Challenges Regarding AI Integration in V2X Communication

Advances in the field of computation, networking, communication and machine learning have allowed for their integration in vehicle-to-everything communication to form intelligent transportation systems. These systems aim to improve safety, mitigate traffic congestion, and enhance fuel efficiency. The main challenge this survey investigates is the integration of artificial intelligence within vehicle-to-everything systems, focusing on its contributions to improving vehicle communications and traffic management. We discuss the current state of artificial intelligence applications in vehicle-to-everything, explore key challenges, and propose future research directions.

I. Introduction

Modern vehicles are equipped with more advanced sensors and onboard units (OBUs) that have higher performance thresholds, allowing them to observe their surroundings with far greater efficiency than in the past. When coupled with advancements in machine learning (ML) algorithms for data analysis and predictive models for traffic congestion, flow, and management, these technologies contribute to minimizing human errors and mitigating human fault.