Empirical Evaluation of Federated Unmanned Traffic Management Architectures: Performance Analysis Under High-Density Operations
Abstract
Unmanned aircraft system traffic management (UTM) frameworks from multiple international initiatives define essential services but remain deliberately non-prescriptive about how architectures should be implemented, how multiple providers should be federated, and how performance should be validated under high-density operations. This research investigated the operational performance of single-provider versus federated multi-provider UTM configurations through controlled simulation experiments. We designed and implemented a modular five-layer UTM experimental framework that includes strategic planning, tactical deconfliction, safety monitoring, identity and security, and federation interfaces, aligned with current UTM concepts and service definitions. A discrete-event simulation instantiated this framework to evaluate system performance across different traffic demand levels (20, 60, and 100 flights per hour) and communication delay conditions (0.2, 1.0, and 5.0 seconds) under both federated and non-federated configurations. Experimental results showed that federation performance depends on the operating regime. At high demand with moderate delay (100 flights per hour and 1.0 second delay), federation reduced mean conflicts by 34% (from 44.0±2.9 to 29.0±11.0) and improved safety scores from 0.637 to 0.818 through coordinated intent planning. In contrast, at low demand with minimal delay (20 flights per hour and 0.2 second delay), federation overhead increased conflicts by roughly a factor of four (from 0.33±0.47 to 1.33±1.89), while safety scores remained high (above 0.96). These findings quantify the operational envelope in which multi-provider coordination provides a net benefit and establish empirical baselines for deployment and policy decisions in federated UTM ecosystems.
Fields of Study & Subjects
Air Traffic Management and Optimization
Aerospace and Aviation Technology
Human-Automation Interaction and Safety
Publication details
- Journal / source
- Preprints.org
- Publication date
- 6 February 2026
- Document type
- Preprint