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Quantitative and Qualitative Evaluation Methods of Automotive Time of Flight Based Sensors

机译:汽车飞行时间传感器的定量和定性评估方法

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Time of Flight (ToF) based three-dimensional (3D) imaging sensors, such as Light Detection and Ranging (LiDAR) sensors or ToF cameras, can be used to depict their surroundings in form of a point cloud. The ToF method measures the time an emitted light signal takes to be reflected by a point in space and derives the distance from the known travel time of light. More and more ToF based 3D sensors are developed for automotive use as their target application. Automotive sensors are part of a safety critical application. Therefore, it is important to ensure that the provided sensor data is accurate with a known probability. In this paper, we describe and evaluate test procedures for quantitative and qualitative performance evaluation of ToF/LiDAR sensors with focus on automotive use. We propose a LiDAR error and influence model from which we derived eight test areas. We described and conducted tests for six of the eight test areas. The described test cases were evaluated on three LiDAR sensors and one ToF camera. The results show that targets and test procedures need to be adapted to the specific tested ToF/LiDAR sensor. Especially noticeable where influences on test procedures due sparse sensor resolution. Furthermore, the test results show that target application specific tests can provide additional information on the behaviour of the sensor.
机译:基于飞行时间(ToF)的三维(3D)成像传感器,例如光检测和测距(LiDAR)传感器或ToF相机,可用于以点云的形式描绘其周围环境。 ToF方法测量发射的光信号被空间中的点反射所需的时间,并从已知的光传播时间得出距离。越来越多的基于ToF的3D传感器被开发为汽车领域的目标应用。汽车传感器是安全性至关重要的应用的一部分。因此,重要的是要确保所提供的传感器数据在已知概率下是准确的。在本文中,我们描述并评估了针对汽车用途的ToF / LiDAR传感器的定量和定性性能评估的测试程序。我们提出了一个LiDAR误差和影响模型,从中我们得出了八个测试区域。我们描述了八个测试区域中的六个并进行了测试。在三个LiDAR传感器和一个ToF相机上评估了描述的测试用例。结果表明,目标和测试程序需要适应于特定的经过测试的ToF / LiDAR传感器。稀疏的传感器分辨率对测试程序的影响特别明显。此外,测试结果表明,针对特定目标应用的测试可以提供有关传感器行为的其他信息。

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