Artificial Intelligence and Machine Learning as key enablers for V2X communications: A comprehensive survey-Reference-Cited by-同舟云学术

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Artificial Intelligence and Machine Learning as key enablers for V2X communications: A comprehensive survey

Published:2023-02 Issue: Volume:39 Page:100569
ISSN:2214-2096
Container-title:Vehicular Communications
language:en
Short-container-title:Vehicular Communications

Author:

Christopoulou Maria^ORCID,Barmpounakis Sokratis^ORCID,Koumaras Harilaos^ORCID,Kaloxylos Alexandros^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Automotive Engineering

Reference137 articles.

1. SAE, Automated Driving - Levels of Driving Automation Are Defined in New Sae International Standard J3016, 2016.

2. Vehicle-to-pedestrian communication for vulnerable road users: survey, design considerations, and challenges;Sewalkar;Sensors (Switzerland),2019

3. 3GPP, TR 22.885 (V14.0.0). Study on LTE Support for Vehicle to Everything (V2X) Services Release 14.

4. 3GPP, TR 22.886 (V16.2.0). Study on Enhancements and Support for 5G V2X Services; Release 16.

5. Notes on DSRC & WAVE standards suite: its architecture, design, and characteristics;Morgan;IEEE Commun. Surv. Tutor.,2010

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2. Automotive intelligence: Unleashing the potential of AI beyond advance driver assisting system, a comprehensive review;Computers and Electrical Engineering;2024-07

3. Forecasting and Improving Latency in 5G V2X Networks for Autonomous Driving Scenarios;2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON);2024-06-25

4. Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies;Sensors;2024-06-18

5. Resource allocation in V2X communication: State-of-the-art and research challenges;Physical Communication;2024-06

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