## 2 Related Work  
Fifth-generation wireless communications (5G) and artificial intelligence (AI) are thought to be two separate research fields. Artificial intelligence and next-generation wireless communication technologies have been specifically developed to meet applications at this convergence of the creation of an AI-based Vehicle-to-Everything (AI-V2X) system for intelligent cities and autonomous vehicles that combine artificial intelligence with 5G networking technology. To improve traffic performance and safety, ref. [17] proposed a new emergency vehicle route-clarifying technique based on vehicle-to-vehicle (V2V) communication. The technique is intended to locate the nearest car with which to contact and clear the road lane, ensuring that the emergency vehicle arrives at its location with as little travel time as possible. To improve Quality-of-Service (QoS) in high-mobility vehicular networks, ref. [18] developed a cooperative communication strategy that combines V2I and V2V approaches. It increased system reliability and efficiency in a variety of environmental circumstances by optimizing key QoS performances through adaptive transmission scheme selection. Ref. [19] looked at ways to improve vehicle-to-vehicle communication (V2V) using 5G technology, which provides faster data rates and more bandwidth than the DSRC (5.9 GHz) system it replaces. The study looked at how sand and dust affected the communication paths lost for both DSRC and 5G frequency bands in urban and highway settings, and it proposed a new link margin model to calculate their effects. Moreover, ref. [20] developed a deep learning approach to improve Vehicle-to-Everything (V2X) communication in vehicular networks, with the goal of determining the optimal interference power for increased connectivity, QoS, and communication link reliability. The findings confirmed the model's ability to improve road traffic information efficiency and safety through increased V2X communication. In the context of connected and autonomous vehicles, this convergence of technologies attempts to maximize the potential of both AI and 5G to improve communication and performance. The proposed strategy in [21] aimed to improve driving performance, comfort, and safety by utilizing data-driven approaches and real-time communication, leading to appreciable advancements in transportation, traffic monitoring, V2X communication development, driving comfort, and a decrease in traffic congestion. Furthermore, ref. [22] suggested a 5G Vehicle-to-Everything (V2X) Intelligent Intrusion Detection System (IIDS) for connected and autonomous vehicles (CAVs) based on a modified Convolutional Neural Network (CNN). The IIDS detected attacks with a remarkable 98% accuracy, effectively increasing security in the Internet of Vehicles (IoV) system by identifying and classifying rogue AVs. Moreover, ref. [23] provided a comprehensive overview of 5G New Radio (NR) in cellular vehicle-to-everything (V2X) systems for future connected autonomous communication networks. The article covered various aspects, including the physical layer, sidelink communication, architecture flexibility, security, privacy mechanisms, precise positioning techniques, and the potential of machine learning for performance enhancement. Additionally, it highlighted 5G NR's configuration to support advanced V2X use cases. Additionally, in [24] a deep learning-based traffic safety solution for a mixed-autonomous/manual Intelligent Transportation System (ITS) was proposed, leveraging 5G technology. By utilizing driving trajectory and natural-driving datasets, the approach achieved higher real-time intention identification rates for lane changes, resulting in improved accuracy and safety in mixed traffic scenarios. It is worth mentioning that other techniques were developed to improve the performance of AVs in different manners. Ref. [25] presented a secure user authentication mechanism for self-driving cars operating in a 5G network.