Robust Encounter Avoidance and Conflict Resolution for Advanced Air Mobility (REACT-AAM)

In Phase I, we demonstrated initial feasibility of innovative improvements of our Robust Encounter Avoidance and Conflict Resolution (REACT) Technology to handle multiple simultaneous encounters expected to arise in the dense Advanced Air Mobility airspaces. Specifically, the innovations include an efficient implementation of evolutionary algorithms to produce a multi-segment maneuver for resolving encounters that would have resulted to near-mid-air collisions. Another innovation is simultaneous risk assessment in the face of multiple encounters within transit corridors. Phase I showed that REACT exceeds the target level of safety of 10e-8 loss of vehicle incidents per flight hour. SSCI proposes to further extend our existing REACT solution by incorporating additional realistic AAM constraints and data from an airspace information manager. The data will be used for maneuver generation and construction of the fitness function. To prevent cases when no feasible solution can be found, we will augment our baseline strategy by a hierarchical constraint weighting function to guarantee a feasible result. With broader context of aircraft intent from the airspace information manager, the FORECAST module will produce improved predictions of vehicle traffic patterns and potential loss of separation. The focus will be toward the Regional Air Mobility (RAM) use case, where untowered airports and shared manned/unmanned airspace will be typical. We plan to use the Terminal Area Encounter Model as a basis for developing realistic encounter scenarios. Since high-risk phases of flight are in the terminal areas, our analysis during Phase II will focus on applications of our innovation to encounters typical during departure and arrival scenarios. We will prepare a hardware-in-the-loop (HWIL) testbed and scenario generator to produce performance analysis of the EA-based avoidance guidance. We will compare the EA-based performance to a baseline that uses single-segment maneuvers. For Advanced Air Mobility to accommodate dense airspace utilization, each participant will need to resolve the risk of collision posed by air traffic.  We propose a process to quantify and respond to risk of collision when the intentions of other vehicles are not known, by fusing measures of risk from multiple threats as part of a cost function, and considering all simultaneous threats in the avoidance strategy. REACT-AAM seeks to improve our baseline collision avoidance approach to accommodate the higher density utilization of mixed-use airspace envisioned in the Advanced Air Mobility concept.  To accomplish this, SSCI proposes to use machine intelligence for designing avoidance algorithms so that the flight path is optimized for the mission and multiple intruders. In this work, we seek to extend the guarantees of safety to a set of multi-sequence avoidance maneuvers through our real-time evolutionary algorithms.  Thus, we can improve performance of the mission and meet the metrics for flight safety amid multiple intruders through a heterogeneous series of dynamic responses.    This project expands the prototype to include more realism from the Advanced Air Mobility design concepts, specifically for Regional Air Mobility (RAM) for flight safety around untowered airports.  We will perform the following technical tasks:  Create System Requirements for the RAM scenarios.  Enhance SSCI’s REACT implementation by incorporating an airspace information manager to account for airspace constraints and traffic patterns to improve intent prediction.   The simulation tools will be expanded to support scenario generation using Lincoln Lab's encounter model for terminal area operations. Evaluate prototype software, which includes multi-PRS and real-time Evolutionary Algorithm-based maneuvers to compute the avoidance maneuvers under multiple simultaneous threats, and provide TLoS analysis through hardware-in-the-loop simulations. SSCI will deliver final reporting package with system design documentation, simulation data, and results of simulation analysis in the context of the metrics described in the DO-365 MOPs.  The final delivery will also include the prototype software package.  

The key NASA application of REACT-AAM technology is to the AAM and UTM Programs. applications are envisioned in the remote sensing missions which will use multiple collaborating UAS operating beyond visual line of sight, and where there is a need for separation assurance with other traffic and between team members. Companies that are currently involved in AAM-related development include Joby Aviation, Wisk Aero, Reliable Robotics, Merlin Labs, Xwing, and others, and are envisioned as the first users of the REACT-AAM technology on their UAS. REACT-AAM technology will be an important contributor to enabling the safe use of UAS in urban and suburban areas for BVLOS applications including parcel delivery, transportation of goods, traffic monitoring, and inspection of railroad tracks, power lines, and pipelines. A general nature of the technology makes it also applicable to ground and maritime vehicles as well as to spacecraft.

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