The Impact of AI on Traffic Management and Safety in the Internet of Vehicles through Mobile Edge Computing

The integration of Artificial Intelligence (AI) and Mobile Edge Computing (MEC) emerges as a transformative force in optimizing traffic control mechanisms, preventing congestion, and enhancing overall safety in the Internet of Vehicles (IoV). This systematic literature review explores the synergistic impact of AI and MEC on traffic management and safety within the IoV. Spanning the period from 2018 to 2023, the study synthesizes findings from key sources in the IEEE, Google Scholar, and Science-Direct databases. The review addresses pivotal research questions, including the role of AI in efficient vehicle-to-vehicle communication, the challenges in implementing AI-powered MEC, and the potential impacts on road safety. Findings underscore the positive contributions of AI and MEC across various facets of IoV, from predictive traffic management to accident prevention and collaborative autonomous driving. The implications of this study extend to policymakers, industry stakeholders, and researchers, emphasizing the need for robust security frameworks, optimized edge computing infrastructure, and collaborative efforts to overcome challenges. This study also highlights future trends such as the integration of AI with 5G, advancements in edge computing, and the convergence of technologies, anticipating a more intelligent and connected IoV ecosystem. While the study acknowledges limitations in the reviewed literature, it underscores the importance of ongoing research to address emerging trends and ensure the effective deployment of AI and MEC for a safer and more efficient IoV.