Computer vision in automated parking systems: Design, implementation and challenges
Markus Heimberger, Jonathan Horgan, Ciaran Hughes, John McDonald,, Senthil Yogamani

TL;DR
This paper discusses the design, implementation, and challenges of computer vision-based automated parking systems, emphasizing the importance of vision modules for robustness and safety in low-cost, real-world applications.
Contribution
It provides a comprehensive systemic view of a commercial automated parking system focusing on computer vision algorithms and their integration for practical deployment.
Findings
Camera systems are crucial for addressing parking use cases.
Vision modules like 3D reconstruction and detection enhance system robustness.
The paper is the first detailed systemic discussion of commercial automated parking.
Abstract
Automated driving is an active area of research in both industry and academia. Automated Parking, which is automated driving in a restricted scenario of parking with low speed manoeuvring, is a key enabling product for fully autonomous driving systems. It is also an important milestone from the perspective of a higher end system built from the previous generation driver assistance systems comprising of collision warning, pedestrian detection, etc. In this paper, we discuss the design and implementation of an automated parking system from the perspective of computer vision algorithms. Designing a low-cost system with functional safety is challenging and leads to a large gap between the prototype and the end product, in order to handle all the corner cases. We demonstrate how camera systems are crucial for addressing a range of automated parking use cases and also, to add robustness to…
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