Automotive sensing: assessing the impact of fog on LWIR, MWIR, SWIR, visible, and lidar performance
Automotive sensing: assessing the impact of fog on LWIR, MWIR, SWIR, visible, and lidar performance
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汽车传感：评估雾对长波红外、中波红外、短波红外、可见光和激光雷达性能的影响
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
A. Richards
中科院分区：
文献类型：
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作者：
K. Judd;M. Thornton;A. Richards
自动驾驶汽车传感器套件必须在各种天气条件下运行，以实现可接受的安全性和可靠性水平。雾是最具挑战性的驾驶条件之一。本文给出了热红外（长波和中波）、短波红外和可见光成像传感器在不同试验舱雾下的定性性能数据。我们发现，LWIR成像的性能受到轻到中度雾的影响明显小于其他两个IR传感器，可见光成像仪和低分辨率Velodyne LiDAR。本文建议进行额外的雾室测试，以生成有助于开发成像仿真能力的数据，这些成像仿真能力可以准确地模拟这些波段的雾，从而提高ADAS和自动驾驶车辆（AV）视觉系统开发的可靠性和覆盖范围。
Autonomous vehicle sensor suites must perform in a variety of weather conditions to achieve acceptable levels of safety and reliability. Fog is one of the most challenging driving conditions. This paper presents qualitative performance data of thermal infrared (both longwave and midwave), shortwave infrared, and visible-light imaging sensors under different testchamber fogs. We find that the performance of LWIR imaging is impacted significantly less by light-to-moderate fog than the other two IR sensors, the visible imager, and a low-resolution Velodyne LiDAR. The paper recommends additional fog chamber testing to generate data that will be useful for the development of imaging simulation capability that accurately models fog across these wavebands for improved reliability and coverage in the development of ADAS and autonomous vehicle (AV) vision systems.