A Rapid Iterative Trajectory Planning Method for Automated Parking through Differential Flatness

2025-08-23

AI Summary

In automated parking, path-velocity decomposition (PVD)-based trajectory planning faces a trade-off between real-time performance and collision-free accuracy, while suffering from insufficient control feasibility at gear-shift points (GSPs). This paper proposes a fast iterative PVD planning method: (1) a collision-avoidance framework is constructed leveraging differential flatness to ensure dynamical consistency and path curvature continuity; (2) terminal smoothing constraints are imposed at GSPs to enhance transient control feasibility during gear shifts. The method integrates the PVD architecture, nonlinear optimization, and terminal constraints into a unified planning–control framework implemented on ROS. Simulation results demonstrate low computational latency and small tracking errors. Real-vehicle experiments validate its effectiveness and engineering applicability.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Intelligent Robots: Motion and Path Planning
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

As autonomous driving continues to advance, automated parking is becoming increasingly essential. However, significant challenges arise when implementing path velocity decomposition (PVD) trajectory planning for automated parking. The primary challenge is ensuring rapid and precise collision-free trajectory planning, which is often in conflict. The secondary challenge involves maintaining sufficient control feasibility of the planned trajectory, particularly at gear shifting points (GSP). This paper proposes a PVD-based rapid iterative trajectory planning (RITP) method to solve the above challenges. The proposed method effectively balances the necessity for time efficiency and precise collision avoidance through a novel collision avoidance framework. Moreover, it enhances the overall control feasibility of the planned trajectory by incorporating the vehicle kinematics model and including terminal smoothing constraints (TSC) at GSP during path planning. Specifically, the proposed method leverages differential flatness to ensure the planned path adheres to the vehicle kinematic model. Additionally, it utilizes TSC to maintain curvature continuity at GSP, thereby enhancing the control feasibility of the overall trajectory. The simulation results demonstrate superior time efficiency and tracking errors compared to model-integrated and other iteration-based trajectory planning methods. In the real-world experiment, the proposed method was implemented and validated on a ROS-based vehicle, demonstrating the applicability of the RITP method for real vehicles.

Problem

• Ensuring rapid and precise collision-free automated parking trajectory planning
• Maintaining control feasibility at gear shifting points during parking
• Balancing time efficiency with kinematic constraints for vehicle trajectories

Innovation

• Differential flatness for kinematic adherence
• Terminal smoothing constraints for curvature continuity
• Rapid iterative planning with collision avoidance