An Analysis of the Spatio-Temporal Factors Affecting Aircraft Conflicts Based on Simulation Modelling

The demand for air travel worldwide continues to grow at a rapid rate, especially in Europe and the United States. In Europe, the demand exceeded predictions with a real annual growth of 7.1% in the period 1985-1990, against a prediction of 2.4%. By the year 2010, the demand is expected to double from the 1990 level. Within the UK international scheduled passenger traffic is predicted to increase, on average, by 5.8 per cent per year between 1999 and 2003. The demand has not been matched by availability of capacity. In Western Europe many of the largest airports suffer from runway capacity constraints. Europe also suffers from an en-route airspace capacity constraint, which is determined by the workload of the air traffic controllers, i.e. the physical and mental work that controllers must undertake to safely conduct air traffic under their jurisdiction through en-route airspace. The annual cost to Europe due to air traffic inefficiency and congestion in en-route airspace is estimated to be 5 billion US Dollars, primarily due to delays caused by non-optimal route structures and reduced productivity of controllers due to equipment inefficiencies. Therefore, to in order to decrease the total delay, an increase in en-route capacity is of paramount importance. At a global scale and in the early 1980s, the International Civil Aviation Organisation (ICAO) recognised that the traditional air traffic control (ATC) systems would not cope with the growth in demand for capacity. Consequently new technologies and procedures have been proposed to enable ATC to cope with this demand, e.g. satellite-based system concept to meet the future civil aviation requirements for communication, navigation and surveillance/ air traffic management (CNS/ATM). In Europe, the organisation EUROCONTROL (established in 1960 to co-ordinate European ATM) proposed a variety of measures to increase the capacity of en-route airspace. A key change envisaged is the increasing delegation of responsibilities for control to flight crew, by the use of airborne separation assurance between aircraft, leading eventually to ?free flight? airspace. However, there are major concerns regarding the safety of operations in ?free flight? airspace. The safety of such airspace can be investigated by analysing the factors that affect conflict occurrence, i.e. a loss of the prescribed separation between two aircraft in airspace. This paper analyses the factors affecting conflict occurrence in current airspace and future free flight airspace by using a simulation model of air traffic controller workload, the RAMS model. The paper begins with a literature review of the factors that affect conflict occurrence. This is followed by a description of the RAMS model and of its use in this analysis. The airspace simulated is the Mediterranean Free Flight region, and the major attributes of this region and of the traffic demand patterns are outlined next. In particular a day?s air traffic is simulated in the two airspace scenarios, and rules for conflict detection and resolution are carefully defined. The following section outlines the framework for analysing the output from the simulations, using negative binomial (NB) and generalised negative binomial (GNB) regression, and discusses the estimation methods required. The next section presents the results of the regression analysis, taking into account the spatio-temporal nature of the data. The following section presents an analysis of the spatial and temporal pattern of conflicts in the two airspace scenarios across a day, highlighting possible metrics to indicate this. The paper concludes with future research directions based upon this analysis.

Development of a generic activities model of command and control

This paper reports on five different models of command and control. Four different models are reviewed: a process model, a contextual control model, a decision ladder model and a functional model. Further to this, command and control activities are analysed in three distinct domains: armed forces, emergency services and civilian services. From this analysis, taxonomies of command and control activities are developed that give rise to an activities model of command and control. This model will be used to guide further research into technological support of command and control activities

Engage D5.6 Thematic challenge briefing notes (1st and 2nd releases)

Engage identified four thematic challenges to address research topics not contemporaneously (sufficiently) addressed by SESAR. This deliverable serves primarily as a record of the two sets of released thematic challenge briefing notes

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 359)

This bibliography lists 164 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jan. 1992. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

What we got Here, is a Failure to Coordinate: Implicit and Explicit Coordination in Air Combat

Publisher Copyright: © Copyright 2023, Human Factors and Ergonomics Society.Air combat is the ultimate test for teamwork, as teams of fighter pilot (or flights), must coordinate their actions in a highly complex, hostile, dynamic and time critical environment. Flights can coordinate their actions using communication, that is, explicitly, or by relying on team situation awareness (SA), that is, implicitly. This paper examines how these two forms of coordination are associated with performance when prosecuting or evading an attack in simulated air combat. This was done by investigating the flights’ team SA, number of SA-related communication acts and performance in these two types of critical events during air combat. The results exhibit a quadratic dependence between team SA and communication. The rate of change of SA-related communication frequency with respect to change of team SA was negative: communication was needed to build team SA, but once an appropriate level of team SA was established, fewer communications were required. If, however, team SA deteriorated the number of SA communication acts increased. However, during time critical events, the flights did not always have enough time to coordinate their actions verbally. If the flights’ team SA in such situations was low, the flights’ explicit coordination attempts were not sufficient to avoid poor performance.Peer reviewe

System theoretic challenges and research opportunities in military C3 systems

"September 1980" "Proceedings 19th IEEE Decision and Control Conference, Albuquerque, N.M., December 1980."Bibliography: leaf 5."Office of Naval Research ... contract ONR/N00014-77-C-0532" "Air Force Office of Scientific Research ... contract AFOSR-80-0229"Michael Athans

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations

Semantic correlation of behavior for the interoperability of heterogeneous simulations

A desirable goal of military simulation training is to provide large scale or joint exercises to train personnel at higher echelons. To help meet this goal, many of the lower echelon combatants must consist of computer generated forces with some of these echelons composed of units from different simulations. The object of the research described is to correlate the behaviors of entities in different simulations so that they can interoperate with one another to support simulation training. Specific source behaviors can be translated to a form in terms of general behaviors which can then be correlated to any desired specific destination simulation behavior without prior knowledge of the pairing. The correlation, however, does not result in 100% effectiveness because most simulations have different semantics and were designed for different training needs. An ontology of general behaviors and behavior parameters, a database of source behaviors written in terms of these general behaviors with a database of destination behaviors. This comparison is based upon the similarity of sub-behaviors and the behavior parameters. Source behaviors/parameters may be deemed similar based upon their sub-behaviors or sub-parameters and their relationship (more specific or more general) to destination behaviors/parameters. As an additional constraint for correlation, a conversion path from all required destination parameters to a source parameter must be found in order for the behavior to be correlated and thus executed. The length of this conversion path often determines the similarity for behavior parameters, both source and destination. This research has shown, through a set of experiments, that heuristic metrics, in conjunction with a corresponding behavior and parameter ontology, are sufficient for the correlation of heterogeneous simulation behavior. These metrics successfully correlated known pairings provided by experts and provided reasonable correlations for behaviors that have no corresponding destination behavior. For different simulations, these metrics serve as a foundation for more complex methods of behavior correlation