基于边缘计算的协同定位，实现车道级高精度导航
Location as a service with a MEC architecture
- 通过移动边缘云聚合多车GPS数据
- 结合概率滤波与高精地图，定位精度达车道级
- 适合自动驾驶与高级辅助驾驶系统使用
近年来，自动驾驶逐渐成为现实，高级驾驶辅助系统（ADAS）已成为现代汽车的标配。这些系统需要极高精度的定位。本文提出一种协同定位方法：将多个道路用户的GPS信息汇集至移动边缘计算（MEC）云中，利用GNSS定位特性，结合概率滤波与高精地图，为所有参与者提供车道级定位精度。
原文摘要 · Abstract (English)
In recent years, automated driving has become viable, and advanced driver assistance systems (ADAS) are now part of modern cars. These systems require highly precise positioning. In this paper, a cooperative approach to localization is presented. The GPS information from several road users is collected in a Mobile Edge Computing cloud, and the characteristics of GNSS positioning are used to provide lane-precise positioning for all participants by applying probabilistic filters and HD maps.
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