# Unmanned Autonomous Intelligent System in 6G Non-Terrestrial Network
## 4 Application of UAV-Aided Non-Terrestrial Networks in UAIS
### Connected and Automated Vehicles in UAV-Aided NTNs
#### 4.2.1 Vehicle-to-Everything Communication via NTN  
The autonomous driving capabilities of CAVs rely on information from both onboard sensors and external connections. Cameras, Global Positioning Systems (GPS), and Light Detection and Ranging (LIDAR) are typical sensors onboard CAVs. The external connections of vehicles include Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle (V2V), Vehicle-to-Cloud (V2C), and finally Vehicle-to-Everything (V2X), which are established via communication methods like cellular or direct communication [130; 131; 132; 133]. The future development of 6G technology holds promise for enabling the V2X prospects through an advanced communication network that is flexible, high-speed, ultra-reliable, and has low-latency for information interactions between CAVs and other infrastructure. This will be achieved through the comprehensive integration of terrestrial and non-terrestrial networks. It is believed that 6G communication technology will better satisfy the requirements of the next-generation V2X in remote and uncovered areas via satellite and UAV communication. Furthermore, in the case of cloud/edge-based real-time tasks for CAVs, a reliable and low-latency connection is of extreme importance. With NTN communication technology, the data transmitting and offloading between CAVs and external devices can achieve an ultra-low latency of less than 1 ms [134; 135; 136]. To enable autonomous driving in intelligent transportation systems, CAVs must maintain connections with various vehicles and roadside units (RSUs) in a real-time manner. This connection is vital for accurate traffic perception, automatic navigation, and collision avoidance of CAVs. With the advancement of cellular-vehicle-to-everything (C-V2X) technology, the utilization of V2X present high demands for extensive network coverage, offloading computation-intensive task, low latency, and stringent reliability. This presents new challenges for communication systems. Due to the high deployment cost and strict location selection requirements, conventional terrestrial base stations cannot guarantee wide area coverage of V2X applications. Therefore, UAV-assisted V2X was introduced as a non-terrestrial means with flexibility and ease of deployment to support CAV wireless communication. Non-terrestrial networks tend to be an effective means for V2X communications. UAV non-terrestrial networks show promise for establishing V2X connections scenarios where signal blockage occurs due to buildings and challenging terrains. However, UAV-based V2X communication still faces underlying challenges, including ultra-low latency communication, limited battery life, high volume communication, and low access efficiency. A variety of studies have been published on non-terrestrial UAV V2X communication for CAVs, addressing issues such as low-latency vehicle-to-vehicle communication, energy consumption optimization, and channel prediction. Researchers [137] analyzed rotary-wing and fixed-wing unmanned aerial vehicles as CAV network access points, using millimeter-wave technology for high-speed connectivity to CAVs (Figure 5). Based on the study results, UAV HAPS systems outperformed low Earth orbit satellites (LEOs) in terms of lower latency. To address the latency issues of CAV V2X communication [138], explored a scheme involving UAV-assisted deployment of roadside units, with a focus on minimizing CAV latency while also optimizing CAV energy consumption. To address the requirements of vehicular platooning or formation control issues, a study in [139] evaluated a UAV-V2X network in the context of UAV unstable motion. The evaluation involved the use of association probability for a vehicular-to-UAV link, while vehicular-to-vehicular links were modeled using the Poisson point process. In V2X connections, data dissemination is essential for sharing information between CAVs. In reference [140], a novel dynamic path-planning method for a UAV base station was employed to optimize the data dissemination process by minimizing communication overhead.