Grant supports Buckeyes' efforts to enable automated driving in a smart city
Low speed autonomous shuttles could provide a reliable, safe solution to the first mile/last mile problem in transportation—the challenge commuters face in reaching a public transit station to begin their commute and then get from the station to their ultimate destination. But a unified and scalable architecture must first be developed before such shuttles could be deployed widely and cost-effectively.
Ohio State engineering researchers received a two-year $200,000 CPS EAGER grant from the National Science Foundation to develop the Smart Shuttle, a unified, scalable and replicable software, hardware, control and decision making architecture that will enable automated driving in a smart city.
Levent Guvenc, professor of mechanical and aerospace engineering with a joint appointment in electrical and computer engineering, leads the project together with Bilin Aksun Guvenc, visiting professor with the Center for Automotive Research, and mechanical and aerospace engineering, and Keith Redmill, assistant clinical professor of electrical and computer engineering. Initial project work is taking place in the Automated Driving Lab of the Center for Automotive Research.
The two-seater Dash EV electric vehicle, donated by Innova UEV, is one of the vehicles that will be utilized in the project.
The project will be deployed as part of Smart Columbus, an unprecedented $140 million program to transform central Ohio into the nation’s premier transportation innovation region.
“The idea of Smart Shuttle is to build a unified, replicable and scalable architecture for connected and automated driving that can be used by different vendors and can be replicated in different deployment sites and different cities,” explained Levent Guvenc.
The results will be demonstrated using a proof-of-concept demo deployment in Easton Town Center—a 30+ acre outdoor shopping and dining area. Researchers will use a two-seat autonomous electric vehicle for initial research and testing prior to deploying larger autonomous shuttles.
Once developed, the generic, unified and scalable architecture for low speed automated driving shuttles will be shared with other interested researchers.