Geometric Features-based Parking Slot Detection

2019-11-04Tool
Highly accurate parking slot detection methods are crucial for Automated Valet Parking (AVP) systems, to meet their demanding safety and functional requirements. While previous efforts have mostly focused on the algorithms’ capabilities to detect different types of slots under varying conditions, i.e. the detection rate, their accuracy has received little attention at this time. This paper highlights the importance of trustworthy slot detection methods, which address both the detection rate and the detection accuracy. To achieve this goal, an accurate slot detection method and a reliable ground-truth slot measurement method have been proposed in this paper. First, based on a 2D laser range finder, datapoints of obstacle vehicles on both sides of a slot have been collected and preprocessed. Second, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm has been improved to efficiently cluster these unevenly-distributed datapoints. After that, the Random Sample Consensus (RANSAC) algorithm has been improved to accurately fit the vehicles’ longitudinal contours. Finally, the candidate slot has been constructed and checked for its rationality. The final slot detection results have been defined in a way that contains both the slot size information and the slot relative position to the ego vehicle, which increases the requirement for detection accuracy. The performance of the proposed slot detection method has been verified on a test vehicle, and the experimental results show that the maximum errors in the detected slots under different conditions are 11.86 cm (position) and 3.35 deg (orientation).
Detection
  1. Abstract and Figures In this paper, we propose a parking slot markings detection method based on the geometric features of parking slots. The proposed system mainly consists of two steps, namely.
  2. Detecting a stationary car in the footage is a good predictor of the actual parking slot location. Sure, there will be movement while the cars enter/exit the slot. But those are noises which we can tune out. Once determined the parking slots all that remains is to detect if a car is present or absent in a new frame.
  3. It consists of two submodules, i.e., around view construction and parking slot detection. A line filter is designed to abstract central points of parking lines. The designed line filter makes full use of the feature of parking lines that are brighter than its neighborhood. Geometry constraints of parking slots are used to localize parking slots.
  4. Role that parking has to play in place shaping as well as a possible tool for promoting travel choice. Case studies have been used to assess the impact of current parking standards and their functional relationship to the development they serve. A fundamental change included in the revised parking standards is a move.
DOI: https://doi.org/10.4271/2019-01-5061
Citation: Yang, Q., Chen, H., Su, J., and Li, J., 'Towards High Accuracy Parking Slot Detection for Automated Valet Parking System,' SAE Technical Paper 2019-01-5061, 2019, https://doi.org/10.4271/2019-01-5061.
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Author(s): Qinghua Yang, Hui Chen, Junzhe Su, Jie Li

Redundancy is intentional and enables the use of different subsets of sensors when developing Advanced Driver Assistance Systems (ADAS) applications (e.g. Pedestrian detection, obstacle detection, vehicle following, collision warning, traffic sign recognition, parking slot detection, backup maneuver, collision detection, etc.).

ParkingGeometric features-based parking slot detection devices
Pages: 10
Event: New Energy & Intelligent Connected Vehicle Technology Conference
e-ISSN: 2688-3627

Geometric Features-based Parking Slot Detection Software

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