The automotive and railway industries are rapidly transforming with a strong drive towards automation and digitalization, with the goal of increased convenience, safety, efficiency, and sustainability. Since assisted and fully automated automotive and train transport services increasingly rely on vehicle-to-everything communications, and high-accuracy real-time positioning, it is necessary to continuously maintain high-accuracy localization, even in occlusion scenes such as tunnels, urban canyons, or areas covered by dense foliage. In this paper, we review the 5G positioning framework of the 3rd Generation Partnership Project in terms of methods and architecture and propose enhancements to meet the stringent requirements imposed by the transport industry. In particular, we highlight the benefit of fusing cellular and sensor measurements and discuss required architecture and protocol support for achieving this at the network side. We also propose a positioning framework to fuse cellular network measurements with measurements by onboard sensors. We illustrate the viability of the proposed fusion-based positioning approach using a numerical example.

翻译：汽车和铁路工业正在迅速转变,大力推动自动化和数字化,目标是提高方便性、安全性、效率和可持续性;由于协助和完全自动化的汽车和火车运输服务日益依赖车辆到一切的通信和高精度实时定位,因此有必要保持高度准确的定位,甚至在隧道、城市峡谷或密集叶子覆盖的地区等隐蔽场景中也是如此;在本文件中,我们从方法和结构方面审查了第三代伙伴关系项目的5G定位框架,并提出改进建议,以满足运输业的严格要求;特别是,我们强调使用手机和传感器测量的好处,并讨论在网络一侧实现这一点所需的结构和协议支持;我们还提议了一个定位框架,通过机载传感器进行测量,将蜂窝网络测量结合起来;我们用数字示例说明拟议的聚变定位方法的可行性。