Unlike traditional multi-agent coordination frameworks, which assume a fixed number of agents, UAS traffic management (UTM) requires a platform that enables Uncrewed Aerial Systems (UAS) to freely enter or exit constrained low-altitude airspace. Consequently, the number of UAS operating in a given region is time-varying, with vehicles dynamically joining or leaving even in dense, obstacle-laden environments. The primary goal of this paper is to develop a computationally efficient management system that maximizes airspace usability while ensuring safety and efficiency. To achieve this, we first introduce physics-informed methods to structure fixed skyroads across multiple altitude layers of urban airspace, with the directionality of each skyroad designed to guarantee full reachability. We then present a novel Continuous UTM (C-UTM) framework that optimally allocates skyroads to UAS requests while accounting for the time-varying capacity of the airspace. Collectively, the proposed model addresses the key challenges of low-altitude UTM by providing a scalable, safe, and efficient solution for urban airspace usability.

翻译：与传统多智能体协调框架（假设智能体数量固定）不同，无人机交通管理（UTM）需要一个平台，使无人驾驶航空系统（UAS）能够自由进入或离开受约束的低空空域。因此，在给定区域内运行的UAS数量是时变的，即使在密集、障碍物充斥的环境中，飞行器也会动态加入或离开。本文的主要目标是开发一个计算高效的管理系统，在确保安全与效率的同时最大化空域可用性。为实现这一目标，我们首先引入物理信息方法，在城市空域的多个高度层中构建固定空中航路，每条航路的方向性设计旨在保证完全可达性。随后，我们提出了一种新颖的连续UTM（C-UTM）框架，该框架在考虑空域时变容量的同时，将空中航路最优分配给UAS请求。总体而言，所提出的模型通过为城市空域可用性提供可扩展、安全且高效的解决方案，应对了低空UTM的关键挑战。