Amalgamating Vehicular Networks With Vehicular Clouds, AI, and Big Data for Next-Generation ITS Services

• Published in: IEEE transactions on intelligent transportation systems 2024-01, Vol.25 (1), p.1-15
• Main Authors: Rajput, Nitin Singh, Singh, Upendra, Dua, Amit, Kumar, Neeraj, Rodrigues, Joel J. P. C., Sisodia, Sheetal, Elhoseny, Mohammed, Lakys, Yahya
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Big Data; Cloud computing; Computer architecture; Data mining; ITS; Multilayers; Roads; Transportation; transportation big data; VANETS; Vehicles; Vehicular ad hoc networks; vehicular cloud computing
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2023.3234559

Advances in the connected vehicle and cloud computing technologies, Big data, and artificial intelligence techniques have opened new research opportunities. We can integrate them to work out the issues originating from transportation complexities and offer improved services. In this work, we present a seamless multi-module multi-layer vehicular cloud computing system developed using resources of parked vehicles, cloud computing facilities, and vehicular networking technologies. It can offer transportation-specific AI and Big data-empowered services to on-road vehicles. As use cases, we present two innovative and improved services, vehicular Big data mining and vehicular route optimization. A physical testbed is formed to show the feasibility of this work. Results analysis shows that the systems perform better than the standalone systems and servers under different scenarios. Relevant fundamental challenges and future outlooks are also highlighted in this work.