{"title":"Maneuver Coordination Service With Reliability and Relevance Enhancements","authors":"Andreia Figueiredo;João Viegas;Pedro Rito;Miguel Luís;Susana Sargento","doi":"10.1109/OJITS.2025.3613990","DOIUrl":null,"url":null,"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.","PeriodicalId":100631,"journal":{"name":"IEEE Open Journal of Intelligent Transportation Systems","volume":"6 ","pages":"1325-1345"},"PeriodicalIF":5.3000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11177009","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11177009/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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.