A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles
An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The pr...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/4/1213 |
| _version_ | 1828280190833262592 |
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| author | Jae Kyu Suhr Ho Gi Jung |
| author_facet | Jae Kyu Suhr Ho Gi Jung |
| author_sort | Jae Kyu Suhr |
| collection | DOAJ |
| description | An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision. |
| first_indexed | 2024-04-13T07:56:37Z |
| format | Article |
| id | doaj.art-26e8676a738840d7b3a391687587aa56 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T07:56:37Z |
| publishDate | 2018-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-26e8676a738840d7b3a391687587aa562022-12-22T02:55:23ZengMDPI AGSensors1424-82202018-04-01184121310.3390/s18041213s18041213A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf VehiclesJae Kyu Suhr0Ho Gi Jung1School of Intelligent Mechatronics Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, KoreaDepartment of Electronic Engineering, Korea National University of Transportation, 50 Daehak-ro, Chungju-si, Chungbuk 27469, KoreaAn automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision.http://www.mdpi.com/1424-8220/18/4/1213automatic parking systemparking slot recognitionaround-view monitor (AVM) systemsensor fusion |
| spellingShingle | Jae Kyu Suhr Ho Gi Jung A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles Sensors automatic parking system parking slot recognition around-view monitor (AVM) system sensor fusion |
| title | A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles |
| title_full | A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles |
| title_fullStr | A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles |
| title_full_unstemmed | A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles |
| title_short | A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles |
| title_sort | universal vacant parking slot recognition system using sensors mounted on off the shelf vehicles |
| topic | automatic parking system parking slot recognition around-view monitor (AVM) system sensor fusion |
| url | http://www.mdpi.com/1424-8220/18/4/1213 |
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