The Cognitive Internet of Vehicles for Autonomous Driving

As it combines AI and IoT, autonomous driving has attracted a great deal of attention from both academia and industry because of its benefits to the economy and society. However, ultra-low delay and ultra-high reliability cannot be guaranteed by individual autonomous vehicles with limited intelligen...

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Bibliographic Details
Published in:IEEE network 2019-05, Vol.33 (3), p.65-73
Main Authors: Lu, Huimin, Liu, Qiang, Tian, Daxin, Li, Yujie, Kim, Hyoungseop, Serikawa, Seiichi
Format: Article
Language:English
Subjects:
Artificial intelligence
Autonomous vehicles
Computer architecture
Computer simulation
Edge computing
Fog
Internet
Internet of Things
Internet of Vehicles
Task analysis
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Summary:As it combines AI and IoT, autonomous driving has attracted a great deal of attention from both academia and industry because of its benefits to the economy and society. However, ultra-low delay and ultra-high reliability cannot be guaranteed by individual autonomous vehicles with limited intelligence and the existing architectures of the Internet of Vehicles. In this article, based on a cloud/fog-computing pattern and the IoT AI service framework, we propose a cross-domain solution for auto-driving. In contrast to existing studies, which mainly focus on communication technologies, our solution achieves intelligent and flexible autonomous driving task processing and enhances transportation performance with the help of the Cognitive Internet of Vehicles. We first present an overview of the enabling technology and the architecture of the Cognitive Internet of Vehicles for autonomous driving. Then we discuss the autonomous driving Cognitive Internet of Vehicles specifically from the perspectives of what to compute, where to compute, and how to compute. Simulations are then conducted to prove the effect of the Cognitive Internet of Vehicles for autonomous driving. Our study explores the research value and opportunities of the Cognitive Internet of Vehicles in autonomous driving.
ISSN:0890-8044
1558-156X
DOI:10.1109/MNET.2019.1800339