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基于主路径分析的车联网领域知识发展轨迹

Knowledge Development Trajectory of the Internet of Vehicles Domain Based on Main Path Analysis.

机构信息

College of Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.

Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.

出版信息

Sensors (Basel). 2023 Jul 3;23(13):6120. doi: 10.3390/s23136120.

DOI:10.3390/s23136120
PMID:37447969
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10347000/
Abstract

The Internet of vehicles (IoV) is an Internet-of-things-based network in the area of transportation. It comprises sensors, network communication, automation control, and data processing and enables connectivity between vehicles and other objects. This study performed main path analysis (MPA) to investigate the trajectory of research regarding the IoV. Studies were extracted from the Web of Science database, and citation networks among these studies were generated. MPA revealed that research in this field has mainly covered media access control, vehicle-to-vehicle channels, device-to-device communications, layers, non-orthogonal multiple access, and sixth-generation communications. Cluster analysis and data mining revealed that the main research topics related to the IoV included wireless channels, communication protocols, vehicular ad hoc networks, security and privacy, resource allocation and optimization, autonomous cruise control, deep learning, and edge computing. By using data mining and statistical analysis, we identified emerging research topics related to the IoV, namely blockchains, deep learning, edge computing, cloud computing, vehicular dynamics, and fifth- and sixth-generation mobile communications. These topics are likely to help drive innovation and the further development of IoV technologies and contribute to smart transportation, smart cities, and other applications. On the basis of the present results, this paper offers several predictions regarding the future of research regarding the IoV.

摘要

车联网（IoV）是交通运输领域基于物联网的网络。它由传感器、网络通信、自动化控制和数据处理组成，实现了车辆与其他物体之间的连接。本研究采用主路径分析（MPA）来研究 IoV 的研究轨迹。从 Web of Science 数据库中提取了研究论文，并生成了这些研究论文之间的引文网络。MPA 表明，该领域的研究主要涵盖媒体接入控制、车对车信道、设备到设备通信、层、非正交多址接入和第六代通信。聚类分析和数据挖掘揭示了与 IoV 相关的主要研究主题包括无线信道、通信协议、车联网、安全性和隐私性、资源分配和优化、自动驾驶控制、深度学习和边缘计算。通过使用数据挖掘和统计分析，我们确定了与 IoV 相关的新兴研究主题，包括区块链、深度学习、边缘计算、云计算、车辆动力学以及第五代和第六代移动通信。这些主题可能有助于推动 IoV 技术的创新和进一步发展，并为智能交通、智慧城市和其他应用做出贡献。基于目前的研究结果，本文对 IoV 的未来研究提出了一些预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/7dd939e3bb42/sensors-23-06120-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/7dd939e3bb42/sensors-23-06120-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/2f01202c936b/sensors-23-06120-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/18233c789f2b/sensors-23-06120-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/d2b2373ef201/sensors-23-06120-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/cb5b12871912/sensors-23-06120-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/240493b9a0f9/sensors-23-06120-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/4b5b8be5996b/sensors-23-06120-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/354c0120354f/sensors-23-06120-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/24a2f033f935/sensors-23-06120-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1112/10347000/7dd939e3bb42/sensors-23-06120-g013.jpg

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