Swaminathan Harihara Bharathy, Sommer Aron, Becker Andreas, Atzmueller Martin
Semantic Information Systems Group, Osnabrück University, 49090 Osnabrück, Germany.
Aptiv Services Deutschland GmbH, 42119 Wuppertal, Germany.
Sensors (Basel). 2022 Nov 2;22(21):8419. doi: 10.3390/s22218419.
Global Navigation Satellite Systems provide autonomous vehicles with precise position information through the process of position augmentation. This paper presents a series of performance tests aimed to compare the position accuracy of augmentation techniques such as classical Differential Global Navigation Satellite System, Real-time Kinematic and Real-time eXtended. The aim is to understand the limitations and choose the best position augmentation technique in order to obtain accurate, trustworthy position estimates of a vehicle in urban environments. The tests are performed in and around the German cities of Wuppertal and Duesseldorf, using a vehicle fitted with the navigation system POS-LV 220, developed by Applanix Corporation. In order to evaluate the real-time performance of position augmentation techniques in a highly challenging environment, a total of four test regions are selected. The four test regions are characterized mainly by uneven terrain with tall buildings around the University of Wuppertal, flat terrain with roads of varying width in the city centre of Wuppertal and Duesseldorf and flat terrain in a tunnel section located in the city of Wuppertal. The performances of the different position augmentation are compared using a Root Mean Square (RMS) error estimate obtained as an output from the Applanix system. Furthermore, a High-Definition map of the environment is used for the purpose of model validation, which justifies the use of RMS error estimate as an evaluation metric for the performance analysis tests. According to the performance tests carried out as per the conditions specified in this paper, the Real-time eXtended (RTX) position augmentation method enables to obtain a more robust position information of the vehicle than Real-time Kinematic (RTK) method, with a typical accuracy of a few centimeter in an urban environment.
全球导航卫星系统通过位置增强过程为自动驾驶车辆提供精确的位置信息。本文介绍了一系列性能测试，旨在比较经典差分全球导航卫星系统、实时动态定位和实时扩展等增强技术的定位精度。目的是了解这些技术的局限性，并选择最佳的位置增强技术，以便在城市环境中获得车辆准确、可靠的位置估计。测试在德国伍珀塔尔市和杜塞尔多夫市及其周边地区进行，使用一辆装有Applanix公司开发的POS-LV 220导航系统的车辆。为了评估位置增强技术在极具挑战性环境中的实时性能，总共选择了四个测试区域。这四个测试区域的主要特点是：伍珀塔尔大学周围地形不平且有高楼大厦；伍珀塔尔市和杜塞尔多夫市中心地形平坦但道路宽度各异；伍珀塔尔市一段隧道内地形平坦。使用从Applanix系统输出的均方根（RMS）误差估计来比较不同位置增强技术的性能。此外，使用环境的高清地图进行模型验证，这证明了使用RMS误差估计作为性能分析测试的评估指标是合理的。根据本文规定的条件进行的性能测试，实时扩展（RTX）位置增强方法比实时动态定位（RTK）方法能够获得更可靠的车辆位置信息，在城市环境中的典型精度为几厘米。
