Advances of vehicular ad hoc network using machine learning approach

See Thian Meng (Faculty of Information Science and Technology, Multimedia University)
Sumendra Yogarayan (Faculty of Information Science and Technology, Multimedia University)
Siti Fatimah Abdul Razak (Faculty of Information Science and Technology, Multimedia University)
Subarmaniam Kannan (Faculty of Information Science and Technology, Multimedia University)
Afizan Azman (Faculty of Information and Technology, Taylors University)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 32, No 3: December 2023

Vehicular Ad hoc Networks (VANETs) play a crucial role in Intelligent Transportation Systems (ITS), enabling seamless communication between vehicles and other entities. VANETs provide a wide range of services, allowing vehicles to communicate with each other and with roadside infrastructure. With the increasing amount of data generated by VANETs, machine learning approaches have emerged as valuable tools to address complex challenges in this domain. This paper presents a comprehensive literature review on the application of machine learning in VANETs. The paper discusses the potential challenges and future research directions in the field, emphasizing the need for more accessible machine learning solutions for VANETs. This review emphasizes the significant role of machine learning approach in advancing the capabilities of VANETs and shaping the future of intelligent transportation systems.