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.

使用NVIDIA DriveWorks平台和单目摄像头，通过实时算法处理，本研究提出了一种地理定位道路物体的方法，为先进驾驶辅助系统（ADAS）和自动驾驶平台提供即时的物体识别和空间定位功能。实验证明，在控制和动态环境下，该方法可以在半径15米范围内使自动驾驶平台定位目标，静止时精度小于1米，在较高速度（60km/h）下误差小于4米。

使用逆 Haversine 公式在 NVIDIA Driveworks 中进行道路物体地理定位