An efficient genetic algorithm with uniform crossover for air traffic control

2009 ◽  
Vol 36 (1) ◽  
pp. 245-259 ◽  
Author(s):  
Xiao-Bing Hu ◽  
Ezequiel Di Paolo
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Air Traffic ◽  
Uniform Crossover

scholarly journals A Genetic Algorithm-based BP Neural Network Method for Operational Performance Assessment of ATC Sector

2016 ◽  
Vol 28 (6) ◽  
pp. 563-574 ◽  
Author(s):  
Jianping Zhang ◽  
Liwei Duan ◽  
Jing Guo ◽  
Weidong Liu ◽  
Xiaojia Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Performance Assessment ◽  
Bp Neural Network ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Back Propagation ◽  
Air Traffic ◽  
Operational Performance ◽  
Network Method

To assess operational performance of air traffic control sector, a multivariate detection index system consisting of 5 variables and 17 indicators is presented, which includes operational trafficability, operational complexity, operational safety, operational efficiency, and air traffic controller workload. An improved comprehensive evaluation method, is designed for the assessment by optimizing initial weights and thresholds of back propagation (BP) neural network using genetic algorithm. By empirical study conducted in one air traffic control sector, 400 sets of sample data are selected and divided into 350 sets for network training and 50 sets for network testing, and the architecture of genetic algorithm-based back propagation (GABP) neural network is established as a three-layer network with 17 nodes in input layer, 5 nodes in hidden layers, and 1 node in output layer. Further testing with both GABP and traditional BP neural network reveals that GABP neural network performs betterthan BP neural work in terms of mean error, mean square error and error probability, indicating that GABP neural network can assess operational performance of air traffic control sector with high accuracy and stable generalization ability. The multivariate detection index system and GABP neural network method in this paper can provide comprehensive, accurate, reliable and practical operational performance assessment of air traffic control sector, which enable the frontline of air traffic service provider to detect and evaluate operational performance of air traffic control sector in real time, and trigger an alarm when necessary.

Aeronautical Study for Flight Time Estimation Applying Artificial Neural Network and Genetic Algorithm

2014 ◽  
Vol 919-921 ◽  
pp. 1063-1074
Author(s):  
Yung Ching Lin ◽  
Lee Kuo Lin ◽  
Shao Hong Tsai
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Flight Time ◽  
Air Traffic ◽  
Artificial Neural

Since the adoption of open-air policy, people make more frequent use of air travel to do various business or tourism activities. The volume of air traffic has greatly increased, along with the occurrences of traffic jam in the air. Delays of landings or take-offs and the congestions in the approach air space have become commonplace, exacerbating the already heavy workload of air-traffic controllers and the inadequacies of ATC system. Therefore, a study of flight time in ATC operation to help alleviate airspace congestions has become more and more urgent and important. Taking international airway A1 as an example, this study makes use of the known entry time, flight altitude, speed, penetrating and descending as the input of artificial neural networks; the time between departure and transfer point as the output of Artificial Neural Networks, to establish artificial neural network. Applying artificial neural networks and genetic algorithm to the study to simulate the result of actual flight, one can precisely estimate the flight time, thereby making it an efficient air-traffic-control instrument. It can help controllers handle different time segments of air traffic, thus upgrading the quality of air traffic control service.

Workload Perception of Air Traffic Control Officers and Pilots During Continuous Descent Operations Approach Procedures

2019 ◽  
Vol 9 (1) ◽  
pp. 2-11
Author(s):  
Marina Efthymiou ◽  
Frank Fichert ◽  
Olaf Lantzsch
Keyword(s):  
Fuel Consumption ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Negative Impact ◽  
Air Traffic ◽  
Reduce Fuel Consumption ◽  
Total Load ◽  
Open Path

Abstract. The paper examines the workload perceived by air traffic control officers (ATCOs) and pilots during continuous descent operations (CDOs), applying closed- and open-path procedures. CDOs reduce fuel consumption and noise emissions. Therefore, they are supported by airports as well as airlines. However, their use often depends on pilots asking for CDOs and controllers giving approval and directions. An adapted NASA Total Load Index (TLX) was used to measure the workload perception of ATCOs and pilots when applying CDOs at selected European airports. The main finding is that ATCOs’ workload increased when giving both closed- and open-path CDOs, which may have a negative impact on their willingness to apply CDOs. The main problem reported by pilots was insufficient distance-to-go information provided by ATCOs. The workload change is important when considering the use of CDOs.

How to Evaluate Remote Tower Metrics in Connection With Weather Observations

2018 ◽  
Vol 8 (2) ◽  
pp. 100-111 ◽  
Author(s):  
Maik Friedrich ◽  
Christoph Möhlenbrink
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Influential Factors ◽  
Air Traffic ◽  
Weather Event ◽  
Evaluation Of Performance ◽  
Weather Events ◽  
Weather Observations ◽  
Validation Experiment ◽  
Remote Controller

Abstract. Owing to the different approaches for remote tower operation, a standardized set of indicators is needed to evaluate the technical implementations at a task performance level. One of the most influential factors for air traffic control is weather. This article describes the influence of weather metrics on remote tower operations and how to validate them against each other. Weather metrics are essential to the evaluation of different remote controller working positions. Therefore, weather metrics were identified as part of a validation at the Erfurt-Weimar Airport. Air traffic control officers observed weather events at the tower control working position and the remote control working position. The eight participating air traffic control officers answered time-synchronized questionnaires at both workplaces. The questionnaires addressed operationally relevant weather events in the aerodrome. The validation experiment targeted the air traffic control officer’s ability to categorize and judge the same weather event at different workplaces. The results show the potential of standardized indicators for the evaluation of performance and the importance of weather metrics in relation to other evaluation metrics.

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