Abstract

Future air mobility will consist of increased unmanned aerial vehicle (UAV) traffic operating in urban areas. Currently, the lower airspace in these environments is mainly used by traffic operating under visual flight rules, particularly helicopters in emergency medical services (HEMS). In the presented work, we analyze urban HEMS missions with automatic dependent surveillance-broadcast (ADS-B) data to identify the potential benefits to support UAV traffic management (UTM). In our methodology, we first restrict an existing HEMS ADS-B data set to a specific city and then further process it to extract the valid HEMS flights. Because no other mission information is available, we apply rule-based algorithms to define different helicopter flight segments and characterize specific HEMS mission segments. The resulting data set is analyzed to extract the characteristic information about the HEMS traffic within the city. The methodology is applied to the ADS-B HEMS flight data in the area of Berlin. The results show that the HEMS and flight segments can be identified robustly, and specific flight patterns are characteristic for them. Based on the results of this analysis, UAV traffic alert strategies are proposed to demonstrate the potential benefit of integrating ADS-B data statistics for UTM.

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