Advanced Functions for Lowering Nuisance Alerts in a DAA System: Implementation and Performance Evaluation in Real-Time Human-in-the-Loop Testing

Over the past several decades, Remotely Piloted Aircraft Systems (RPAS) have experienced a large spreading into a number of applications, however, the current operational limitations imposed by the Aviation Authorities concerning safety, make their integration in the controlled airspace a great challenge. To this aim, the detect and avoid (DAA) systems play a fundamental role giving to the RPAS the capability to detect conflicting traffic or other hazards and take appropriate actions in order to guarantee the airspace safety. In this framework, the present work describes the DAA module, named ADAPT, that the Italian Aerospace Research Centre (CIRA) is developing. Such system merges several aspects of DAA state-of-the-art introducing some improvements to decrease the nuisance alerts and increase the situational awareness of the remote pilot through the customization of the graphical appearance of the human machine interface. The effectiveness of the developed DAA system has been demonstrated through the execution of a real-time human-in-the-loop test campaign of which some remarkable results are reported.