Analysis of Current Sectors Based on Traffic and Geometry

This paper desc ribes an evaluation of current sectors in the continental United States using a variety of traffic and geometric metrics. Most of the metrics have been computed using real track -data. In instances where this was not possible, s imulated traffic data are use d. Statistics of these metrics are summarized for higher altitude sectors in the twenty air route tr affic control centers and in eight geographical regions . The analysis shows that most sectors have fewer than twenty aircraft and three conflicts at any giv en time. Air traff ic in higher altitude sectors consists of mostly jets that fly in a narrow range of airspeeds and altitudes. A wide variation was found in the volume, area, height, length and transit times of the sectors. Most sectors were found to be el ongated and aligned in the direction of the traffic flows. The properties of today's sectors reflect the technologies and procedures used for air traffic control. With the introduction of automation, the design of airspace partitions will not be contrained by how controllers manage traffic. However, if controllers are involved to some degree in the future system, it might be useful to account for some of the characteristics of the current sectors in the design of future airspace partitions. I. Introductio n n the current national airspace system, design of sectors have evolved over a long period of time based on incremental addition of new technologies and procedures for air traffic control. Each sector has a fixed capacity. When these capacities are exce eded by traffic demand, traffic flows are restriced to bring the demand below capacity. The concept in Ref. 1 suggests that instead of restricting tr affic , which causes delays, airspace capacity can be increased by partitioning the airspace differently. Mo tivated by this concept, s everal methods for airspace partitioning that are described in Refs. 2 through 6 have been developed. These methods use some measure of controller workload to guide the design . In the future, with increased level of automation, ai rspace design might not be guided by controller workload considerations. Depending on how different the future design is from the current design, the controller's ability to actively separate aircraft might be limited. It might be useful to carry some of t he design features of the current system into the future one, if some role for human controller is envisioned in the future air traffic control system. The motivation for computing metrics for the existing sectors is to capture some of the design features of the current sectors. Since the design of current sectors is based on the routes of flight and controller workload considerations , metrics related to controller workload can be expected to capure the design features. There are numerous traffic and geom etry metrics described in the literature that have been found to be useful for modeling controller's perception of workload and in operational error studies. 7-11 These studies are limited to sectors in few centers. A comprehensive study of sectors in all t he twenty centers is unavailable. In this paper, thirty -three traffic and geometric metrics from Ref s. 7 to 11 are computed for 364 higher al titude sectors in each of the twenty centers, and in eight geographical regions. Higher altitude sectors were chos en because the benefits of airspace partitioning are expected to be realized in these sectors first. Data presented in this paper describes the design of the current sectors and will be found to be useful for comparing the designs of future airspace partit ions

Modeling and predicting mental workload in en route air traffic control: Critical review and broader implications

Objective: We perform a critical review of research on mental workload in en route air traffic control (ATC). We present a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems. Background: Air traffic volume is increasing worldwide. If air traffic management organizations are to meet future demand safely, better models of controller workload are needed. Method: We present the theoretical model and then review investigations of how effectively traffic factors, airspace factors, and operational constraints predict controller workload. Results: Although task demand has a strong relationship with workload, evidence suggests that the relationship depends on the capacity of the controllers to select priorities, manage their cognitive resources, and regulate their own performance. We review research on strategies employed by controllers to minimize the control activity and information-processing requirements of control tasks. Conclusion: Controller workload will not be effectively modeled until controllers' strategies for regulating the cognitive impact of task demand have been modeled. Application: Actual and potential applications of our conclusions include a reorientation of workload modeling in complex work systems to capture the dynamic and adaptive nature of the operator's work. Models based around workload regulation may be more useful in helping management organizations adapt to future control regimens in complex work systems