Radar and Camera Fusion for Vacant Parking Space Detection

2022 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2022): INTELLIGENT TECHNOLOGY IN THE POST-PANDEMIC ERA(2022)

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摘要
This paper proposed a parking space detection system using the fusion of both radar and camera. Such fused approach addresses the challenging issue in which the border of parking slots is missing and/or not well drawn. Considering the adoption cost of the system, we incorporate Mediatek's Autus R10 (MT2706) Ultra-Short Range Radar with single transmitter and receiver (1T1R) antenna configuration. Such 1T1R radar has a lower cost than mTmR counterparts used in a vast majority of papers on the subject of radar signal processing. To the best of our knowledge, this is the first system fusing camera and radar (1T1R) to detect vacant parking space and estimate precise parking space coordinate without border lines of parking slots. At the same time, the proposed approach can also tackle extreme use-cases e.g., (1) non-car object occupation on the parking slot and (2) in a dim light night or rainy day. In the proposed system, the camera and radar detect the vacant parking space separately, then the corresponding results are fused together to get the final parking space coordinate for the auto-parking system. The experimental evaluations showed that the space prediction error was less than 1% with sufficient light and around 8% for the extreme situation. In summary, the proposed system handles the use-cases in different light conditions and weather, such as sunny days, rainy days, and night.
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关键词
sensor fusion, deep learning, radar, computer vision
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