MECHANICAL ENGINEERING PHD THESIS DEFENSE BY AHMET CANBERK MANAV



Title: Autonomous Truck-Trailer Parking – Path Planning and Path Tracking Control

Speaker: Ahmet Canberk Manav

Time: August 2, 2022, 10:00

Place: Online Meeting via Zoom

Thesis Committee Members:

Prof. Dr. İsmail Lazoğlu (Advisor, Koç University)

Prof. Dr. Metin Türkay (Koç University)

Assoc. Prof. Arif Karabeyoğlu (Koç University)

Prof. Dr. Hakan Temeltaş (İstanbul Technical University)

Prof. Dr. Erdinç Altuğ (İstanbul Technical University)

Abstract:

Maneuvering a truck-trailer system while docking is extremely challenging. This study aims to alleviate this problem by presenting a novel cascade path planning framework and an enhanced path-following control framework for autonomous semi-trailer docking. In the proposed system, the cascade path planning framework generates kinematically feasible and drivable maneuvers for trailer parking and the path-following control framework introduces adaptive controllers that utilize gain scheduling for forward and reverse path-following tasks in docking maneuvers to increase the robustness and path-following performance.

In the cascade path planning approach, a realistic and deterministic parking behavior model, iterative analytical method (IAM), is proposed and combined with an enhanced Closed-Loop Rapidly Exploring Random Tree (CL-RRT) approach. Cascade path planning approach combining CL-RRT with IAM mimicking real-world parking practice enables generation of both kinematically feasible and deterministic parking maneuvers with obstacle avoidance. For evaluation, different parking scenarios are generated and selected through a developed case generation tool. The proposed path planning approach is evaluated through MATLAB simulations for performance evaluation. The results achieved a noticeable success with a high rate of generated feasible maneuvers for truck-trailer parking.

In the proposed path following control framework, the system includes an improved pure pursuit controller with adaptive look-ahead distance for forward path following; a cascade controller of reverse pure pursuit, and a gain-scheduled linear-quadratic (LQ) control for reverse path-following. In the evaluation of the path-following performance of forward and reverse controllers, the closed-loop system of path-following controllers with the truck-trailer kinematic model is simulated in MATLAB/Simulink for various test cases, and the results are compared with those of other studies. Furthermore, different docking scenarios are generated via the cascade path planning algorithm for autonomous semitrailer docking. These are tested with a high degree semi-trailer model within the IPG TruckMaker simulation environment, and with a full truck-trailer vehicle in the test field. The results of both simulations and physical testing clearly demonstrate improvements in terms of the control problem formulation, i.e. the stabilized path-following is obtained with acceptable path-following errors.