Air Traffic Management-eXploration (ATM-X)
The Air Traffic Management – eXploration (ATM-X) project will transform the air traffic management system to safely accommodate the growing demand of new air vehicles to enter the airspace to perform a variety of missions. ATM-X also works on technologies to allow the traditional large commercial aircraft to fly more user-preferred routes with improved predictability, resulting in fuel and time savings.

Autonomous Flight Operations (AFO)
The current air traffic system imposes significant operating restrictions on airspace users and impedes National Airspace System growth. The CSAOB is researching how to introduce alternative automation-enable operations under “Autonomous Flight Rules” (AFR) without disrupting current operations conducted under IFR.  CSAOB is developing state-of-the-art cockpit automation tools to enable aircraft to “self-separate” from other traffic and airspace hazards in complex, high-density airspace while optimizing their trajectory and meeting arrival-time constraints.

Crew State Monitoring (CSM)
Attention-related performance issues have been identified as causal factors in commercial aviation accidents and incidents, especially in monitoring automation. In order to avoid attention related human performance issues in aeronautic operations, CSAOB is researching how the induction of human attention performance limiting state during realistic flight training simulations could mitigate these issues.

eXternal Vision Systems (XVS)
In successful low/no sonic boom supersonic aircraft, design drives the vehicle’s shape. The pilot’s forward visibility may be severely compromised if provided any visibility at all. Center prohibitive operational restrictions mandate design features which are not practical for manned supersonic aircraft.

Flight Deck Interval Management (FIM)
FIM tackles the challenges of improving the spacing precision of aircraft arriving into busy airports. Our research seeks to increase airport throughput, reduce delays, and shorten fuel usage.

Natural Language User Interface
The CSAOB is looking to enable mission managers, not UAV pilots, to define, set up, and manage multiple coordinated UAVs for multiple missions through the use of natural language processing.

Pairwise Trajectory Management (PTM)
PTM is a concept that utilizes airborne and ground-based capabilities to enable spacing operations in oceanic regions. These operations allow an aircraft to spend more time on its optimal trajectory which enables reductions in fuel burn. We want to use ADS-B in technology to increase situation awareness and enable new procedures by the flight crew to improve flight efficiency.

Traffic Aware Strategic Aircrew Requests (TASAR)
CSAOB is enabling real-time, in-flight route optimization by providing advanced trajectory management tools to pilots that leverage networked cockpit automation, while offering near-term benefits of ADS-B at low cost.  Building on decades of CSAOB R&D in Airborne Trajectory Management, the technology enabling this early route efficiency application initiates a roadmap of applications leading to potential operational autonomy in the future.

Trajectory-Based Operations (TBO)
The mission of Trajectory-Based Operations research is to support clean and efficient air transportation while safely accommodating the expected growth in air traffic demand with a wide range of vehicle performance characteristics and equipage. Participants include Traffic management units, Air Traffic Controllers, flight crews, airline operations centers, and systems command centers.

Traffic and DataComm Information Manager
Within an air traffic management + 3 environment, Net-Centric Ops (i.e, the transmittance of command, control, state, and the intent information via IAS agents), will be a prerequisite for operational coordination and efficiency. To ensure the requisite human oversight, awareness, and possible intervention, an Increasingly Autonomous System (IAS) is needed to effectively inform humans of relevant information (traffic, intent, messaging) being passed machine-to-machine without overwhelming the human participants (both volume and clutter).

Traffic Surveillance by Increasingly Autonomous System
The fundamental design of any Conflict Detection and Resolution (CD&R) system involves the trade-off between missed detections and false alarms. Current “detect, sense, and avoid” systems for unmanned vehicles are unacceptable for manned vehicles. We seek to create a significantly improved resolution with improvement/tailoring via human involvement by increasingly autonomous systems.

Technologies for Airplanes State Awareness (TASA)
Loss of Control due to a lowered state of awareness and energy caused by lack of external visual references is a major aviation safety issue. This project aims to mitigate the problems and contributing factors that lead to a flight crew’s loss of airplane state awareness. The CSAOB is developing data systems, models, training methods, and technologies for transition to the aviation community.

UAS Integration in the National Airspace System
Unmanned Aircraft are required to “remain well clear of other aircraft” by FAA regulation. FAA mandate has also stipulated the need for detect and avoid systems for unmanned aircraft. Research is needed to develop algorithms that provide alerting and guidance to other aircraft, and which are interoperable with collision avoidance systems.