Integrating Unmanned Aerial Vehicles in Airspace: A Systematic Review

Arif Tuncal, Ufuk Erol
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Abstract

In this article, a comprehensive review of the integration of Unmanned Aerial Vehicles (UAVs) into shared airspace is presented. The primary objective is to underscore and gain a full understanding of the challenges, issues, and potential solutions related to regulatory frameworks, safety, and coordination. The methodology employed is a systematic review approach, which ensures the reliability and efficacy of the selected literature. The findings underscore the significance of various components, including multi-layered airspace models, path planning, secure communication networks, Conflict Detection and Resolution (CDR), and regulatory measures, in augmenting the safety of UAV integration. Additionally, the article explores the utilization of Reinforcement Learning (RL) and Human-in-the-loop Reinforcement Learning (HRL) algorithms as promising techniques for instructing UAVs to navigate complex environments and adapt to changing circumstances. The study emphasizes the importance of collaboration among all stakeholders, the support of technology development, and the need for continuous research.
将无人驾驶飞行器纳入空域:系统回顾
本文全面回顾了将无人驾驶飞行器(UAV)纳入共享空域的情况。主要目的是强调并全面了解与监管框架、安全和协调有关的挑战、问题和潜在解决方案。所采用的方法是系统回顾法,可确保所选文献的可靠性和有效性。研究结果强调了包括多层空域模型、路径规划、安全通信网络、冲突检测与解决(CDR)和监管措施在内的各个组成部分在增强无人机集成安全性方面的重要性。此外,文章还探讨了如何利用强化学习(RL)和人在环强化学习(HRL)算法,将其作为指导无人机在复杂环境中导航并适应不断变化的环境的有效技术。该研究强调了所有利益相关者之间合作的重要性、对技术开发的支持以及持续研究的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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