From Decision-Making to Database: Identifying Critical Ground-Based Information in Urban UTM

Urban Air Mobility (UAM) necessitates management methods beyond traditional Air Traffic Management (ATM), to ensure safe and efficient airspace in urban areas. This new approach is termed Unmanned aircraft systems Traffic Management (UTM). However, it has not emerged without challenges. A key issue in this shift is understanding how groundbased events, both scheduled and unscheduled, affect decision-making in UAS Traffic Controllers (UTCOs). This study aims to identify which ground-based constraints are influencing UTM and how information about these constraints should be managed within a future UTM database. To achieve this, data were collected through scenario-centered workshops and semi-structured interviews with air traffic controllers and police representatives. The findings were analyzed through the Joint Control Framework (JCF), particularly the Levels of Autonomy in Cognitive Control (LACC), to understand how ground-based information is integrated into UTM. The results indicate that not all events are equally important for UTCOs. Instead, the informational value depends on context, event type, and operational complexity. Informational requirements for a future database include data about time, location, stakeholders, restrictions, and mission type. This structured data could constitute a foundation to visualize information for UTCOs, and thereby support their decision-making process. The study contributes to the development of socially sustainable UAM by highlighting the need for selective and contextualized data management in UTM systems.