A 5G Roadside Infrastructure Assisting Connected and Automated Vehicles in Vulnerable Road User Protection

IF 4.6 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Raffaele Viterbo;Federico Campolo;Mattia Cerutti;Satyesh Shanker Awasthi;Stefano Arrigoni;Mattia Brambilla;Monica Nicoli
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引用次数: 0

Abstract

Road safety is one of the major concerns when considering road vehicles, with issues referring to both drivers and Vulnerable Road Users (VRUs) (e.g., pedestrians). The role of roadside infrastructures in augmenting VRU protection is gaining popularity thanks to the development of smart and connected sensing systems, which enable the detection of critical events and their forwarding to nearby Connected and Automated Vehicles (CAVs) by Vehicle-to-Everything (V2X) communications. In this context, the fifth generation (5G) of mobile radio networks is emerging as the communication enabler for advanced V2X services for CAVs. In this work we propose the design, development, and assessment on road of a 5G roadside infrastructure for VRU protection, performing an in-depth analysis of the single components and their integration into the service. More specifically, we present a Roadside Unit (RSU) capable to detect, localize, and track VRUs; a communication architecture that exploits 5G V2X connectivity for sending VRUs detections; a CAV with on-board algorithms warning the driver of the presence of the VRU and an Autonomous Emergency Braking (AEB) solution triggered by the 5G V2X architecture. We validate the efficacy of the proposed solution in a road scenario inside the campus of Politecnico di Milano.
5G路边基础设施助力互联自动驾驶汽车保护弱势道路使用者
在考虑道路车辆时,道路安全是主要问题之一,涉及驾驶员和弱势道路使用者(例如行人)的问题。由于智能和互联传感系统的发展,路边基础设施在增强VRU保护方面的作用越来越受欢迎,智能和互联传感系统能够检测关键事件,并通过车辆对一切(V2X)通信将其转发给附近的互联和自动驾驶车辆(cav)。在此背景下,第五代(5G)移动无线网络正在成为自动驾驶汽车先进V2X服务的通信推动者。在这项工作中,我们提出了用于VRU保护的5G路边基础设施的设计、开发和道路评估,对单个组件及其集成到服务中进行了深入分析。更具体地说,我们提出了一个路边单元(RSU),能够检测、定位和跟踪vru;利用5G V2X连接发送vru检测的通信架构;带有车载算法的自动驾驶汽车(CAV)会警告驾驶员VRU的存在,以及由5G V2X架构触发的自动紧急制动(AEB)解决方案。我们在米兰理工大学校园内的道路场景中验证了所提出解决方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
5.40
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0.00%
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