Path planning and trajectory tracking control in current automatic parking systems are usually independent of each other, resulting in more complex computations. Therefore, this paper proposes an integrated automatic parking path planning and trajectory tracking optimization method based on Multi-stage Nonlinear Model Predictive Control (MSNMPC). Each phase defined by the MSNMPC controller has specific cost and constraint functions that depend only on the vehicle state and control inputs of that phase to satisfy the constraints of all phases of the parking process. In addition, the method integrates path planning and tracking control into a single optimization problem, which is solved online to achieve integrated parking control. By comparing with the hierarchical control architecture based on MPC and RRT*, the proposed integrated parking scheme has good flexibility and tracking performance, and the parking elapsed time is reduced by 10.47%.

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Integrated Automatic Parking Path Planning and Trajectory Tracking Optimization Method

  • Changhao Piao,
  • Yongkang Su,
  • Junren Shi

摘要

Path planning and trajectory tracking control in current automatic parking systems are usually independent of each other, resulting in more complex computations. Therefore, this paper proposes an integrated automatic parking path planning and trajectory tracking optimization method based on Multi-stage Nonlinear Model Predictive Control (MSNMPC). Each phase defined by the MSNMPC controller has specific cost and constraint functions that depend only on the vehicle state and control inputs of that phase to satisfy the constraints of all phases of the parking process. In addition, the method integrates path planning and tracking control into a single optimization problem, which is solved online to achieve integrated parking control. By comparing with the hierarchical control architecture based on MPC and RRT*, the proposed integrated parking scheme has good flexibility and tracking performance, and the parking elapsed time is reduced by 10.47%.