I cash prize and advanced to Stage II as a Semifinalist.
According to the DOT, an estimated 25.5 million Americans experience a travel-limiting disability that impacts their access to employment, medical care, and other activities of daily living. The current COVID-19 pandemic has further highlighted the critical need for vulnerable populations to have on-demand transportation services to access healthcare, pharmacies, grocery stores, and other essential services. Automated vehicles, particularly those designed to be operated exclusively by Level 4 and Level 5 Automated Driving Systems (ADS), hold great promise to enhance freedom of movement for these individuals.
The DOT’s Inclusive Design Challenge sought innovative, inclusive design features to enable people with physical, sensory, and cognitive disabilities to use automated vehicles, particularly ADS-dedicated vehicles (ADS-DV).
As a Stage I winner, Northeastern’s Lin and the project team will develop “Ava”, the Autonomous Vehicle Assistant, an innovative ride-hailing and localization smartphone application designed to seamlessly assist passengers with visual impairment and older adults during pre-journey planning, travel to pick-up locations, and vehicle entry. It will use innovative human-machine interfaces and technologies such as GPS and computer vision to help users find and ultimately arrive at an ADS-DV safely. The initial rollout of Ava’s training modules can be fully deployed and utilized via users’ existing smartphones, representing a cost-effective and timely solution to the problem of trust in automated vehicles.
The project builds upon a seed-grant funded joint project between Northeastern and the University of Maine to improve accessibility, safety, and situational awareness within the self-driving vehicle with a new model of human-AI vehicle interaction.