Emergency Lane Change Trajectory Planning for High Center of Gravity Vehicles using Time-Domain Dual Connecting Points Optimization

This study proposes a computationally efficient trajectory planning algorithm for emergency collision avoidance in high center of gravity (CoG) vehicles, building upon the previously developed Dual Connecting Points Optimization (DCPO) framework. While existing methods often suffer from computational inefficiency or limited avoidance performance, the DCPO approach effectively utilizes lateral acceleration up to the rollover threshold, enabling safe and responsive maneuvers for high CoG vehicles. By employing exponential lateral acceleration profiles and only two optimization variables, the algorithm achieves both rapid lane changes and real-time feasibility. This work enhances the prior DCPO formulation by redesigning the cost function to adaptively adjust trajectories based on obstacle proximity-producing smoother paths for moderate threats and sharper maneuvers for imminent ones. Simulation results confirm the proposed method's effectiveness across diverse emergency scenarios.