107,734 research outputs found

    Using generalized stochastic method to evaluate probability of conflict in controlled air traffic

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    The introduction of the new concepts of air traffic management (ATM) and transition from centralized to decentralized air traffic control (ATC) with the change of traditional ATM to Cooperative ATM sets new tasks and opens new capabilities for air traffic safety systems. This paper is devoted to the problem of evaluating the probability of aircraft collision under the condition of Cooperative ATM, when the necessary information is available to the subjects involved in the decision‐making process. The generalized stochastic conflict probability evaluation method is developed. This method is based on the generalized conflict probability equation for evaluation of potential conflict probability and aircraft collision probability that is derived by taking into account stochastic nature and time correlation of deviation from planned flight trajectory in controlled air traffic. This equation is described as a multi‐dimensional parabolic partial differential equation using a differential (infinitesimal) operator of the multi‐dimensional stochastic process of relative aircraft movement. The common procedure for the prediction of conflict probability is given, and the practical application of the generalized method presented is shown. All equational coefficients of a differential operator for a practical solution of a parabolic partial differential equation are derived. For some conditions, the numerical solution of the conflict probability equation is obtained and illustrated graphically. First published online: 14 Oct 201

    Bayesian learning of models for estimating uncertainty in alert systems: application to air traffic conflict avoidance

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    Alert systems detect critical events which can happen in the short term. Uncertainties in data and in the models used for detection cause alert errors. In the case of air traffic control systems such as Short-Term Conflict Alert (STCA), uncertainty increases errors in alerts of separation loss. Statistical methods that are based on analytical assumptions can provide biased estimates of uncertainties. More accurate analysis can be achieved by using Bayesian Model Averaging, which provides estimates of the posterior probability distribution of a prediction. We propose a new approach to estimate the prediction uncertainty, which is based on observations that the uncertainty can be quantified by variance of predicted outcomes. In our approach, predictions for which variances of posterior probabilities are above a given threshold are assigned to be uncertain. To verify our approach we calculate a probability of alert based on the extrapolation of closest point of approach. Using Heathrow airport flight data we found that alerts are often generated under different conditions, variations in which lead to alert detection errors. Achieving 82.1% accuracy of modelling the STCA system, which is a necessary condition for evaluating the uncertainty in prediction, we found that the proposed method is capable of reducing the uncertain component. Comparison with a bootstrap aggregation method has demonstrated a significant reduction of uncertainty in predictions. Realistic estimates of uncertainties will open up new approaches to improving the performance of alert systems

    Formulating the cognitive design problem of air traffic management

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    Evolutionary approaches to cognitive design in the air traffic management (ATM) system can be attributed with a history of delayed developments. This issue is well illustrated in the case of the flight progress strip where attempts to design a computer-based system to replace the paper strip have consistently been met with rejection. An alternative approach to cognitive design of air traffic management is needed and this paper proposes an approach centred on the formulation of cognitive design problems. The paper gives an account of how a cognitive design problem was formulated for a simulated ATM task performed by controller subjects in the laboratory. The problem is formulated in terms of two complimentary models. First, a model of the ATM domain describes the cognitive task environment of managing the simulated air traffic. Second, a model of the ATM worksystem describes the abstracted cognitive behaviours of the controllers and their tools in performing the traffic management task. Taken together, the models provide a statement of worksystem performance, and express the cognitive design problem for the simulated system. The use of the problem formulation in supporting cognitive design, including the design of computer-based flight strips, is discussed

    How to monitor sustainable mobility in cities? Literature review in the frame of creating a set of sustainable mobility indicators

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    The role of sustainable mobility and its impact on society and the environment is evident and recognized worldwide. Nevertheless, although there is a growing number of measures and projects that deal with sustainable mobility issues, it is not so easy to compare their results and, so far, there is no globally applicable set of tools and indicators that ensure holistic evaluation and facilitate replicability of the best practices. In this paper, based on the extensive literature review, we give a systematic overview of relevant and scientifically sound indicators that cover different aspects of sustainable mobility that are applicable in different social and economic contexts around the world. Overall, 22 sustainable mobility indicators have been selected and an overview of the applied measures described across the literature review has been presented

    Guidelines for the Use of Synthetic Fluid Dust Control Palliatives on Unpaved Roads

