Geolocation is integral to the seamless functioning of autonomous vehicles and advanced traffic monitoring infrastructures. This paper introduces a methodology to geolocate road objects using a monocular camera, leveraging the NVIDIA DriveWorks platform. We use the Centimeter Positioning Service (CPOS) and the inverse Haversine formula to geo-locate road objects accurately. The real-time algorithm processing capability of the NVIDIA DriveWorks platform enables instantaneous object recognition and spatial localization for Advanced Driver Assistance Systems (ADAS) and autonomous driving platforms. We present a measurement pipeline suitable for autonomous driving (AD) platforms and provide detailed guidelines for calibrating cameras using NVIDIA DriveWorks. Experiments were carried out to validate the accuracy of the proposed method for geolocating targets in both controlled and dynamic settings. We show that our approach can locate targets with less than 1m error when the AD platform is stationary and less than 4m error at higher speeds (i.e. up to 60km/h) within a 15m radius.

翻译：地理定位对于自动驾驶车辆与先进交通监测基础设施的无缝运行至关重要。本文提出一种基于单目摄像头、借助NVIDIA DriveWorks平台实现道路目标地理定位的方法。我们利用厘米级定位服务（CPOS）与逆半正矢公式实现对道路目标的精确地理定位。NVIDIA DriveWorks平台的实时算法处理能力能够为高级驾驶辅助系统（ADAS）及自动驾驶平台提供即时目标识别与空间定位。我们提出了一套适用于自动驾驶（AD）平台的测量流程，并给出了使用NVIDIA DriveWorks标定摄像头的详细指南。通过实验验证了该方法在受控环境与动态环境下对目标定位的准确性。结果表明，当自动驾驶平台静止时，本方法可在15米半径内实现误差小于1米的目标定位；在较高速度（即高达60公里/小时）下，定位误差小于4米。