The design and evaluation of complex systems can benefit from a software simulation - sometimes called a digital twin. The simulation can be used to characterize system performance or to test its performance under conditions that are difficult to measure (e.g., nighttime for automotive perception systems). We describe the image system simulation software tools that we use to evaluate the performance of image systems for object (automobile) detection. We describe experiments with 13 different cameras with a variety of optics and pixel sizes. To measure the impact of camera spatial resolution, we designed a collection of driving scenes that had cars at many different distances. We quantified system performance by measuring average precision and we report a trend relating system resolution and object detection performance. We also quantified the large performance degradation under nighttime conditions, compared to daytime, for all cameras and a COCO pre-trained network.

翻译：复杂系统的设计与评估可受益于软件仿真（有时称为数字孪生）。仿真可用于表征系统性能，或测试其在难以测量的条件（例如汽车感知系统的夜间场景）下的表现。我们描述了用于评估汽车目标检测图像系统性能的图像系统仿真软件工具。我们介绍了使用13种不同摄像头（配备多种光学器件和像素尺寸）进行的实验。为衡量摄像头空间分辨率的影响，我们设计了一系列包含不同距离车辆的驾驶场景。通过测量平均精度来量化系统性能，并报告了系统分辨率与目标检测性能之间的关联趋势。我们还量化了所有摄像头在COCO预训练网络下夜间条件相比白天条件的显著性能下降。