Low cost design of parallel parking assist system based on an ultrasonic sensor

Jeong, Seonghee; Choi, Chi Gun; Oh, Jun-Nam; Yoon, Pal Joo; Kim, B. S.; Kim, M.; Lee, K. H.

doi:10.1007/s12239-010-0050-0

Cited by 52 publications

(30 citation statements)

References 6 publications

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“…Most parking-assist system products currently available in the market adopt this method. This is categorized by space-recognizing sensors; the most common of which is an ultra-sonic sensor [4]- [5], although range sensors such as LiDAR (light detection and ranging) sensors [6]- [7] and microwave radar sensors [8]- [9] are also used. Recently, research on vision-based space recognition techniques has been actively conducted.…”

Section: Related Workmentioning

confidence: 99%

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Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Han¹,

Choi²

2015

ETRI J

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An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient‐line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

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Section: Related Workmentioning

confidence: 99%

“…Here, V(v) and H(u) are the vertical and horizontal weighted slice functions, respectively. The examples of the estimated pillbox kernel obtained by (5) are shown in Fig. 5.…”

Section: Pillbox Kernel Estimation and Fast Convolutionmentioning

confidence: 99%

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Han¹,

Choi²

2015

ETRI J

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“…Its requirements of hardware in perception parts mainly refer to the selection of sensors (Jeong et al, 2010). That is to say it requires high precision sensors.…”

Section: Ultrasonic Sensor and Radar Technologymentioning

confidence: 99%

Automatic parking of vehicles: A review of literatures

Wang

Song

Zhang

et al. 2014

Int.J Automot. Technol.

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Collision accidents often occur during parking or reversing cars. In allusion to this point, this paper conducts a review of literatures on automatic parking. To begin with, a brief introduction of automatic parking including its background and significance is given. Then its commercial application, research status and latest progress are summarized which include visual perception, ultrasonic sensors and radar technology, path planning, control algorithms based on fuzzy theory, neural network, image processing and recognition technology, and digital signal processing technology, etc. On further analysis, some reasonable conclusions are drawn and the future work is suggested.

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“…This is the most widely used approach as it can be implemented using various range-finding sensors, such as ultrasonic sensors [9][10][11][12][13][14][15], laser scanners [16][17][18], short-range radars [19][20][21], structured light [22], depth cameras [23], stereo cameras [24][25][26][27][28][29], etc. However, the free-space-based approach has an inherent drawback in that it cannot find free spaces when there is no adjacent vehicles and its accuracy depends on the positions and poses of adjacent vehicles.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

Zhang

Huang

et al. 2018

Symmetry

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Recent years have witnessed a growing interest in developing automatic parking systems in the field of intelligent vehicles. However, how to effectively and efficiently locating parking-slots using a vision-based system is still an unresolved issue. Even more seriously, there is no publicly available labeled benchmark dataset for tuning and testing parking-slot detection algorithms. In this paper, we attempt to fill the above-mentioned research gaps to some extent and our contributions are twofold. Firstly, to facilitate the study of vision-based parking-slot detection, a large-scale parking-slot image database is established. This database comprises 8600 surround-view images collected from typical indoor and outdoor parking sites. For each image in this database, the marking-points and parking-slots are carefully labeled. Such a database can serve as a benchmark to design and validate parking-slot detection algorithms. Secondly, a learning-based parking-slot detection approach, namely PSD L , is proposed. Using PSD L , given a surround-view image, the marking-points will be detected first and then the valid parking-slots can be inferred. The efficacy and efficiency of PSD L have been corroborated on our database. It is expected that PSD L can serve as a baseline when the other researchers develop more sophisticated methods.

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Low cost design of parallel parking assist system based on an ultrasonic sensor

Cited by 52 publications

References 6 publications

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Automatic parking of vehicles: A review of literatures

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

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