Risk-Based Design of Urban UAS Corridors

The rapid expansion of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) poses significant challenges for the integration of Unmanned Aircraft Systems (UAS) into dense urban environments, where safety risks and population exposure are particularly high. This study proposes and applies a methodology based on probabilistic assessment of both ground and air risk, grounded in the principles of safety management and the use of geospatial data from OpenStreetMap (OSM), official aeronautical charts, and digital urban models. The urban area is discretized into a spatial grid on which independent risks are calculated per cell and later combined through a cumulative probabilistic fusion model. The resulting risk estimates enable the construction of cost matrices compatible with path-search algorithms. The methodology is applied to a case study in Medellín, Colombia, connecting the Oviedo and San Diego shopping centers through Beyond Visual Line of Sight (BVLOS) operations of a DJI FlyCart 30 drone. Results show that planning with the A* algorithm produces safe routes that minimize exposure to critical areas such as hospitals and restricted air corridors, while maintaining operational efficiency metrics. This approach demonstrates a practical bridge between regulatory theory and operational practice in UAM corridor design, offering a replicable solution for risk management in urban scenarios.