This paper proposes an integrated framework for decision-making, trajectory planning, and controlling in support of intelligent vehicles, where driving ethics and road regulations are explicitly considered. First, by simulating various scenarios that a driver may encounter in everyday driving, different decision-making plans are formulated to ensure compliance with traffic rules and driving ethics. Second, through parameter optimization, a trajectory planning strategy based on integrated graph search and quadratic programming is developed, providing a safe, feasible, and passenger-comfort-oriented reference trajectory. Finally, a combined PID-MPC approach is employed to enhance trajectory tracking control accuracy. Simulation results in PreScan environment demonstrate that the proposed scheme effectively handles various scenarios in regulated driving environments, providing a safe and effective automated driving solution.

Autonomous vehicles,obstacle avoidance,model predictive control,trajectory planning,tracking control