Trajectory Optimization and Collision Avoidance for the Detect and Save System

Recent advancements in autonomous driving and advanced driver-assistance systems (ADAS) have made significant progress in improving road safety. This study introduces an Emergency Lane Change and Parking Algorithm designed to autonomously maneuver a vehicle to the emergency lane and bring it to a controlled stop upon detecting driver fatigue or drowsiness. The system integrates advanced trajectory planning and collision avoidance algorithms to ensure safe lane transitions even under complex traffic conditions. The proposed approach was validated in the CARLA simulation environment, demonstrating robust performance across various speeds and traffic scenarios. This system provides a comprehensive solution that effectively manages emergency lane transitions while enhancing safety and supporting compliance with traffic regulations.