USING PUBLIC DATA TO OPTIMIZE AUTONOMOUS VEHICLE HD MAPPING

CARMERA is an autonomous vehicle (AV) high-definition (HD) mapping company that specializes in roadway change management. It is critical for public safety that HD maps have granular and up-to-date information on road features to anticipate the road ahead. CARMERA enlisted a Capstone team to review data sharing policies at the federal, state, and city levels and help identify connections between roadway changes collected by cities and private AV firms. The team utilized a spatial regression model to examine whether public datasets can help predict the observed roadway changes from CARMERA’s pilot program in San Francisco. Its preliminary findings indicate an opportunity for the optimization of private company data gathering based on public datasets. The team produced a final report detailing ways to use public data to inform policies and recommendations for cities and private AV firms with the shared goal of coordinated and efficient capture of roadway changes on HD maps.