A knowledge-based conflict resolution algorithm for terminal area air traffic control advisory generation

Stochastic optimal control for aircraft conflict resolution under wind uncertainty

A method for conflict detection and resolution based on the parameterization of the aircraft intents is presented. The method is also based on the use of predefined trajectory patterns, which are in fact flight intents; these patterns include standard airline procedures and air traffic control regulations. The conflict resolution problem is formulated as a parametric optimization problem subject to constraints; the optimality criterium is defined so that the deviation from the intended (preferred) trajectories in the lateral profile is minimized. The resolution trajectory patterns take into account changes of the nominal waypoints (vectoring) and changes of the aircraft speeds. The method is applied to the case of multiple conflicts among commercial transport aircraft in converging traffic in the terminal area; different scenarios are considered, which include locked aircraft, that is, aircraft whose trajectories are known and fixed. The conflict detection and resolution algorithm relies on a kinetic trajectory predictor (nonlinear point-mass model with variable mass), which is accurate, flexible, and transparent, and provides the high-fidelity prediction required in the analysis of the demanding terminal area traffic. The cost of the global conflict resolution process is assessed, in terms of extra distance traveled, extra flight time, and extra fuel consumed for each aircraft.

The FAA, carrier airlines and passengers are all familiar with the inefficiencies and costs that result from delays in the air transportation system. A significant portion of the delays are associated with operations on or near the surface of major airports. There continues to be keen interest in improving efficiency of surface operations in order to reduce delay costs. The projected growth of air traffic demand is further fueling this interest. The Tower Flight Data Manager (TFDM) initiative by the FAA is aimed at providing tools in the air traffic control tower that would aid in improving operational efficiency on the surface. This initiative seeks to provide benefits through the consolidation of legacy automation systems/displays, the coherent fusion of information from multiple external systems, and the prediction and planning of flight operations on the surface. The ability to predict and plan operations on the surface is delivered to air traffic controllers through a set of decision support tools. These tools provide decision support in the following functional areas: airport configuration, runway assignment, taxi routing, sequencing & scheduling, departure metering, and departure routing. This paper is focused on describing an implementation of these tools in a prototype of the TFDM system. This prototype system is installed at Dallas/Fort Worth airport and is undergoing operational testing. The paper provides selected results from the application of the decision support tools, as well as discussion of future enhancements to the tools.

Conflict is inevitable to take place in collaborative design, and conflict resolution plays an important part in complex product collaborative design systems. Firstly, a mathematic description model in collaborative design considering resource conflict, process conflict and design conflict is given, and the mathematic model expresses the origin of conflict and shows that conflict resolution is a multiobjective planning problem. Next, a conflict resolution algorithm considering design objective optimization is presented, and fuzzy value and fuzzy grade are applied in the algorithm. Depending on both considering design variables having fundamental influences on its design objectives and the cost of conflict resolution, the algorithm can improve the quality and efficiency of conflict resolution. Finally, an example of single cylindrical gear reducer is used to show the validity of the algorithm.

An airborne conflict resolution approach is presented that is capable of providing flight plans forecast to be conflict-free with both area and traffic hazards. This approach is capable of meeting constraints on the flight plan such as required times of arrival (RTA) at a fix. The conflict resolution algorithm is based upon a genetic algorithm, and can thus seek conflict-free flight plans meeting broader flight planning objectives such as minimum time, fuel or total cost. The method has been applied to conflicts occurring 6 to 25 minutes in the future in climb, cruise and descent phases of flight. The conflict resolution approach separates the detection, trajectory generation and flight rules function from the resolution algorithm. The method is capable of supporting pilot-constructed resolutions, cooperative and non-cooperative maneuvers, and also providing conflict resolution on trajectories forecast by an onboard FMC.

