Deep and Reinforcement Learning Technologies on Internet of Vehicle (IoV) Applications: Current Issues and Future Trends

Recently, artificial intelligence (AI) technology has great attention in transportation systems, which led to the emergence of a new concept known as Internet of Vehicles (IoV). The IoV has been associated with the IoT revolution and has become an active field of research due to the great need, in addition to the increase in the various applications of vehicle communication. AI provides unique solutions to enhance the quality of services (QoS) and performance of IoV systems as well. In this paper, some concepts related to deep learning networks will be discussed as one of the uses of machine learning in IoV systems, in addition to studying the effect of neural networks (NNs) and their types, as well as deep learning mechanisms that help in processing large amounts of unclassified data. Moreover, this paper briefly discusses the classification and clustering approaches in predicative analysis and reviews their abilities to enhance the performance of IoV application systems.

Automated summary

This paper discusses the application of artificial intelligence in transportation systems, specifically the emerging concept of the Internet of Vehicles (IoV). AI provides unique solutions through deep learning networks to enhance the performance of IoV systems, particularly in processing unclassified data. The paper also explores the classification and clustering approaches in predictive analysis and their impact on improving IoV application systems.