Calculation Of Air Traffic Controller Workload Based On Traffic Characteristics Of The Sector

The performance of the air traffic controller (ATCer) has been a direct impact factor on air traffic safety and efficiency of the operation, it also plays a very important role on the safety of the aircraft. The level of the ATC workload has been a relatively hot topic, and the problem of how accurate calculate and reflect the level of the ATCer’s workload has been a focus of the human factors research in air traffic management. Currently, the calculation and assessment studies of the controller’s workload level mainly has two ways:questionnaire and investigation methods. With investigation method, the complexity problem of the sector is the basic issue in calculating the workload level of controllers. In many researches of the sector complexity studies, the number of the aircraft always be the biggest, important and unique factor, to some extent, it maybe reflect part of the ATCer’s workload. However, the existing literature and researches suggest that the method of aircraft calculation of the sector did not consider the static factors of the sector which may be has a correlation relationship between the sector complexity factors, and it cannot be a real and effective calculation to assess the workload level of the ATCer.In this paper, sector complexity has been divided into static sector factors and dynamic sector factors, on this basis, it got a set of basic sector variables, with the ATC_lab experimental radar control plant, controllers take part in the simulate experiment. When finished, we use those two kinds of sector complexity basic variables to establish linear and nonlinear mathematical models to compute the controller’s workload, to get a more accurate calculations and assessments of the ATCer’s workload.With three kinds of different static complexity sectors, participates need to finish those three different radar control tasks with difficulty scenarios, then the author built two mathematical models to establish the workload level assessment methods under different complexity variables of control scenarios. The result shows that, under the combination of static and dynamic sector complexity factors, the predict model has a better predict effect than that with a separate dynamic sector complexity factors. And in nonlinear predict model, it shows a better validity to predict the level of the ATCer’s workload than the linear predict model. Comparative results showed that, the ATCer’s workload predict model of nonlinear method based on the static and dynamic sector complexity factors has a better predict ability, and can be more accurate on the assessment of the controller’s workload.