Fifth-generation Vehicle-to-Everything (V2X) networks have ushered in a new set of challenges that negatively affect seamless connectivity, specifically owing to high user equipment (UE) mobility and high density. As UE accelerates, there are frequent transitions from one cell to another, and handovers (HOs) are triggered by network performance metrics, including latency, higher energy consumption, and greater packet loss. Traditional HO mechanisms fail to handle such network conditions, requiring the development of Intelligent HO Decisions for V2X (IHD-V2X). By leveraging Q-Learning, the intelligent mechanism seamlessly adapts to real-time network congestion and varying UE speeds, thereby resulting in efficient handover decisions. Based on the results, IHD-V2X significantly outperforms the other mechanisms in high-density and high-mobility networks. This results in a reduction of 73% in unnecessary handover operations, and an 18% reduction in effective energy consumption. On the other hand, it improved handover success rates by 80% from the necessary handover and lowered packet loss for high mobility UE by 73%. The latency was kept at a minimum of 22% for application-specific requirements. The proposed intelligent approach is particularly effective for high-mobility situations and ultra-dense networks, where excessive handovers can degrade user experience.

The deployment of Augmented Reality (AR) is a necessity as an enabling technology for intelligent transportation systems (ITSs), with the potential to boost the implementation of Vehicle-to-Everything (V2X) networks while improving driver experience and increasing driving safety to fulfill AR functionality requirements. In this regard, V2X networks must maintain a high quality of service AR functionality, which is more challenging because of the nature of 5G V2X networks. Moreover, the execution of diverse traffic requirements with varying degrees of service quality is essential for seamless connectivity, which is accomplished by introducing efficient handover (HO) techniques. However, existing methods are still limited to basic services, including conversional, video streaming, and general traffic services. In this study, a Multiple Criteria Decision-Making (MCDM) technique is envisioned to address the handover issues posed by high-speed vehicles connected to ultra-high-density (UDN) heterogeneous networks. Compared with existing methods, the proposed HO mechanism handles high mobility in dense 5G V2X environments by performing a holistic evaluation of network conditions and addressing connection context requirements while using cutting-edge applications such as AR. The simulation results show a reduction in handover delays, failures, and ping-pong, with 84% prevention of unnecessary handovers.

Rapid urbanization and the design of smart cities create new challenges for the safety and well-being of their citizens. Among the factors that affect citizens’ safety are demographic explosion, an increase of public transportation and private vehicles, overcrowding by pedestrian road users, and unsafe driving behaviors. The increase in vehicular traffic-related fatalities in many urban areas can be averted by the implementation of safe mobility solutions for smart cities. 5G networks are touted as a game-changing mobile communications advancement because they provide high data rates with ultra-low latency for the benefit of real-time applications such as augmented reality. Beyond speed improvement, 5G is expected to unleash a massive 5G Internet of Things (IoT) ecosystem where networks can serve communication needs for billions of connected devices in the context of smart cities, with the right trade-offs between speed, latency, and cost. Recently, Vehicle-to-Everything (V2X) has emerged as a new hybrid type of communication between transport vehicles (V2V), pedestrians (V2P), infrastructure (V2I), and networks (V2N), which requires the features of the 5G network to provide application connectivity and for citizens’ new mobile services. V2X uses cases/applications that enable vehicles to connect and exchange data with other vehicles, traffic lights, parking spaces, nearby people, and services to coordinate traffic flow and environmental safety. Augmented reality (AR) is an emerging technology that can greatly enhance the implementation of V2X in terms of information processing and public safety. AR can transform the way users and devices work by turning information into immersive experience to enhance drivers’/passengers’ deep sensing and situational awareness, provide improved real-time hazard alerts, and inform traffic scenarios and pedestrian behavior. This chapter discusses the implications of AR technologies in V2X, as well as the challenges and future directions in the implementation of these emerging technologies. <!----> <!----> <!----> <!---->