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VAM Cluster Optimization
Halmstad University, School of Information Technology.
2023 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis will research and evaluate the state of the current ETSI VAM standard. The thesis evaluates and discusses the means of improving the speed and response of ETSI VAM by reducing the load on the radio medium. The research looks to prove that fewer messages broadcasted improve VRU awareness. The thesis focuses mainly on the benefits of VRU clustering as a means of reducing radio medium load through numerical evaluation and physical implementation testing. Evaluation of basic and alternate cluster parameters is performed to find the most optimal ones; alternate clustering strategies are also discussed and proposed. The thesis aims to improve the standard by finding and evaluating alternate methods and parameters in order to propose improved options.

Abstract [sv]

Projektet utvärderar och diskuterar sätten att förbättra hastigheten och responsen hos ETSI VAM genom att minska belastningen på radiomediet. Forskningen syftar till att bevisa att färre meddelanden som sänds förbättrar systemets VRU-medvetenhet. Fokuset ligger huvudsakligen på att utvärdera fördelarna med "VRU-klustring" som ett sätt att minska radiomediebelastningen genom numerisk utvärdering och fysisk testning. Utvärdering av grundläggande och alternativa klusterparametrar utförs för att hitta de mest optimala; alternativa klustringsstrategier diskuteras och föreslås också. Projektet syftar till att förbättra standarden genom att hitta och utvärdera alternativa metoder och parametrar för att föreslå förbättrade alternativ.

Place, publisher, year, edition, pages
2023. , p. 26
Keywords [en]
Traffic-Safety, Clustering, Vulnerable-Road-Users, ETSI, Intelligent-Transport-System, V2X
Keywords [sv]
Trafik-Säkerhet, Klustring, Oskyddade-Trafikanter, ETSI, Intelligent-Transport-System, V2X
National Category
Communication Systems Computer Systems
Identifiers
URN: urn:nbn:se:hh:diva-51110OAI: oai:DiVA.org:hh-51110DiVA, id: diva2:1776963
Subject / course
Computer science and engineering
Educational program
Computer Engineer, 180 credits
Supervisors
Examiners
Available from: 2023-07-06 Created: 2023-06-28 Last updated: 2023-07-06Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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