Real-Time Near-Optimal Path And Maneuver Planning In Automatic Parking Using A Simultaneous Dynamic Optimization Approach

We propose a real-time near-optimal motion and trajectory planner using an interior-point method (IPM) based simultaneous dynamic optimization approach applicable to automatic parallel parking. Partitioning an automatic parking zone into two areas with and without inequality constraints drastically improves the convergence efficiency of the IPM-based simultaneous dynamic optimization of nonlinear programs while retaining the accuracy and stability of simulation for optimization. An optimal ready-to-reverse point (RRP), from where backward moving parking maneuver starts, is provided based on the cost function of the tracking time and additional delayed time of gear shifts caused by multiple maneuvers. The stability and accuracy of the proposed method was verified through simulation using AMPL with an IPOPT solver.