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下（例如汽车感知系统的夜间场景）的性能表现。本文描述了用于评估物体（汽车）检测图像系统性能的图像系统仿真软件工具。我们针对13种具有不同光学器件与像素尺寸的相机进行了实验。为衡量相机空间分辨率的影响，我们设计了包含不同距离车辆的场景集合。通过测量平均精度对系统性能进行量化，并报告了系统分辨率与物体检测性能之间的关联趋势。同时，我们量化了所有相机在夜间条件下相较于日间条件的显著性能下降（基于COCO预训练网络）。