AI RESEARCH
Beyond Crash: Hijacking Your Autonomous Vehicle for Fun and Profit
arXiv CS.LG
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ArXi:2602.07249v2 Announce Type: replace-cross Autonomous Vehicles (AVs), especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical environments, understanding their robustness in an adversarial environment is an important research problem. Prior physical adversarial attacks on vision-based autonomous vehicles predominantly target immediate safety failures (e.g., a crash, a traffic-rule violation, or a transient lane departure) by inducing a short-lived perception or control error.