Artificial Intelligence for Autonomous Vehicular Communication Networks [From the Guest Editors]

IEEE Vehicular Technology Magazine, vol. 17, pp. 83–84

Abstract

With advances in sensing, communication, and networking, autonomous vehicles and unmanned aerial vehicles (UAVs) are expected to play a vital role in a variety of areas, including health care, Industry 4.0, smart farming and agriculture, logistics, transportation, and public safety. Together with the upcoming 5G/6G technologies, connected vehicular systems will become more ubiquitous and practical. Artificial intelligence (AI) and machine learning (ML) can provide significant benefits toward automating the tasks of sensing, computing, and communicating in vehicular communication networks. By leveraging traces of numerous operations, AI can optimize network decisions that are reflected in resource utilization and service enhancement.

Authors 6

1. Li‐Chun Wang

   National Yang Ming Chiao Tung University

   Affiliation as printed

   Department of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

2. Haris Gacanin Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Aachen, Germany

3. Dusit Tao Niyato

   Nanyang Technological University

   Affiliation as printed

   School of Computer Science and Engineering, Nanyang Technological University, Singapore

4. Yu‐Jia Chen

   National Central University

   Affiliation as printed

   Department of Communication Engineering, National Central University, Taoyuan City, Taiwan

5. Chun‐Hung Liu

   Mississippi State University

   Affiliation as printed

   Department of Electrical and Computer Engineering, Mississippi State University, Starkville, Mississippi, USA

6. Alagan Anpalagan

   Toronto Metropolitan University

   Affiliation as printed

   Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada