The New Safety Net for Human-Assisted AVs

Researchers from Purdue and the University of Michigan are tackling one of autonomous driving’s toughest challenges: keeping remotely operated AVs safe when human intervention is needed. Their work exposes how latency, operator error, and cyberattacks can quickly turn teleoperation risky—and introduces a safety-check system that detects dangerous maneuvers and overrides them before a crash occurs. By adding collaborative sensing from nearby vehicles and infrastructure, they also show how to expand visibility, strengthen communication reliability, and cut latency. The result is a promising hybrid framework that makes remote AV operation more resilient, more aware, and dramatically safer.