Maneuver Prediction and Avoidance Logic For Unmanned Aircraft System (UAS) Encounters with Non-Cooperative Air Traffic


OBJECTIVE: Develop an analytic framework and methodology to address unanticipated maneuver encounter modeling, collision risk estimation and ownship maneuver logic to support optimal operation of manned and unmanned aircraft in a complex and congested airspace. DESCRIPTION: With the widespread introduction of unmanned aircraft, the nature of the airspace will change significantly over the next 10-20 years as they are fully integrated into both segregated and non-segregated airspace. New procedures and technologies will be required to ensure safe airspace operations while accommodating increasing traffic demands. Current top level design requirements for sensor systems supporting collision avoidance assume stressing straight-line intruder collision trajectories to establish hardware requirements as a function of maneuver decision latency and own-ship maneuverability. This is a very reasonable approach to establish the system design. In practice the current state of the art maneuver logic must be improved to consider unanticipated maneuvers by an intruder occurring after the own-ship collision avoidance maneuver initiation. Such a situation exists when encountering non-cooperative, maneuvering intruders, such as those operating under Visual Flight Rules (VFR). These encounters are particularly challenging due to the inherent uncertainties in predicting the future trajectories of these intruders. Understanding the nature of unanticipated maneuvers and their likelihood during encounters in representative actual airspace types is essential for the development of the collision avoidance logic. Investigators have suggested [1] that one way of meeting this challenge is to treat"well clear"as a separation standard that is quantified using the risk (i.e. probability) of Near Mid-Air Collision (NMAC) at some future time, and to alert pilots when action is required to avoid violating this separation. A maneuver decision approach which matches suitable encounter models with sensor, air vehicle and level of decision autonomy is needed. This likely involves (explicitly or implicitly) a stochastic model to quantify likely intruder trajectories. A number of candidate approaches exist for computing such risks including the use of continuous-time, maneuver-based stochastic models and diffusion-based methods. A key element in such an approach is the ability to capture variations in maneuvering aircraft trajectories over representative encounter time scales, that it be viable for a real-time collision avoidance and provide a quantifiable performance improvement in terms of the traditional detection-theoretic metrics of probability of detection (Pd) and probability of false alarm (Pfa). Such an approach could then be utilized in the assessment of the overall system level of safety and support administrative certification. PHASE I: Develop the overall analytic framework and methodology for collision avoidance maneuver logic in the presence of unanticipated intruder maneuvers occurring after the ownship (UAS) collision avoidance maneuver initiation . Identify the key elements in a maneuver decision approach which matches suitable encounter models with sensor capabilities, air vehicle dynamics and level of decision autonomy. PHASE II: Develop a maneuver decision approach to account for unanticipated maneuvers as a function of class of airspace and varying levels of knowledge about the type of intruder aircraft. Demonstrate the approach on representative encounter scenarios. Develop models to validate the approach relative to the risk metrics. PHASE III: Transition the approach and supporting algorithms into general use for airborne collision avoidance systems in service or under development. PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: The research directly supports civil integration of UAS into the NAS. Commercial market for UAS including police departments is a huge private sector growth area. REFERENCES: 1. Kochenderfer, M.J., Edwards, M.W.M, Espindle, L.P., Kuchar, J.K., & Griffith, J.D. (2010). Airspace encounter models for estimating collision risk. Journal of Guidance, Control, and Dynamics, 33(2), 487-499. doi:10.2514/1.44867 2. M. Kochenderfer, L. Espindle, J. Kuchar, and J. Griffith,"A Comprehensive Aircraft Encounter Model of the National Airspace System,"Lincoln Laboratory Journal, Volume 17, Number 2, 2008 3. Weibel, R.E., Edwards, M.W.M., Fernandes, C.S. (2011). Establishing a risk-based separation standard for unmanned aircraft self separation. Ninth USA/Europe Air Traffic Management Research & Development Seminar, 1-7. Retrieved from

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