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Detail
Journal Article
Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps
- Authors
- Seung-Jun Han, Jeongdan Choi
- Issue Date
- 2015-12
- Citation
- ETRI Journal, v.37, no.6, pp.1220-1230
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- 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.
- KSP Keywords
- Autonomous vehicle, Bayesian Classifier, Environment Recognition, Height map, Image Sensor, Line feature, Map generation, Parking space, Recognition rate, execution time, feature extractor