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Parking space detection from a radar based target list

机译:从基于雷达的目标列表中检测停车位

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摘要

The detection of an unoccupied parking spaces is a requirement of autonomous parking systems. This paper presents a radar based real-time algorithm, which detects, classifies, and evaluates parking spaces in a vehicle's immediate vicinity. In contrast to frequently used gridmap methods, our approach processes the radar data in a specially designed target list of 2D vectors. Consequently, quantization errors are avoided and computational burdens reduced. Experiments show that the proposed algorithm is suited for both parallel and perpendicular parking spaces in urban scenes.
机译:空闲停车位的检测是自主停车系统的要求。本文提出了一种基于雷达的实时算法,该算法可以检测,分类和评估车辆附近的停车位。与常用的网格图方法相比,我们的方法在专门设计的2D矢量目标列表中处理雷达数据。因此,避免了量化误差并且减少了计算负担。实验表明,该算法适用于城市场景中的平行和垂直停车位。

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