Navigating Network Availability: A Shortest Path Approach to Uav Traffic Routing

Abstract

The use of unmanned aerial vehicles (UAVs), commonly known as drones, is rapidly increasing across both commercial and recreational domains. This growth highlights a significant challenge: the lack of a drone traffic management system with a well-defined airspace traffic network and, routing and flight path planning. As drone operations expand, airspace becomes increasingly crowded, increasing the risk of aerial conflicts and emphasizing the need for effective regulatory and operational frameworks. This research aims to address these challenges by developing tools to be integrated into UAV Traffic Management (UTM) systems, enabling efficient flight planning for UAVs within an airspace structured as a network in consideration of ongoing traffic. A novel mathematical model is proposed to find a flight plan that specifies the flight path as well as a time schedule of traversing arcs on the path. A network transformation method is developed to reformulate the problem on an auxiliary network that allows solution by a novel labeling algorithm. Computational experiments demonstrate that our proposed solution approach outperforms a commercial solver by efficiently solving large-scale problems in under one second, making it highly suitable for seamless integration into UTM systems. Our findings offer valuable insights into determining the optimal flight paths of UAVs across various problem settings, such as the distance between origin and destination, the duration of the operation horizon, and network traffic. These insights may guide UTM providers in designing UTM systems that facilitate efficient airspace management.

Keywords: unmanned aerial vehicles, flight path planning, airspace traffic management, shortest path problem, intermittent arcavailability, labeling algorithm