Under the concept of Free Flight, future air traffic operations may permit the transfer of responsibility for various tasks, including conflict detection and resolution, from ground-based air traffic controllers to the flight crew. While aircraft-based conflict resolution is attractive from a user-preferences standpoint, the degree to which it can efficiently resolve complex conflicts among several interacting aircraft remains a significant issue. The objective of this study is to compare the performance of a decentralized conflict resolution strategy against that of a benchmark centralized conflict resolution strategy. A generalized methodology for such a comparison does not exist; therefore two qualitatively different conflict scenarios, characterized by complex interactions among multiple aircraft, were constructed to conduct simulation studies using an idealized model. Preliminary investigations indicate that a decentralized resolution strategy can successfully solve complex multiple-aircraft problems in real time, albeit with some performance degradation relative to a centralized strategy. Research Scientist, Automation Concepts Research Branch; Mail Stop 210-10; E-mail; kbilimoria@mail.arc.nasa.gov. Associate Fellow, AIAA. f Software Specialist, Raytheon ITSS. Research Assistant, Dept. of Aeronautics and Astronautics. Associate Professor, Dept. of Aeronautics and Astronautics; E-mail: feron@mit.edu. Senior Member, AIAA. Copyright © 2000 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental purposes. All other rights are reserved by the copyright owner. Introduction The advent of new technologies for Air Traffic Management (ATM) has the potential to change the operational paradigm of the air transportation system by delegating more responsibility to the flight deck for airplane trajectory management functions; this includes conflict detection and resolution (CDR this is an idealized representation of a situation where several free aircraft are simultaneously attempting to arrive at some terminal area entry point. The second scenario features two closelyspaced traffic streams (each consisting of several aircraft) intersecting at a common point; this is an idealized representation of aircraft flying along intersecting free routes in en route airspace. The performance of a reactive decentralized resolution method that provides sequential, pairwise conflict resolutions based on a geometric optimization approach10 is compared against that of a proactive centralized resolution method that provides a single coordinated conflict resolution based on a global optimization algorithm.5 Although determining a fully coordinated optimal solution to conflicts involving multiple aircraft is computationally challenging, the centralized conflict resolution method described in Ref. 5 is able to compute these solutions, which are used as benchmarks for the best performance that can be achieved. The performance of decentralized strategies is then compared against these benchmark solutions. This paper is organized as follows: First, the mathematical models used for aircraft trajectories and conflict avoidance are presented. The centralized and decentralized conflict resolution methods used in this study are then outlined. Next, performance measures for conflict resolution are defined, and two conflict scenarios are described. Finally, a comparison of the performance of the decentralized conflict resolution strategy relative to the centralized conflict resolution strategy is presented, along with some general observations about their characteristics.

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

- Efficient examination scheduling is critical for maintaining academic integrity and optimizing resources in educational institutions. This research focuses on developing an automated exam timetable generation system that dynamically resolves conflicts and accommodates diverse institutional constraints. By leveraging detailed algorithms for faculty invigilation, student schedules, room allocation, and conflict resolution, the system minimizes manual errors and improves operational efficiency. The proposed methodology includes real-time data collection, scheduling optimization, and robust invigilation assignment processes. Expected outcomes of this research include significant reductions in scheduling time, enhanced stakeholder satisfaction, and scalability to accommodate institutional growth. By addressing existing gaps in scheduling methods, this study offers a transformative approach to academic resource management, setting the foundation for advancements in educational technology. Key Words: Examination Scheduling, Timetable Generation, Conflict Resolution, Faculty Availability, Resource Optimization, Educational Technology, Automation, Scalability, Greedy approach, Sophisticated Algorithm

This paper addresses the speed regulation problem in air traffic management. Because global air traffic volume is continuously increasing, improvement in air traffic control has become a priority. During this decade, European and United States initiatives have been launched to design the future of air traffic management. One of their objectives is to increase air traffic density and optimize flight route plans. This can be achieved through en route deconfliction. Air conflicts have the potential to occur when two or more aircraft are predicted to be below a separation norm in the near future. Such situations affect air traffic controllers' workload; thus, these situations limit controllers' capacity to deal with large numbers of aircraft and induce flight delay. Reducing air traffic controllers' potential workload through speed regulation has been investigated in the En Route Air Traffic Soft Management Ultimate System project. Efficiency of the method has been validated through simulations, including human-in-the-loop experiments, which opens the door to conflict resolution algorithms based on speed regulation. In this paper a formulation for the speed regulation problem is proposed. First, a potential conflict detection and resolution framework is presented. Uncertainty is then introduced in the model, with the aim of reproducing realistic air navigation conditions. A case study of real air traffic instances is described, and results are discussed to assess the potential of the proposed algorithm.

China has been gradually relaxing its ban on the use of low-altitude airspace across the country. To guarantee the high reliability of air traffic management (ATM), conflict detection and conflict resolution (CDR) approaches are indispensable to maintain safe separation between neighbouring small fixed-wing aircraft. In this study, we analyse a temporal and spatial integrated strategy for safety assessment purposes in opening the low-altitude urban airspace of Chinese pilot cities. First, we present a detailed mathematical description of the proposed algorithms based on a spatial grid partitioning system (SGPS). For our system, a conflict detection (CD) algorithm is designed to determine if two trajectories pass through the same grid space within overlapping time windows. A conflict resolution (CR) algorithm integrates a proposed time scheduling-based technique (TST) and vertical change-based technique (VCT), which operate under predetermined basic principles. Then, based on our novel CDR algorithms, a causal model is constructed in graphical modelling and analysis software (GMAS) to generate a state space that can provide a global perspective on scenario dynamics and better understanding of induced conflict occurrences. Finally, simulation results demonstrate that the proposed approach is practical and efficient.

