Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Braking

Abstract-- Automatic Emergency Braking (AEB) systems are a crucial component in ensuring the safety of passengers in autonomous vehicles. Through extensive experimentation, we have validated the effectiveness of our method. The Autonomous Emergency Braking (AEB) system is a critical safety feature in autonomous vehicles, designed to information, making it impossible to predict an impending mitigate or prevent collisions by automatically activating the collision. Similarly, while end-to-end methods process raw brakes when a potential collision is detected [1]. Numerous sensory data, they often lack the reasoning capacity to studies [1]-[5] have demonstrated the effectiveness of AEB interpret indirect cues--such as the illuminated brake lights systems, with reductions in rear-end collisions ranging from on the vehicle to the left of the ego vehicle--that may 25% to 50%.