  Recent studies reveal that Autonomous Vehicles (AVs) can be manipulated by
hidden backdoors, causing them to perform harmful actions when activated by
physical triggers. However, it is still unclear how these triggers can be
activated while adhering to traffic principles. Understanding this
vulnerability in a dynamic traffic environment is crucial. This work addresses
this gap by presenting physical trigger activation as a reachability problem of
controlled dynamic system. Our technique identifies security-critical areas in
traffic systems where trigger conditions for accidents can be reached, and
provides intended trajectories for how those conditions can be reached. Testing
on typical traffic scenarios showed the system can be successfully driven to
trigger conditions with near 100% activation rate. Our method benefits from
identifying AV vulnerability and enabling effective safety strategies.
