A path planning and path-following control framework for a general 2-trailer with a car-like tractor

TL;DR

This paper introduces a comprehensive path planning and control framework for a complex 2-trailer vehicle with a car-like tractor, enabling automatic maneuvering in challenging parking and obstacle scenarios, validated through simulations and real-world tests.

Contribution

It develops a lattice-based path planner and a trailer-aware path-following controller with a nonlinear observer, all operable using only tractor-mounted sensors, for the first time in this context.

Findings

Successfully planned collision-free paths in complex environments.

Achieved stable path following with minimal lateral and angular errors.

Validated framework effectiveness through real-world experiments.

Abstract

Maneuvering a general 2-trailer with a car-like tractor in backward motion is a task that requires significant skill to master and is unarguably one of the most complicated tasks a truck driver has to perform. This paper presents a path planning and path-following control solution that can be used to automatically plan and execute difficult parking and obstacle avoidance maneuvers by combining backward and forward motion. A lattice-based path planning framework is developed in order to generate kinematically feasible and collision-free paths and a path-following controller is designed to stabilize the lateral and angular path-following error states during path execution. To estimate the vehicle state needed for control, a nonlinear observer is developed which only utilizes information from sensors that are mounted on the car-like tractor, making the system independent of additional trailer sensors. The proposed path planning and path-following control framework is implemented on a full-scale test vehicle and results from simulations and real-world experiments are presented.