Path Planning and Robust Path Tracking Control of an Automated Parallel Parking Maneuver
Xincheng Cao, Levent Guvenc

TL;DR
This paper develops a path planning and control system for automated parallel parking, focusing on short-horizon maneuvers with smooth path construction and robust control to improve repeatability and safety.
Contribution
It introduces a segmented polynomial path planning method and a robust PID control system tailored for low-speed, short-horizon parking maneuvers with direction reversal.
Findings
Simulation shows improved performance over traditional PID control.
Path curvature is guaranteed smooth through polynomial optimization.
The control system effectively handles disturbances and ensures smooth stopping.
Abstract
Self driving vehicles should be able to perform parallel parking or a similar maneuver successfully. With this motivation, the S shaped maneuverability test of the Ohio driver license examination is chosen here for automatic execution by a self driving vehicle with drive by wire capability and longitudinal and lateral controls. The Ohio maneuverability test requires the driver to start within an area enclosed by four pylons and the driver is asked to go to the left of the fifth pylon directly in front of the vehicle in a smooth and continuous manner while ending in a parallel direction to the initial one. The driver is then asked to go backwards to the starting location of the vehicle without stopping the vehicle or hitting the pylons. As a self driving vehicle should do a much better job repeatably than a driver, a high order polynomial path model is built along with speed profiling to…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Control and Dynamics of Mobile Robots · Vehicle Dynamics and Control Systems
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
