A Physics-Informed Fixed Skyroad Model for Continuous UAS Traffic Management (C-UTM)

2025-12-05

AI Summary

To address the challenges of dynamic, high-concurrency unmanned traffic management (UTM) in dense urban low-altitude environments, this paper proposes a physics-informed multi-layer directional “skyway” architecture and a continuous spatiotemporal UTM scheduling framework. Methodologically, it integrates physics-based constraints, hierarchical directional airspace partitioning, and dynamic resource allocation to enable omnidirectional drone accessibility and real-time dynamic access. Crucially, time-varying airspace capacity is explicitly embedded into the scheduling model, enabling computationally efficient and scalable safe scheduling. Experiments in complex 3D urban settings demonstrate that the system significantly improves airspace utilization (+32.7%) and scheduling throughput (2.1×), while guaranteeing millisecond-level response latency and zero collision—establishing a deployable infrastructure paradigm for large-scale intelligent low-altitude transportation.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Application Domains: Mobility, Driving & Flight

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

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.

Problem

• Develops a scalable UAS traffic management system for dynamic airspace
• Introduces physics-informed fixed skyroads to ensure safety and reachability
• Optimally allocates skyroads to handle time-varying UAS traffic efficiently

Innovation

• Physics-informed fixed skyroads for urban airspace structuring
• Continuous UTM framework for dynamic UAS traffic allocation
• Scalable solution ensuring safety and efficiency in dense environments