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    The amount of small soil particles, dust, lost from typical unpaved roads to fugitive dust is staggering. A 1 km stretch of unpaved road can contribute over 2400 kg of dust to the atmosphere (4.2 ton/mile) in a typical 3-month summer season. Road managers typically manage dust from unpaved roads with various dust-control palliatives, which are effective for up to 1 year. Synthetic fluids are a relatively new category of dust-control palliatives. Unlike the more commonly used dust-control palliatives, such as salts, engineering guidelines do not exist for the application and maintenance of synthetic fluids on unpaved roads. To fill this void, we present through this document guidelines for road design and maintenance, palliative selection, application, and care of synthetic fluid-treated roadways.Midwest Industrial Supply United States Department of TransportationReport Documentation Page .............................................................................................. ii Disclaimer ......................................................................................................................... iii List of Figures .................................................................................................................... vi Executive Summary............................................................................................................. 1 CHAPTER 1.0 – Introduction............................................................................................... 4 CHAPTER 2.0 – Background.............................................................................................. 6 Measurements of the Effectiveness of Dust Palliatives .....................................................10 CHAPTER 3.0 – Guidelines .............................................................................................. 16 Road Design and Maintenance...........................................................................................16 Palliative Selection..............................................................................................................20 Application .........................................................................................................................22 Areas Requiring Special Attention......................................................................................26 Maintenance .......................................................................................................................27 CHAPTER 4.0 – Summary................................................................................................. 31 CHAPTER 5.0 – References.............................................................................................. 3

    A Simulation Framework for Fast Design Space Exploration of Unmanned Air System Traffic Management Policies

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    The number of daily small Unmanned Aircraft Systems (sUAS) operations in uncontrolled low altitude airspace is expected to reach into the millions. UAS Traffic Management (UTM) is an emerging concept aiming at the safe and efficient management of such very dense traffic, but few studies are addressing the policies to accommodate such demand and the required ground infrastructure in suburban or urban environments. Searching for the optimal air traffic management policy is a combinatorial optimization problem with intractable complexity when the number of sUAS and the constraints increases. As the demands on the airspace increase and traffic patterns get complicated, it is difficult to forecast the potential low altitude airspace hotspots and the corresponding ground resource requirements. This work presents a Multi-agent Air Traffic and Resource Usage Simulation (MATRUS) framework that aims for fast evaluation of different air traffic management policies and the relationship between policy, environment and resulting traffic patterns. It can also be used as a tool to decide the resource distribution and launch site location in the planning of a next-generation smart city. As a case study, detailed comparisons are provided for the sUAS flight time, conflict ratio, cellular communication resource usage, for a managed (centrally coordinated) and unmanaged (free flight) traffic scenario.Comment: The Integrated Communications Navigation and Surveillance (ICNS) Conference in 201

    Introducing the STAMP method in road tunnel safety assessment

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    After the tremendous accidents in European road tunnels over the past decade, many risk assessment methods have been proposed worldwide, most of them based on Quantitative Risk Assessment (QRA). Although QRAs are helpful to address physical aspects and facilities of tunnels, current approaches in the road tunnel field have limitations to model organizational aspects, software behavior and the adaptation of the tunnel system over time. This paper reviews the aforementioned limitations and highlights the need to enhance the safety assessment process of these critical infrastructures with a complementary approach that links the organizational factors to the operational and technical issues, analyze software behavior and models the dynamics of the tunnel system. To achieve this objective, this paper examines the scope for introducing a safety assessment method which is based on the systems thinking paradigm and draws upon the STAMP model. The method proposed is demonstrated through a case study of a tunnel ventilation system and the results show that it has the potential to identify scenarios that encompass both the technical system and the organizational structure. However, since the method does not provide quantitative estimations of risk, it is recommended to be used as a complementary approach to the traditional risk assessments rather than as an alternative. (C) 2012 Elsevier Ltd. All rights reserved

    Inverse Optimal Planning for Air Traffic Control

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    We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around commercial airports. We develop a method to learn the rules of air traffic control from real data as a cost function via maximum entropy inverse reinforcement learning. This cost function is used as a penalty for a search-based motion planning method that discretizes both the control and the state space. We illustrate the methodology by showing that our approach can learn to imitate the airport arrival routes and separation rules of dense commercial air traffic. The resulting trajectories are shown to be safe, feasible, and efficient
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