Posted by John McHale EAST SYRACUSE, N.Y., 26 Oct. 2010. Sensis Corp.'s Aerobahn airport surface management system Predictive Engine capability is now available. The Aerobahn Predictive Engine uses a proprietary adaptive learning technique with continually received, recent historic surface surveillance information to provide airline and airport users with an accurate projection of activity. These projected actions, such as taxi routes, gate usage and estimated times of arrival/departure, can be viewed as much as two hours into the future and are continually updated. The adaptive learning technique of the Aerobahn Predictive Engine allows the system to modify based on changes in airport surface conditions (e.g., weather, surface traffic congestion, taxiway closure), and can be easily adapted to any new airport, providing highly accurate estimates of aircraft taxi durations and taxi-in/taxi-out times. This advanced capability is being integrated with Hartsfield-Jackson Atlanta International Airport's Aerobahn system to enable the world's busiest airport to proactively manage surface activity for more efficient operations and improved customer experience. Sensis Aerobahn combines airside operational information, such as flight schedules, with the exact location and identification of aircraft and vehicles on the airport surface for a real-time, comprehensive view and management of operations. Additionally, Aerobahn data is archived for playback and analysis, enabling post-event review and processes improvement. "Sensis Aerobahn's Predictive Engine enables an airport operator or airline to see into the future of the airport with a high degree of accuracy," says John Jarrell, vice president and general manager of Sensis Air Traffic Systems. "When you combine the Predictive capabilities with Aerobahn's Dynamic Rules Alerting functionality at Atlanta, you can automatically generate alerts based on future events. For example, an airline operations manager can be alerted in advance that an incoming wide-body flight with a high number of connecting passengers will be arriving at a specific time. That alert can also be sent by email to the individual who is responsible for the ramp to be appropriately staffed and equipped just in time for the arrival."The Sensis Predictive Engine supports Federal Aviation administration (FAA) Surface Collaborative Decision Making (CDM) System and European Airport-CDM requirements. The Engine uses Aerobahn's historic surveillance data and timing information for every aircraft movement on the airport’s surface to accurately predict taxi times, determine estimated time of arrivals and departures, when and what gates will be in use and the path the aircraft will most likely use to maneuver around the airport surface. This continually updated information will enable airport and airline operations personnel to better anticipate key events that impact daily operations, such as peak arrival and departure times, planned gate assignments, ground crew staffing and push-back sequencing according to previous events. The Predictive Engine is scheduled for operational use at Atlanta in the fourth quarter of 2010. In addition to the Predictive capability, Sensis Aerobahn enables users to observe departure queues, view actual arrival demand and contrast the demand with available gates for arriving aircraft. Further, users can customize the views and maps, such as adding annotations, and use the picture-in-picture capability to monitor both a specific area and the entire airport simultaneously. The system can be set to provide users with a visual or email alert when performance thresholds, such as taxi-out times, are met or exceeded. Aerobahn also provides users with the ability to create their own reports, based on numerous variables, for detailed analysis of operations. Sensis is also deploying at Atlanta a GPS-based vehicle tracking system that leverages an airport-wide wireless communication network for location and identification of vehicles on the airport surface without using the 1090 spectrum. Vehicle position data from the wireless network is seamlessly integrated into Aerobahn’s surface surveillance display to provide fully integrated aircraft and vehicle tracking. "At Atlanta, users will have the industry's first fully integrated vehicle and aircraft situational awareness and identification system that provides a common, shared display of all surface activity among airport stakeholders," Jarrell says. "This facilitates improved coordination of ground services between service providers, the airport and airlines to further enhance Atlanta's efficiency."
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