국내 최대 기계 및 로봇 연구정보

기술보고서

기술보고서 게시판 내용
타이틀	Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments
저자	Lee, Paul U.;; Prevot, Thomas
Keyword	AIR TRAFFIC;; AIR TRAFFIC CONTROL;; AIRSPACE;; CONTROLLERS;; DATA TRANSMISSION;; ESTIMATING;; ROUTES;; TRAJECTORIES;; VOICE COMMUNICATION;; WORKLOADS (PSYCHOPHYSIOLOGY)
URL	http://hdl.handle.net/2060/20120016433
보고서번호	ARC-E-DAA-TN5578
발행년도	2012
출처	NTRS (NASA Technical Report Server)
ABSTRACT	Controller workload is a key factor in limiting en route air traffic capacity. Past efforts to quantify and predict workload have resulted in identifying objective metrics that correlate well with subjective workload ratings during current air traffic control operations. Although these metrics provide a reasonable statistical fit to existing data, they do not provide a good mechanism for estimating controller workload for future air traffic concepts and environments that make different assumptions about automation, enabling technologies, and controller tasks. One such future environment is characterized by en route airspace with a mixture of aircraft equipped with and without Data Communications (Data Comm). In this environment, aircraft with Data Comm will impact controller workload less than aircraft requiring voice communication, altering the close correlation between aircraft count and controller workload that exists in current air traffic operations. This paper outlines a new trajectory-based complexity (TBX) calculation that was presented to controllers during a human-in-the-loop simulation. The results showed that TBX accurately estimated the workload in a mixed Data Comm equipage environment and the resulting complexity values were understood and readily interpreted by the controllers. The complexity was represented as a "modified aircraft account" that weighted different complexity factors and summed them in such a way that the controllers could effectively treat them as aircraft count. The factors were also relatively easy to tune without an extensive data set. The results showed that the TBX approach is well suited for presenting traffic complexity in future air traffic environments.