I developed the Airspace Auction Simulator, an open-source tool for optimizing airspace allocation for drones in urban environments. As drone traffic increases over dense urban areas, efficient unmanned traffic management (UTM) systems become essential to distribute airspace fairly and safely beyond first-come-first-serve approaches.
The simulator uses realistic 3D city models to evaluate allocation mechanisms across welfare maximization and revenue optimization strategies. I implemented pathfinding algorithms including A* search and greedy optimizations that account for complex flight routes and building obstacles. The open, extensible architecture allows researchers to integrate and test custom allocation mechanisms through a web interface with interactive 3D visualization.
Simulation analysis evaluates allocation mechanisms across efficiency, fairness, and safety metrics. The simulator processes complex scenarios to provide insights into future drone traffic management, supporting UTM system research, route optimization in urban areas, and safety protocol development for drone traffic.
The Airspace Auction Simulator is an advanced open-source tool for optimizing airspace allocation for drones in urban areas. It uses realistic 3D city models and advanced algorithms to simulate and evaluate various airspace usage scenarios.
The simulator offers mechanisms for maximizing welfare and revenue, advanced pathfinding algorithms like A* search, realistic environment modeling with 3D city models, and an interactive web interface for configuring and visualizing simulations.
An increasing number of drones will fly over urban areas in coming years. An efficient UTM (unmanned traffic management) system is essential to distribute airspace fairly and safely, improving upon traditional methods like first-come-first-serve.
Pathfinding uses advanced algorithms like A* search and greedy optimizations. These consider complex flight routes and obstacles in the urban environment to calculate safe and efficient flight paths for drones.
The simulator can be used for UTM system research and development, testing various allocation mechanisms, optimizing drone routes in urban areas, and developing safety protocols for drone traffic.
Airspace allocation is optimized through various allocation strategies aimed at maximizing welfare and revenue. The simulator evaluates different mechanisms based on how effectively they distribute airspace among drones while delivering fair and efficient results.
The simulator was implemented with an open, extensible architecture and is accessible as a web application. It requires the ability to process complex 3D city models and execute various pathfinding and optimization algorithms. Visualization occurs through an interactive 3D user interface.
Simulation results are analyzed through various metrics evaluating airspace usage efficiency, distribution fairness, and flight path safety. Analysis helps understand the strengths and weaknesses of different allocation mechanisms and identify improvement potential.
.
Copyright 2026 - Joel P. Barmettler