scholarly journals Network Characteristics Analysis of Air Traffic Management Technical Support System Based on Multi-source Weighting

2019 ◽  
Author(s):  
Kai Fan ◽  
Songchen Han ◽  
Wei Li ◽  
Lisha Yu ◽  
Jiayu Qual ◽  
...  
Keyword(s):  
Complex Network ◽  
Support System ◽  
Traffic Management ◽  
Small World ◽  
Air Traffic Management ◽  
Technical Support ◽  
Air Traffic ◽  
Clustering Coefficient ◽  
Weighted Network ◽  
Characteristics Analysis

In order to make reasonable suggestions for the expansion of the Air Traffic Management Technical Support System (ATMTSS), it is necessary to conduct a comprehensive analysis of the ATMTSS network. This paper constructs a multi-source weighted ATMTSS network which considers the working characteristics and geographical locations of the facilities. The complex network metrics, such as degree, node strength, clustering coefficient, average path length, diameter, and the improved Fast-Newman (FN) algorithm, are used in the analysis of the network. The results show that the ATMTSS network is a complex network with small-world characteristics and random characteristics, and that the distribution of ATMTSS network support capability is not the same as the topology network structure. The weighted network is looser than the non-weighted network. The air traffic management in remote areas is less affected by facilities than that in developed areas.

scholarly journals Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Hongyong Wang ◽  
Ziqi Song ◽  
Ruiying Wen
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Flow Characteristics ◽  
Air Traffic Management ◽  
Air Traffic ◽  
System Capacity ◽  
Traffic Situation ◽  
Flight Delays ◽  
Weighted Network ◽  
Potential Applications

In order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity research, no simple means is available to integrate airspace and traffic flow characteristics. In this paper, we propose a new approach for the measurement of air traffic situation complexity. This approach considers the effects of both airspace and traffic flow and objectively quantifies air traffic situation complexity. Considering the aircraft, waypoints, and airways as nodes, and the complexity relationships among these nodes as edges, a dynamic weighted network is constructed. Air traffic situation complexity is defined as the sum of the weights of all edges in the network, and the relationships of complexity with some commonly used indices are statistically analyzed. The results indicate that the new complexity index is more accurate than traffic count and reflects the number of trajectory changes as well as the high-risk situations. Additionally, analysis of potential applications reveals that this new index contributes to achieving complexity-based management, which represents an efficient method for increasing airspace system capacity.

Safety Culture and Safety-Relevant Behavior in Air Traffic Management

2015 ◽  
Vol 5 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Michaela Schwarz ◽  
K. Wolfgang Kallus
Keyword(s):  
Safety Culture ◽  
Traffic Management ◽  
Service Providers ◽  
Five Factor Model ◽  
Principal Component ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Psychometric Validation ◽  
Safety Attitudes ◽  
Culture Development

Since 2010, air navigation service providers have been mandated to implement a positive and proactive safety culture based on shared beliefs, assumptions, and values regarding safety. This mandate raised the need to develop and validate a concept and tools to assess the level of safety culture in organizations. An initial set of 40 safety culture questions based on eight themes underwent psychometric validation. Principal component analysis was applied to data from 282 air traffic management staff, producing a five-factor model of informed culture, reporting and learning culture, just culture, and flexible culture, as well as management’s safety attitudes. This five-factor solution was validated across two different occupational groups and assessment dates (construct validity). Criterion validity was partly achieved by predicting safety-relevant behavior on the job through three out of five safety culture scores. Results indicated a nonlinear relationship with safety culture scales. Overall the proposed concept proved reliable and valid with respect to safety culture development, providing a robust foundation for managers, safety experts, and operational and safety researchers to measure and further improve the level of safety culture within the air traffic management context.

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