Adaptive Edge Computing for Autonomous Vehicles in Varying Environment

This research offers an in-depth analysis of the integration of Autonomous Vehicle Platooning, Vehicle-to-Everything (V2X) communication, Edge Analytics, and Real-time Traffic Management. Central to the study is “Platooning,” where autonomous vehicles optimize road space, fuel efficiency, and safety. V2X communication, a silent yet critical interaction between vehicles and their surroundings, lays the foundation for advanced safety and navigation in autonomous vehicles. When combined with V2X, platooning generates vast data, making Edge Analytics essential for filtering realtime intelligence for swift decisions. The study emphasizes the importance of Real-time Traffic Management in managing urban congestion, with Edge Analytics providing dynamic route planning. By focusing on algorithms and practical applications, the research aims to merge these technologies for efficient, safe, and responsive Autonomous vehicles (AV) operations, offering insights for urban planning and traffic management, and setting the stage for a sustainable transportation future.