Model Predictive Path-Planning Controller With Potential Function for Emergency Collision Avoidance on Highway Driving

Existing potential functions (PFs) utilized in autonomous vehicles mainly focus on solving the path-planning problems some conventional driving scenarios; thus, their performance may not be satisfactory context of emergency obstacle avoidance. Therefore, we propose a novel model predictive controller (MPPC) combined with PFs to handle complex traffic scenarios (e.g., avoidance when sudden accident occurs). Specifically, enhance safety PFs, developed an MPPC case sigmoid-based safe passage embedded MPC constraints (SPMPC) specific triggering analysis algorithm monitoring emergencies. The presented PF-SPMPC was compiled comparative simulation study using MATLAB/Simulink and CarSim. outperformed latest PF-MPC approach eliminate severe tire oscillations guarantee handling scenario.