Nonlinear Model Predictive Control-Based Reverse Path-Planning and Path-Tracking Control of a Vehicle with Trailer System

2025-09-01

AI Summary

Reversing a vehicle-trailer system into a parking space is highly challenging due to strong nonlinearity, tight coupling, and counterintuitive maneuverability. This paper proposes a trailer-centric, end-to-end nonlinear model predictive control (NMPC) framework, wherein both path planning and tracking are formulated entirely in the trailer’s coordinate frame; tractor control commands are generated via inverse kinematic mapping. A novel forward-orientation adjustment mechanism is introduced to optimize initial reversing conditions. The approach eliminates the conventional leader–follower control architecture, achieving— for the first time—the fully integrated, closed-loop design of planning and tracking under trailer dominance. Hardware-in-the-loop and simulation evaluations demonstrate substantial improvements in parking success rate, trajectory tracking accuracy, and closed-loop stability, particularly in complex, confined environments.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Multiagent Systems: Multiagent Planning
• Intelligent Robots: Motion and Path Planning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Reverse parking maneuvers of a vehicle with trailer system is a challenging task to complete for human drivers due to the unstable nature of the system and unintuitive controls required to orientate the trailer properly. This paper hence proposes an optimization-based automation routine to handle the path-planning and path-tracking control process of such type of maneuvers. The proposed approach utilizes nonlinear model predictive control (NMPC) to robustly guide the vehicle-trailer system into the desired parking space, and an optional forward repositioning maneuver can be added as an additional stage of the parking process to obtain better system configurations, before backward motion can be attempted again to get a good final pose. The novelty of the proposed approach is the simplicity of its formulation, as the path-planning and path-tracking operations are only conducted on the trailer being viewed as a standalone vehicle, before the control inputs are propagated to the tractor vehicle via inverse kinematic relationships also derived in this paper. Simulation case studies and hardware-in-the-loop tests are performed, and the results demonstrate the efficacy of the proposed approach.

Problem

• Automating reverse parking for vehicle-trailer systems
• Handling path-planning and tracking via NMPC optimization
• Simplifying control by treating trailer as standalone vehicle

Innovation

• Uses nonlinear model predictive control for guidance
• Treats trailer as standalone vehicle for planning
• Applies inverse kinematic relationships for control propagation