scholarly journals Deep Behavioral Cloning for Traffic Control with Virtual Expert Demonstration Under a Parallel Learning Framework

2020 ◽  
Vol 53 (5) ◽  
pp. 176-181
Author(s):  
Xiaoshuang Li ◽  
Fenghua Zhu ◽  
Fei-Yue Wang
Keyword(s):  
Traffic Control ◽  
Parallel Learning ◽  
Learning Framework ◽  
Virtual Expert ◽  
Behavioral Cloning

scholarly journals Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

2018 ◽  
Author(s):  
Bing Yu ◽  
Haoteng Yin ◽  
Zhanxing Zhu
Keyword(s):  
Deep Learning ◽  
Traffic Control ◽  
Time Series Prediction ◽  
Urban Traffic ◽  
Traffic Forecasting ◽  
Convolutional Networks ◽  
Learning Framework ◽  
Temporal Correlations ◽  
Temporal Graph ◽  
Spatio Temporal

Timely accurate traffic forecast is crucial for urban traffic control and guidance. Due to the high nonlinearity and complexity of traffic flow, traditional methods cannot satisfy the requirements of mid-and-long term prediction tasks and often neglect spatial and temporal dependencies. In this paper, we propose a novel deep learning framework, Spatio-Temporal Graph Convolutional Networks (STGCN), to tackle the time series prediction problem in traffic domain. Instead of applying regular convolutional and recurrent units, we formulate the problem on graphs and build the model with complete convolutional structures, which enable much faster training speed with fewer parameters. Experiments show that our model STGCN effectively captures comprehensive spatio-temporal correlations through modeling multi-scale traffic networks and consistently outperforms state-of-the-art baselines on various real-world traffic datasets.

Cost-Sensitive Parallel Learning Framework for Insurance Intelligence Operation

2019 ◽  
Vol 66 (12) ◽  
pp. 9713-9723 ◽  
Author(s):  
Xinxin Jiang ◽  
Shirui Pan ◽  
Guodong Long ◽  
Fei Xiong ◽  
Jing Jiang ◽  
...  
Keyword(s):  
Parallel Learning ◽  
Learning Framework

Short-Term Auditory Memory, Oral Perception, and Experimental Sound Learning

1969 ◽  
Vol 12 (1) ◽  
pp. 185-192 ◽  
Author(s):  
John L. Locke
Keyword(s):  
Memory Span ◽  
Auditory Memory ◽  
Span Task ◽  
Short Term ◽  
Learning Framework ◽  
Sound Learning ◽  
Oral Perception

Ten children with high scores on an auditory memory span task were significantly better at imitating three non-English phones than 10 children with low auditory memory span scores. An additional 10 children with high scores on an oral stereognosis task were significantly better at imitating two of the three phones than 10 children with low oral stereognosis scores. Auditory memory span and oral stereognosis appear to be important subskills in the learning of new articulations, perhaps explaining their appearance in the literature as “etiologies” of disordered articulation. Although articulation development and the experimental acquisition of non-English phones have certain obvious differences, they seem to share some common processes, suggesting that the sound learning framework may be an efficacious technique for revealing otherwise inaccessible information.

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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