Principal Investigator: Yiheng Feng
In this work, we propose a framework that enables safe and secure human remote operation when AV systems require support due to the inherent limitations of ML models used. We develop an approach that can effectively detect and mitigate potentially malicious remote human operators, and satisfy the real-time requirements of remote operation despite possibly variable network conditions impacting the communication channel between the AV system and the remote operator. Our solution will be demonstrated on the Mcity 2.0 testbed as a means to validate the proposed design in realistic settings.
Other PIs: Z. Morley Mao, University of Michigan
Keywords: autonomous vehicles, remote operation, Safety, security