LiDAR SecurityExpert
TACTIC: Temporal and Context-Aware LLM Tactical Planning for Roadside LiDAR Attacks
This preprint presents TACTIC, a scene-aware framework that uses a multimodal large language model and roadside perception to choose and tune physical LiDAR attacks in dynamic traffic. In 280 randomized CARLA trials, the full system caused collisions in 100% of evaluation cases, versus 35% for a fixed rule and 60% for random attack selection. The result shows attack success depends on scene context, which matters for evaluating LiDAR safety failures in autonomous driving.