To update the current state of evidence and assess its quality, we conducted a systematic review on the effects of environmental noise exposure on the cardio-metabolic systems as input for the new ...WHO environmental noise guidelines for the European Region. We identified 600 references relating to studies on effects of noise from road, rail and air traffic, and wind turbines on the cardio-metabolic system, published between January 2000 and August 2015. Only 61 studies, investigating different end points, included information enabling estimation of exposure response relationships. These studies were used for meta-analyses, and assessments of the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE). A majority of the studies concerned traffic noise and hypertension, but most were cross-sectional and suffering from a high risk of bias. The most comprehensive evidence was available for road traffic noise and Ischeamic Heart Diseases (IHD). Combining the results of 7 longitudinal studies revealed a Relative Risk (RR) of 1.08 (95% CI: 1.01-1.15) per 10 dB (L
) for the association between road traffic noise and the incidence of IHD. We rated the quality of this evidence as high. Only a few studies reported on the association between transportation noise and stroke, diabetes, and/or obesity. The quality of evidence for these associations was rated from moderate to very low, depending on transportation noise source and outcome. For a comprehensive assessment of the impact of noise exposure on the cardiovascular and metabolic system, we need more and better quality evidence, primarily based on longitudinal studies.
Visuospatial attention is a cognitive skill essential to the performance of air traffic control activities. We evaluated the effect of an anodic session of transcranial low-intensity direct current ...stimulation (tDCS) right parietal associated with cognitive training of visuospatial attention of 21 air traffic controllers. Within-subject designs were used, with all volunteers undergoing two tDCS sessions; an experimental (2 mA anodic) and control (sham) performed concomitantly with the cognitive training (2-Back). Visuospatial performance was measured using the Attention Network Test for Interactions and Vigilance pre- and post-intervention. The results indicate that after an active parietal tDCS session, the ATCOs showed faster responses, but not more accurate, for visuospatial attention in its aspects of orientation and reorientation. This result was significant when comparing baseline and post-tests in the active tDCS group. Comparing the post-tests between the tDCS active and sham groups, it is possible to infer a trend of improvement in the results based on faster and more accurate responses, which suggests a possible refinement of the ATCO’s attentional orientation. However, this population may eventually have reached a plateau in the performance of this skill. From the analysis of the results we arrive at the following hypotheses: (I) the increase in cortical excitability mediated by anodic tDCS frequently recorded may not be accompanied by improvements in behavioural measures; (II) the interaction between anodic tDCS with another event of increased excitability—execution of a cognitive task, may have hindered the occurrence of neuroplasticity; (III) the air traffic control activity may be associated with a high level of attention, which may have contributed to a ceiling effect for the development of this skill; (IV) online assessments may be more relevant to identify acute effects; (V) repeated sessions may be more efficient to find cumulative effects; (VI) the analysis of interactions between attentional networks can contribute to the study of visuospatial attention; (VII) tDCS protocols aimed at ATCO need to consider the specifics of this audience, such as circadian rhythm and sleep and fatigue conditions.
Timely and efficient air traffic flow management (ATFM) is a key issue in future dense air traffic. The emerging demands for unmanned aerial vehicles and general aviation aircraft aggravate the ...burden of the ATFM. Thanks to the advanced automatic dependent surveillance-broadcast (ADS-B) technique, the aerial vehicles can be tracked and monitored in a real-time and accurate manner, providing possibility for establishing a more intelligent ATFM architecture. In this article, we first form an aviation Big Data platform by using the distributed ADS-B ground stations and the obtained ADS-B messages. By exploring the constructed dataset and mapping the extracted information to the routes, the air traffic flow between different cities can be counted and predicted, where the prediction task is implemented on the basis of two machine learning methods, respectively. The experimental results based on real-world data demonstrate that the proposed traffic flow prediction model adopting long short-term memory (LSTM) can achieve better performance, especially when abnormal factors in traffic control are considered.
The European air traffic network (ATN), consisting of a set of airports and area control centres, is highly complex. The current indicator of its performance, air traffic flow management delays, is ...insufficient for planning and management purposes. Topological analysis of ATNs of this kind has highlighted betweenness centrality (BC) as an indicator of network robustness, although such an indicator assumes no knowledge of actual traffic flows and the network's operational characteristics. This paper conducts topological and operational analyses of the European ATN in order to derive a more relevant and appropriate indicator of robustness. By applying a flow maximisation model to the network influenced by a range of capacity reductions at the local level, we propose a new index called the Relative Area Index (RAI). The RAI quantifies the importance of an individual node relevant to the performance of the entire network when it suffers from capacity reduction at a local scale. Air traffic data from three typical busy days in Europe are utilised to show that the RAI is more flexible and capable than BC in capturing the network impact of local capacity degradation. This index can be used to assess network robustness and provide a valuable tool for airspace managers and planners.
•An innovative collaborative air traffic flow management framework is introduced in the scope of the future trajectory based operations paradigm.•An interactive trajectory design process is proposed ...between the airspace users and the air traffic flow management authority aligned with the collaborative decision-making mechanisms.•An integrated linear optimization model is presented, which incorporates all the possible options resulted from the previous interactive trajectory design process.•Real-world operational data are collected and processed in a case study to provide a realistic assessment of the framework for a typical operational day.
