Optimizing Traffic Scheduling in Autonomous Vehicle Networks Using Machine Learning Techniques and T...
Optimizing Traffic Scheduling in Autonomous Vehicle Networks Using Machine Learning Techniques and Time-Sensitive Networking
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
This study investigates the optimization of traffic scheduling in autonomous vehicle networks using time-sensitive networking (TSN), a type of deterministic Ethernet. Ethernet has high bandwidth and compatibility to support various protocols, and its application range is expanding from office environments to smart factories, aerospace, and automobi...
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Full title
Optimizing Traffic Scheduling in Autonomous Vehicle Networks Using Machine Learning Techniques and Time-Sensitive Networking
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Author / Creator
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TN_cdi_proquest_journals_3084745107
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3084745107
Other Identifiers
ISSN
2079-9292
E-ISSN
2079-9292
DOI
10.3390/electronics13142837
