scholarly journals Advanced squirrel algorithm‐trained neural network for efficient spectrum sensing in cognitive radio‐based air traffic control application

2021 ◽  
Author(s):  
Geoffrey Eappen ◽  
T. Shankar ◽  
Rajagopal Nilavalan
Keyword(s):  
Neural Network ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Air Traffic ◽  
Trained Neural Network ◽  
Control Application

scholarly journals A requirements capture method and its use in an air traffic control application

1995 ◽  
Vol 25 (1) ◽  
pp. 47-71 ◽  
Author(s):  
T. L. McCluskey ◽  
J. M. Porteous ◽  
Y. Naik ◽  
C. N. Taylor ◽  
S. Jones
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Air Traffic ◽  
Capture Method ◽  
Control Application

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.

Artificial Intelligence for Evaluating the Mental Workload of Air Traffic Controllers

2020 ◽  
pp. 184-212
Author(s):  
Tetiana Shmelova ◽  
Yuliya Sikirda
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Expert System ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Mental Workload ◽  
Air Traffic ◽  
Control Center ◽  
Air Traffic Controllers ◽  
And Control

In this chapter, the authors propose the application of artificial intelligence (namely expert system and neural network) for estimating the mental workload of air traffic controllers while working at different control centers (sectors): terminal control center, approach control center, area control center. At each air traffic control center, air traffic controllers will perform the following procedures: coordination between units, aircraft transit, climbing, and descending. So with the help of the artificial intelligence (AI) and its branches expert system and neural network, it is possible to estimate the mental workload of dispatchers for a different number of aircraft, compare the workload intensity of the air traffic control sectors, and optimize the workload between sectors and control centers. The differentiating factor of an AI system from a standard software system is the characteristic ability to learn, improve, and predict. Real dispatchers, students, graduate students, and teachers of the National Aviation University took part in these researches.

scholarly journals Probabilistic Prediction of Unsafe Event in Air Traffic Control Department Based on the Improved Backpropagation Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yong Liao ◽  
Zhiyang Miao ◽  
Changqi Yang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Safety Management ◽  
Mapping Method ◽  
Air Traffic ◽  
Occurrence Rate ◽  
Sigmoid Function ◽  
Control Department

Air traffic control is an important tool to ensure the safety of civil aviation. For the departments that do the work of air traffic control, reducing the percentage of unsafe event is the core task of safety management. If the relationship between the percentage of unsafe event and their influencing factors can be effectively clarified, then the probability of unsafe event in some control department can be predicted. So, it is of great importance to improve the level of safety management. To quantitatively estimate the probability of unsafe event, a three-layer BP neural network model is introduced in this paper. First, a probabilistic representation of unsafe event related to air traffic control department is made, and then, the probability of different classes of unsafe events and safe events is taken as the outputs of the BP neural network, the factors influencing occurrence of unsafe event connected with air traffic control is taken as inputs, and the sigmoid function is chosen as activation function for the hidden layer. Based on the error function of neural network, it is proved that the general BP neural network has two drawbacks when used for the training of small probability events, which are as follows: the pattern does not ensure that the sum of probability of all events is equal to one and the relative error between the actual outputs and desired outputs is very large after the training of neural network. The reason proved in this paper is that the occurrence rate of the unsafe event is much smaller than that of the safe event, resulting in each weight in the hide layer being subjected to the desired outputs of the safe event when using the gradient descent method for network training. To address this issue, a new mapping method is put forward to reduce the large difference of the desired outputs between the safe event and unsafe event. It is theoretically proved that the mapping method proposed in this paper can not only improve the training accuracy but also ensure that the sum of probability is equal to one. Finally, a numeric example is given to demonstrate that the method proposed in this paper is effective and feasible.

Research on Safety Comprehensive Assessment Method for Air Traffic Control Based on RBF Neural Network

2014 ◽  
Vol 989-994 ◽  
pp. 2671-2674
Author(s):  
Xu Sheng Gan ◽  
Hua Ping Li
Keyword(s):  
Neural Network ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Safety Assessment ◽  
Rbf Neural Network ◽  
Assessment Method ◽  
Air Traffic ◽  
Comprehensive Assessment ◽  
Assessment Index ◽  
Assessment Index System

To assess the safety situation in air traffic control effectively, a comprehensive assessment method based on RBF neural network is proposed. At first, the safety assessment principle based on RBF neural network is introduced, and then the safety assessment index system for air traffic control is established from four aspects of human, machine, environment and management. Simulation example of ATC safety assessment gives us a satisfactory result for RBF neural network.

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.

Sign in / Sign up

Export Citation Format

Share Document