This paper proposes a collaborative air traffic flow management (ATFM) framework, in the scope of trajectory based operations, aiming to improve the cost-efficiency for airspace users (AUs) when facing ATFM regulations. The framework consists of four modules. The first one involves the AUs initially scheduling their preferred trajectories for all their flights. Based on this initial demand, the second module (assumed to be on the Network Manager -NM- side) detects time-varying hotspots (i.e. overloaded sectors along the day). In the third module, hotspot information is shared back to the AUs who plan alternative trajectory options to avoid crossing these congested airspace volumes (in the lateral and vertical domain); as well as providing to the NM different pre-tactical delay management preferences (including ground holding, linear holding, air holding and pre-tactical delay recovery); based on their internal cost breakdown structures. Incorporating all these potential combined options, the last module computes the best trajectory selections and the optimal distribution of delay assignments, such that the cost deviation from the initial status (all the user-preferred trajectories) is minimized. This model is formulated as mixed integer linear programming (MILP) and validated by a real-world case study focused on 24 h of traffic over the French airspace. Results using the proposed framework suggest a significant system delay reduction by nearly 97% over the existing method, whilst yielding an average of less than 100 kg extra fuel consumption and 50 Euro extra route charges for the 11% flights diverted to their alternative trajectories.
Air traffic management (ATM) is facing a tremendous increase in the amount of available flight data, particularly four-dimensional (4D) trajectories. Computational requirements for analysis and ...storage of such bulk of data are steeply increasing. Compression is one key technology to address this challenge. In this paper we propose two techniques for compressing air traffic 4D trajectories. Our first technique analyzes a set of samples and computes a prediction for the most likely picked successor coordinate by a random walker. The second technique, i.e., referential compression, compresses a 4D trajectory as a collection of subtrajectory pointers into a reference trajectory. We evaluate our algorithms on trajectory data from the Demand Data Repository provided by EUROCONTROL. We show that a combination of our referential and statistical compression techniques compresses 4D trajectories of all air traffic over Europe in the year 2013 from 60 GB down to 0.78 GB, achieving a compression ratio of more than 75 : 1. The compression ratio for our techniques increases with the number of to-be-compressed flights, whereas standard compression techniques achieve a fixed compressed ratio for any number of flights. Our work contributes toward efficient handling of the increasing amount of traffic data in ATM.
Visualizing 3D trajectories to extract insights about their similarities and spatial configuration is a critical task in several domains. Air traffic controllers for example deal with large ...quantities of aircrafts routes to optimize safety in airspace and neuroscientists attempt to understand neuronal pathways in the human brain by visualizing bundles of fibers from DTI images. Extracting insights from masses of 3D trajectories is challenging as the multiple three dimensional lines have complex geometries, may overlap, cross or even merge with each other, making it impossible to follow individual ones in dense areas. As trajectories are inherently spatial and three dimensional, we propose FiberClay: a system to display and interact with 3D trajectories in immersive environments. FiberClay renders a large quantity of trajectories in real time using GP-GPU techniques. FiberClay also introduces a new set of interactive techniques for composing complex queries in 3D space leveraging immersive environment controllers and user position. These techniques enable an analyst to select and compare sets of trajectories with specific geometries and data properties. We conclude by discussing insights found using FiberClay with domain experts in air traffic control and neurology.
Today, aircraft demand is exceeding the capacity of the Air Traffic Control (ATC) system. As a result, airspace is becoming a very complex environment to control. The complexity of airspace is thus ...closely related to the workload of controllers and is a topic of great interest. The major concern is that variables that are related to complexity are currently recognised, but there is still a debate about how to define complexity. This paper attempts to define which variables determine airspace complexity. To do so, a novel methodology based on the use of machine learning models is used. In this way, it tries to overcome one of the main disadvantages of the current complexity models: the subjectivity of the models based on expert opinion. This study has determined that the main indicator that defines complexity is the number of aircraft in the sector, together with the occupancy of the traffic flows and the vertical distribution of aircraft. This research can help numerous studies on both air traffic complexity assessment and Air Traffic Controller (ATCO) workload studies. This model can also help to study the behaviour of air traffic and to verify that there is symmetry in structure and the origin of the complexity in the different ATC sectors. This would have a great benefit on ATM, as it would allow progress to be made in solving the existing capacity problem.
Fast simulation technology is very important to explore the consequences of air traffic management decision. Although a variety of simulation tools have been developed to make decisions for air ...traffic controllers, the cognitive process of air traffic controllers is not effectively integrated into these tools. This article studies a probabilistic cellular automata (CA) model for air traffic flow simulation. By introducing the safety distance parameter into the CA model, the equilibrium property of air traffic system is studiedusing the statistical physics method. The simulation results show that the data are in good agreement with the measured results.
We discuss a widely used air traffic flow management formulation. We show that this formulation can lead to a solution where air delays are assigned to flights during their take-off which is ...prohibited in practice. Although air delay is more expensive than ground delay, the model may assign air delay to a few flights during their take-off to save more on not having as much ground delay. We present a modified formulation and verify its functionality in avoiding incorrect solutions.
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