Field evaluation of descent advisor trajectory prediction accuracy for en-route clearance advisories

Abstract

The Descent Advisor (DA) automation tool has undergone a series of field tests at the Denver Air Route Traffic Control Center to study the feasibility of DAbased clearances and procedures. The latest evaluation, conducted in the fall of 1995, expanded the operational nature of DA testing to include a wider variety of test conditions. A total of 197 commercial flights from three airlines participated in the study over twenty-three days of testing. Aircraft included large and heavy jet transports, both conventional-and flight-managementsystem-equipped, and turboprop commuter types. The primary objective was to measure DA trajectory prediction accuracy for use in validating DA metering advisories and developing conflict-probe error models. Previous evaluations, involving large jet types only, demonstrated an arrival time prediction accuracy within 20 sec. The 1995 test results indicate a mean error of 0.5 sec late with a standard deviation of 14.3 sec. The least variation was found for flight-management-systemequipped jets with a standard deviation of 11.9 sec compared to 15.2 and 15.4 sec for conventionalequipped jets and turboprop types respectively. This paper describes the test and presents an analysis of the descent trajectory prediction accuracy in terms of errors in the horizontal profile, altitude profile, and arrival time.

Preliminary investigation of trajectory prediction impact on decision support automation

“…Some efforts have been relatively comprehensive, examining a wide range of metrics or DSTs. [30][31][32][33] Most efforts have focused on specific aspects of the problem, such as in the presence of meteorological forecasting uncertainty, [34][35][36][37][38] in particular phases of flight, [39][40][41][42] due to departure uncertainty, [43] and improvements due to data link. [44][45][46] These research efforts have laid the groundwork toward a better understanding of how trajectory prediction impacts DST performance.…”

Lateral Intent Error’s Impact on Aircraft Prediction

“…These factors have been the subject of many scientific studies. In [5], the National Airspace Space Administration (NASA) ran aircraft field tests to verify the operational performance of its own TP. In a different study [6], researchers at the MITRE Corporation developed models to evaluate their DST's overall performance by utilizing accuracy statistics of their TP's performance.…”

A Perspective on NASA Ames Air Traffic Management Research

“…14,15 While flight management systems have been able to calculate idle descent paths for years, the challenge is to create paths that account for other traffic so that a controller does not have to suspend an efficient descent by requiring a level off. Accurate trajectory prediction is the key enabler, which is a challenge during descents, as altitude, speed, and course are all changing.…”