用于自动驾驶和无人机地理围栏的动态地图
Dynamic maps for automated driving and UAVs geofencing
摘要：
在过去的几年里，人们对无人驾驶汽车的兴趣显著上升;自然，与此同时，对准确可靠的目标定位和映射系统的需求也比以往任何时候都高。这种系统必须在近距离内向用户提供准确的信息。之前已经有许多研究工作探索了在智能交通系统环境中实现这种高度动态映射系统的不同可能方法，但很少有人讨论其对其他5G垂直和服务的适用性。在本文中，我们首先描述动态映射的概念。然后，我们介绍了我们在创建一个时空动态地图系统时所采取的方法，提出了它的体系结构和不同的组件。在此之后，我们提出了不同的场景，在这些场景中，这种相当新的现代技术可以适用于其他5G服务，特别是无人机地理围栏，最后，我们测试了目标检测模块并讨论了结果。
英文摘要：
The past few years have witnessed a remarkable rise in interest in driver-less cars; and naturally, in parallel, the demand for an accurate and reliable object localization and mapping system is higher than ever. Such a system would have to provide its subscribers with precise information within close range. There have been many previous research works that have explored the different possible approaches to implement such a highly dynamic mapping system in an intelligent transportation system setting, but few have discussed its applicability toward enabling other 5G verticals and services. In this article we start by describing the concept of dynamic maps. We then introduce the approach we took when creating a spatio-temporal dynamic maps system by presenting its architecture and different components. After that, we propose different scenarios where this fairly new and modern technology can be adapted to serve other 5G services, in particular, that of UAV geofencing, and finally, we test the object detection module and discuss the results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
