969 resultados para Air traffic controllers.


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Mode of access: Internet.

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Air Traffic Control Laboratory Simulator (ATC-lab) is a new low- and medium-fidelity task environment that simulates air traffic control. ATC-lab allows the researcher to study human performance of tasks under tightly controlled experimental conditions in a dynamic, spatial environment. The researcher can create standardized air traffic scenarios by manipulating a wide variety of parameters. These include temporal and spatial variables. There are two main versions of ATC-lab. The medium-fidelity simulator provides a simplified version of en route air traffic control, requiring participants to visually search a screen and both recognize and resolve conflicts so that adequate separation is maintained between all aircraft. The low-fidelity simulator presents pairs of aircraft in isolation, controlling the participant's focus of attention, which provides a more systematic measurement of conflict recognition and resolution performance. Preliminary studies have demonstrated that ATC-lab is a flexible tool for applied cognition research.

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Inscriptions: Verso: [stamped] Photograph by Freda Leinwand. [463 West Street, Studio 229G, New York, NY 10014].

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Inscriptions: Verso: [stamped] Photograph by Freda Leinwand. [463 West Street, Studio 229G, New York, NY 10014].

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Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

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This paper proposes an en route speed reduction to complement current ground delay practices in air traffic flow management. Given a nominal cruise speed, there exists a bounded range of speeds that allows aircraft to fly slower with the same or lower fuel consumption than the nominal flight. Therefore, flight times are increased and delay can be partially performed in the air, at no extra fuel cost for the operator. This concept has been analyzed in an initial feasibility study, computing the maximum amount of delay that can be performed in the air in some representative flights. The impact on fuel consumption has been analyzed, and two scenarios are proposed: the flight fuel remains the same as in the nominal flight, and some extra fuel allowance is permitted in order to face uncertainties. Results show significant values of airborne delay that may be useful in many situations, with the exception of short hauls where airborne delay may be too short. If cruise altitude is changed, the amount of airborne delay increases, since changes in cruise speed modify the optimal flight altitudes. From the analyzed flights, a linear dependency is found relating the airborne delay with the amount of extra fuel allowance.

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The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

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The automation of various aspects of air traffic management has many wide-reaching benefits including: reducing the workload for Air Traffic Controllers; increasing the flexibility of operations (both civil and military) within the airspace system through facilitating automated dynamic changes to en-route flight plans; ensuring safe aircraft separation for a complex mix of airspace users within a highly complex and dynamic airspace management system architecture. These benefits accumulate to increase the efficiency and flexibility of airspace use(1). Such functions are critical for the anticipated increase in volume of manned and unmanned aircraft traffic. One significant challenge facing the advancement of airspace automation lies in convincing air traffic regulatory authorities that the level of safety achievable through the use of automation concepts is comparable to, or exceeds, the accepted safety performance of the current system.

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Future air traffic management concepts often involve the proposal of automated separation management algorithms that replaces human air traffic controllers. This paper proposes a new type of automated separation management algorithm (based on the satisficing approach) that utilizes inter-aircraft communication and a track file manager (or bank of Kalman filters) that is capable of resolving conflicts during periods of communication failure. The proposed separation management algorithm is tested in a range of flight scenarios involving during periods of communication failure, in both simulation and flight test (flight tests were conducted as part of the Smart Skies project). The intention of the conducted flight tests was to investigate the benefits of using inter-aircraft communication to provide an extra layer of safety protection in support air traffic management during periods of failure of the communication network. These benefits were confirmed.

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Both perceived organizational support and job stresses have impact on employees’ work outcomes. Great progresses have been made in past researches. However, there are many disputes about the impact of perceived organizational support (POS) on job performance (especially, safety performance), the impact of job stresses on job performance (especially, safety performance) and job attitudes, as well as the interaction of subordinates’ POS and job stresses, and the impact of supervisor on subordinates’ POS et al.. Thus, the aim of the study is to explore the impact of supervisors’ POS, leader-member exchange(LMX) on subordinates’ POS, the direct impact of subordinates’ POS and job stressors from task and rewards on work attitudes(job satisfaction, turnover intention) and safety behaviors(safety compliance and safety participation), and the interaction of subordinates’ POS and job stresses. Analyses are based on the data from interviewing of 20 staff, posts of a Chinese civil aviation Bulletin Board System (BBS) and surveys of 216 subordinates and 42 supervisors from two Chinese civil aviation Air traffic control centers (ATC). The major findings are listed as follows: Firstly, the exchange relationship between supervisors and members has impact on subordinates’ POS by the fully mediating role of subordinates’ perceived supervisor support (PSS). But supervisors’ POS have no impact on subordinates’ POS. Secondly, subordinates’ POS has a direct and positive impact on their job satisfaction and safety behaviors, and a negative impact on turnover intention. Specifically, the higher the employees’ perceived organizational support, the higher job satisfaction and safety behaviors, as well as the lower turnover intention they have. Moreover, POS has stronger relationship with safety participation behaviors than that of safety compliance behaviors. Thirdly, task-related stressor has no significant impact on job satisfaction, turnover intention and safety behaviors. And compensation-related stressor has significant and positive impact on turnover intention and safety behaviors, which means that with the compensation-related stress increases, turnover intention increases, safety behaviors including safety compliance and safety participation also increases. Fourthly, POS and task-related stressor, POS and compensation-related stressor have significant interaction, respectively. Specifically, POS moderates the relationship between task-related stressor and job satisfaction, and between task-related stressor and turnover intention. Moreover, POS also moderates the relationship between compensation-related stressor and safety compliance behaviors.