Controller workload prediction method and system based on multiple regression model

Abstract

The invention discloses a controller workload prediction method and system. The controller workload prediction method comprises the steps of building a multiple regression model according to controller workload prediction related indexes and controller workload prediction sample data; importing air traffic flow situation index prediction data in a controlled sector into the multiple regression model, and obtaining a controller workload prediction result. According to the controller workload prediction method and system, the air traffic flow situation multidimensional indexes which influence controller workload are considered completely and comprehensively, and thereby effective prediction for controller workload is achieved. The designed controller workload prediction system can be applied to an engineering unit and has great operability.

Description

technical field [0001] The invention relates to the monitoring field, in particular to a controller workload prediction method and system. Background technique [0002] With the development of the air transport industry, in order to ensure the safety and order of various flight activities, the air traffic control service came into being and was continuously developed and improved until it became mature in the 1980s. The main content of modern air traffic control services is: Air traffic controllers (referred to as "controllers", the same below) rely on modern communication, navigation, and surveillance technologies to manage and control aircraft under their jurisdiction, coordinate and guide their movement paths and Mode to prevent collisions between aircraft in the air and collisions between aircraft and obstacles in the maneuvering area of ​​the airport, and maintain and speed up the orderly flow of air traffic. The executor of this task is the air traffic controller (abb...

AI Technical Summary

Problems solved by technology

[0009] At present, the relevant research content of controller workload prediction mainly has the following deficiencies: (1) In terms of research methods, there are more qualitative research and less quantitative research, resulting in insufficient objectivity

(2) In terms of research indicators, most of them start with the indicators that directly reflect the controller's workload, and less consider the influencing factor indicators of the controller's workload. The index dimension is relatively single, not comprehensive and comprehensive, and the prediction reliability is not high

(3) In terms of applicability, the existing research is still at the stage of laboratory research, mainly serving strategic decision-making, while there are few actual engineering applications for air traffic control units

Due to the above deficiencies, the current domestic and foreign research on controller workload prediction is lacking in objectivity, comprehensiveness, comprehensiveness, accuracy and operability.

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