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3D-CDTI User Manual v2.1

The 3D-Cockpit Display of Traffic Information (3D-CDTI) is a flight deck tool that presents aircrew with: proximal traffic aircraft location, their current status and flight plan data; strategic conflict detection and alerting; automated conflict resolution strategies; the facility to graphically plan manual route changes; time-based, in-trail spacing on approach. The CDTI is manipulated via a touchpad on the flight deck, and by mouse when presented as part of a desktop flight simulator.

3D CDTI↗

A 3-Dimensional Cockpit Display with Traffic and Terrain Information for the Small Aircraft Transportation System

The report discusses the architecture and the flight test results of a 3-Dimensional Cockpit Display of Traffic and terrain Information (3D-CDTI). The presented 3D-CDTI is a perspective display format that combines existing Synthetic Vision System (SVS) research and Automatic Dependent Surveillance-Broadcast (ADS-B) technology to improve the pilot's situational awareness. The goal of the 3D-CDTI is to contribute to the development of new display concepts for NASA's Small Aircraft Transportation System research program. Papers were presented at the PLANS 2002 meeting and the ION-GPS 2002 meeting. The contents of this report are derived from the results discussed in those papers.

UijtdeHaag, Maarten↗

Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

CWAM↗

Development of an algorithm to model an aircraft equipped with a generic CDTI display

A model of human pilot performance of a tracking task using a generic Cockpit Display of Traffic Information (CDTI) display is developed from experimental data. The tracking task is to use CDTI in tracking a leading aircraft at a nominal separation of three nautical miles over a prescribed trajectory in space. The analysis of the data resulting from a factorial design of experiments reveals that the tracking task performance depends on the pilot and his experience at performing the task. Performance was not strongly affected by the type of control system used (velocity vector control wheel steering versus 3D automatic flight path guidance and control). The model that is developed and verified results in state trajectories whose difference from the experimental state trajectories is small compared to the variation due to the pilot and experience factors.

Driscoll, W. C.↗