Detect And Avoid (DAA) is an essential capability for autonomous and semi-autonomous Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) aircraft operating Beyond Visual Line of Site (BVLOS) within the National Airspace System (NAS).
The capability presented in this proposal will overcome the following barriers to entry: cognition and multi-objective decision making, cost-effective, resilient, and self-organizing communications and verification and validation technology and certification approaches. Our research will benefit detect and avoid algorithms, sensor fusion techniques, robust trajectory planners, and contingency management systems that can enable AAM and higher levels of UAS integration into the NAS.
For a DAA algorithm to be certified for use within the NAS, the computing platform which includes all the software and hardware necessary for it to be executed also needs to be certified. Furthermore, different sensors for detecting intruder aircraft do not perform as well as each other under all operating conditions and utilize technologies that are not equally certifiable. The capability to execute two DAA functions (see examples below) and other autonomy functions concurrently supports the integration of these sensors and technologies enabling aircraft autonomy.
The current state of the art does not offer a low Size, Weight and Power (SWaP) certifiable computing platform suitable for AAM and UAM aircraft that provides this capability.
The computing platform offered by this proposal provides this capability
NASA applications that require DAA functions and other autonomy functions for integration into the national airspace system
Non-NASA applications that require DAA functions and other autonomy functions for integration into the national airspace system