Harnessing the Automotive Infoverse

Abstract:

Until now, the "cyber" component of automobiles has consisted of control algorithms and associated software for vehicular subsystems designed to achieve one or more performance, efficiency, reliability, comfort, or safety (PERCS) goals, primarily based on short-term intrinsic vehicle sensor data. However, there exist many extrinsic factors that can affect the degree to which these goals can be achieved. These factors can be determined from: longer-term traces of in-built sensor data that can be abstracted as triplines, socialized versions of these that are shared amongst vehicle users, and online databases. These three sources of information collectively constitute the automotive infoverse. This project harnesses this automotive infoverse to achieve these goals through high-confidence vehicle tuning and driver feedback decisions. It can have significant societal impact by reducing carbon emissions and improving vehicular safety, can spur innovation in tuning methods and encourage researchers to experiment with this class of cyber-physical systems.