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.

I. Introduction

Edge computing in cars is popping up as a big deal for the internet of Vehicles (IoV) to make traffic more efficient [1]. The Internet of Vehicles is pushing the limit on cool tech, social stuff between vehicles matters for traffic solutions. Smart Driving Vehicles (SDVs) use Mobile Edge Computing (MEC) to handle tricky road stuff better, smart network of SDV and MEC. But High Mobility Edge Computing (HMECHO) service transfer might slow things down and cause security problems and to make the smart grid faster, a hybrid forwarding and reputation management (HTRM) system is presented [2]. The internet of Vehicles (IoV) is key for giving all kinds of services because it gathers information so well in real-time. Typically, the information goes to a central resource-heavy cloud platform to do the service. Edge Computing (EC) puts physical resources near roadside units for IoV to support real time services for drivers. Also, lots of things optimize EC-enabled IoV, but they hardly help make choices based on demands right now [3]. Aiming to create a safer and more effective transportation system, the Internet of Vehicles (IoV) is an emerging technology that connects automobiles, infrastructure, and pedestrians [4]. The integration of mobile edge computing (MEC) and artificial intelligence (AI) into networks can help with traffic management and security which are the two major challenges of the internet of vehicles.