Maneuver Coordination Service With Reliability and Relevance Enhancements

IF 5.3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Andreia Figueiredo;João Viegas;Pedro Rito;Miguel Luís;Susana Sargento
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引用次数: 0

Abstract

The increase in vehicle density exacerbates traffic congestion, accidents, and emissions. Automated Vehicles (AVs), while promising improved safety and efficiency, require seamless coordination and communication to unlock their full potential. The European Telecommunications Standards Institute (ETSI) Maneuver Coordination Service (MCS) draft introduces Vehicle-to-Everything (V2X) communication for real-time vehicle coordination, utilizing a modular architecture designed to enhance inter-vehicle communication. However, a major limitation of the current MCS framework is its vulnerability to message loss during maneuver negotiation, which can increase latency and negatively impact maneuver efficiency. This paper proposes an acknowledgment mechanism in MCS to enhance message reliability and a Relevance Message Detector to filter out irrelevant messages, reducing processing overhead. The experimental results demonstrate that introducing an acknowledgment mechanism can reduce maneuver negotiation time by approximately 900 ms compared to standard methods under packet loss scenarios, significantly improving reliability and efficiency. Furthermore, the Relevance Message Detector effectively minimizes unnecessary message processing, enhancing overall system efficiency. Functional evaluations validate the correct execution of coordinated maneuvers, demonstrating the practical benefits of the proposed extensions. These enhancements contribute to a more robust and efficient MCS framework, improving AV coordination in real-world scenarios.
增强可靠性和相关性的机动协调服务
车辆密度的增加加剧了交通拥堵、事故和排放。自动驾驶汽车(AVs)虽然有望提高安全性和效率,但需要无缝的协调和沟通才能充分发挥其潜力。欧洲电信标准协会(ETSI)机动协调服务(MCS)草案引入了车辆对一切(V2X)通信,用于实时车辆协调,利用模块化架构来增强车辆间通信。然而,当前MCS框架的一个主要限制是在机动协商过程中容易出现消息丢失,这会增加延迟并对机动效率产生负面影响。本文提出了MCS中的确认机制来提高消息的可靠性,并提出了相关消息检测器来过滤不相关的消息,以减少处理开销。实验结果表明,在丢包情况下,引入确认机制可使机动协商时间比标准方法减少约900 ms,显著提高可靠性和效率。此外,相关消息检测器有效地减少了不必要的消息处理,提高了系统的整体效率。功能评估验证了协调操作的正确执行,展示了所建议的扩展的实际好处。这些增强有助于建立一个更强大、更高效的MCS框架,改善现实场景中的自动驾驶协调。
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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