The pilot- and controller-in-the-loop simulation described in this paper demonstrates the potential benefits of a near-term trajectory-based operations concept with datalink communications. Near-term operations with datalink are characterized by a fleet of which not all aircraft are equipped with datalink communications (i.e., mixed equipage). The objectives of this simulation were to continue to develop capabilities such as the conflict resolution algorithm, as well as evaluate new capabilities and concepts such as tactical conflict detection and trajectory-based weather avoidance with feedback from experienced pilots and controllers. Conflict resolutions and tactical conflict detections were compared to controller actions. The direction of the conflict resolution maneuver advised by the algorithm agreed with controller actions 79% of the time when both chose to apply the same type of resolution maneuver to the same aircraft. Comparing controller actions to conflicts detected by the tactical conflict detection function revealed no missed alerts and a false alert rate of 11%. Trajectory-based weather avoidance functions received high ratings from the controllers for usefulness and ease of use. In particular, controllers noted weather avoidance reroutes originating from a simulated traffic management coordinator position alleviated their concerns about potentially disrupting traffic flow management plans, thus expediting the issuance of the reroutes.

Last year, we presented methodology to perform knowledge-based medical imaging informatics research on specific clinical scenarios where brain tumor patients are treated with Proton Beam Therapy (PT). In this presentation, we demonstrate the design and implementation of quantification and visualization tools to develop the knowledge base for therapy treatment planning based on DICOM-RT-ION objects. Proton Beam Therapy (PT) is a particular treatment that utilizes energized charged particles, protons, to deliver dose to the target region. Similar to traditional Radiation Therapy (RT), complex clinical imaging and informatics data are generated during the treatment process that guide the planning and the success of the treatment. Therefore, an Electronic Patient Record (ePR) System has been developed to standardize and centralize clinical imaging and informatics data and properly distribute data throughout the treatment duration. To further improve treatment planning process, we developed a set of decision support tools to improve the QA process in treatment planning process. One such example is a tool to assist in the planning of stereotactic PT cases where CT and MR images need to be analyzed simultaneously during treatment plan assessment. These tools are add-on features for DICOM standard ePR system of brain cancer patients and improve the clinical efficiency of PT treatment planning. Additional outcome data collected for PT cases are included in the overall DICOM-RT-ION database design as knowledge to enhance outcomes analysis for future PT adopters.

This paper presents the DeciMaS framework , which supports the vital stages of information system creation. The case study for the DeciMaS framework is also presented. For this reason an agent-based decision support system (ADSS) is created and described in detail. We discuss the structure and the data mining methods of the designed ADSS. The intelligent ADSS described here provides a platform for integration of related knowledge coming from external heterogeneous sources, and supports its transformation into an understandable set of models and analytical dependencies, with the global aim of assisting a manager with a set of decision support tools.

An experiment is described that aimed at evaluating a principle of dynamic task allocation (DTA) of conflict resolution between aircraft in air-traffic control on a large scale simulator. It included three cognitive agents: the radar controller (RC), in charge of conflict detection and resolution; the planning controller (PC), in charge of entry-exit coordination and of workload regulation; and a conflict resolution computer system (SAINTEX), able to manage only simple conflicts. Within this three-agent paradigm, three conditions were compared: (a) a control condition (without computer assistance); (b) an explicit condition (PC and RC in charge of the allocation); and (c) an assisted explicit condition (SAINTEX proposed allocations which could be changed by PC). Comparisons were made on the basis of a detailed cognitive analysis of verbal protocols. The more the assistance, the more anticipative the mode of operation in controllers and the easier the human-human cooperation (HHC). These positive effects of the computer support are interpreted in terms of decreased workload and increased shared information space. In addition, the more the controllers felt responsible for task allocation, the more they criticized the machine operation.

This paper is incidental to a research program of finding an automation system to govern the civil flight corridors in which the instrumentality of human agency is all but totally devolved onto a complex, multi-layered data electro-mathematical analyzer. Six major actualities comprising of dimensionality, probabilisticality, conflict detection, conflict resolution, maneuvering, global multiplicity of aircraft management, have become the focus of the proposed automation. The un-touched bench mark discourse of the prevalency of an “orderer-ordered” intercommunication between the aircraft agents and the Air Traffic Control meta-agent(s) has been kept sacrosanct for a variety of reasons to avert an over-revolutionary discourse change in a sphere of trafficking where any probable risk entails extraordinary losses of all sorts. A cutaneously rigid, layerized maths-speech act programming adapted by the present authors makes it feasible in the format of Prolog to deliver the responsibility of a mono-controller only capable of being in touch with just one flying object at each real-time instance on to some machine governing “more-than-several” aerospace SUSPENDING DOTS at the very same real-time instance.