Validation of an Air-Traffic Controller behavioral model for fast time simulation (original) (raw)
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Advanced Air Traffic Management (ATM) concepts related to automation, airspace organization and operational procedures are driven by the overall goal to increase ATM system performance. Independently on the nature and/or impact of envisaged changes (e.g. from a short term procedure adjustment to a very long term operational concept or aid tools completion), the preliminary assessment of possible gains in airspace/airport capacity, safety and cost-effectiveness is done by running Model Based Simulations (MBSs, also known as Fast Time Simulations - FTS). Being a not human-in-the-loop technique, the reliability of a MBS results depend on the accuracy and significance of modeled human factors. Despite that, it can be observed in the practice that modeling tools commonly assume a generalized standardization of human behaviors and tasks and consider a very few range of work environment factors that, in the reality, affect the actual human-system performance. The present paper is aimed at opening a discussion about the possibility to keep task description and related weight at a high/general level, suitable for an efficient use of MBSs and, at the same time, increasing simulations reliability adopting some adjustment coming from the elaboration of further variables related to the human aspects of controllers workload.
2010
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Agent-Based Simulations Using Human Performance Models for National Airspace System Risk Assessment
2009
While it is fortunate that the National Airspace System (NAS) has achieved levels of safety unparalleled in almost any other domain, commensurate levels of risk are so low as to be very difficult to assess. This difficulty can be represented from two different-but-corresponding viewpoints: statistical concerns with estimating very rare events, and modeling concerns with estimating very rare events. The statistical concerns stem from the sheer number of data points required to perform a truly random Monte Carlo-type simulation (order of 10 10), and the novel analyses that would be required to form estimates not of 'mean' values, but instead of occurrences in the 'tails' of probability distributions of a priori unknown form. The modeling concerns stem from the difficulty in capturing all the behaviors of every agent in the system and all types of interactions between them such that every possible 'real' behavior is captured. This proposal instead seeks to coordinate the statistical and modeling concerns using an intermediate model fidelity: agent-based simulation of relevant aspects of the NAS. Agent-based simulation of the National Airspace System (NAS) provides a detailed prediction of system behavior. Both micro-level (agent) and macro-level (system-wide) behaviors are simulated simultaneously, highlighting system-wide issues arising from a change in NAS configuration, air traffic procedures, or air or ground technologies-as well as identifying unreasonable demands that system dynamics may place on individual agents such as controllers or pilots. Prior developments established such detailed simulations using human performance models as the pilot and controller agents. Corresponding developments in simulation architectures also demonstrated the ability to accurately model agent interactions, to enable larger scale simulations via distributing the simulation, and to facilitate tighter linkages with the statistical issues with data collection and with establishing sufficient confidence in output parameters. This report describes the following research tasks further developing agent-based simulation as a method for NAS risk assessment: • Closer integration (working with San Jose State University) of human performance models with agent-based simulations, so that they can work seamlessly together. • Implementation of a large-scale agent-based simulation of an aspect of the NAS suitable for assessing safety issues at sufficient level of detail to identify the likely impact of hazards resulting from specific conditions, and to highlight their source and potential solutions. • A two-stage analysis process, one using very detailed agent-models for a lower number of simulation runs, and the second using less detailed agent models for a high number of data runs suitable for statistical analysis. • Supporting research into data analysis techniques and large-scale simulation techniques. A specific test case (analyzing aircraft arrivals into LAX using a variety of spacing techniques) was examined throughout as a test case. It should be noted, however, that the over arching purpose of this work was to provide the research and development base for NAS risk assessment, not to provide a single risk assessment of this one test case.
Aerospace
The study of human factors in aviation makes an important contribution to safety. Within this discipline, real-time simulations (RTS) are a very powerful tool. The use of simulators allows for exercises with controlled air traffic control (ATC) events to be designed so that their influence on the performance of air traffic controllers (ATCOs) can be studied. The CRITERIA (atC event-dRiven capacITy modEls foR aIr nAvigation) project aims to establish capacity models and determine the influence of a series of ATC events on the workload of ATCOs. To establish a correlation between these ATC events and neurophysiological variables, a previous step is needed: a methodology for defining the taskload faced by the ATCO during the development of each simulation. This paper presents the development of this methodology and a series of recommendations for extrapolating the lessons learnt from this line of research to similar experiments. This methodology starts from a taskload design, and after...
Eats: An Agent-Based Air Traffic Simulator
2007
We present an Experimental Air Traffic Simulator (EATS).It is conceived as a tool for preliminary evaluation of flight procedures, algorithms and human-machine interfaces to be used in future Navigation and Air Traffic surrounding the new Communication, Navigation and Surveillance System to Air Traffic Management (CNS/ATM). The proposed EATS simulator version provides realistic data for the aircraft dynamic and includes the exchange of information among the aircraft from the point of view of the Air Traffic Control (ATC). It also takes into account the meteorological conditions and terrain constraints. This system has been designed as a Multi-Agent System and implemented on a JADE framework. Its architecture facilitates its later extension to incorporate and to evaluate new communication protocols and negotiation between agents operating in a specific air space.
ATC-lab: An air traffic control simulator for the laboratory
Behavior Research Methods, Instruments, & Computers, 2004
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 mediumfidelity 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.
Literature review of air traffic controller modeling for traffic simulations
AIAA/IEEE Digital Avionics Systems Conference - Proceedings, 2008
Innovative air traffic management concepts can be effectively evaluated using fast-time computer simulations, which require air traffic control models. This paper presents a literature survey of the state-of-the-art in air traffic controller modeling, with an emphasis on the application of these models for investigating the implementation of continuous descent approaches in traffic simulations, with brief attention to various modeling approaches for conflict detection and resolution decision-making.
Human-In-the-Loop Evaluation of NextGen Concepts in the Airspace Operations Laboratory
AIAA Modeling and Simulation Technologies Conference, 2010
The Airspace Operations Laboratory (AOL) at the NASA Ames Research Center hosts a powerful simulation environment for human-in-the-loop studies of air traffic operations. The primary real-time simulation capabilities are developed by the AOL development team as part of the Multi Aircraft Control System (MACS) and cover a wide range of operational environments from current day operations to future operational concepts like those envisioned for the Next Generation Air Transportation System (NextGen). The research focus in the AOL is on examining air traffic control and traffic management operations across multiple air traffic control sectors and Centers in rich air/ground environments that can include oceanic, enroute and terminal airspace. The basic simulation capabilities and earlier research was presented at the AIAA Modeling and Simulation Technologies conference in 2006. Since then, the AOL capabilities have been continuously improved and expanded. Over the past four years the AOL has been extensively utilized to investigate a variety of NextGen concepts for NASA's NextGen Airspace Program and the FAA's Air Traffic Organization for Planning, Research and Technology. The primary focus areas under investigation in the AOL are Separation Assurance and the associated Functional Allocation for NextGen, Controller Managed Spacing for near-to mid-term Terminal area operations, flow-based trajectory management and multi-sector planning and dynamic airspace configuration and flexible airspace management. This paper first gives an overview over the most significant capabilities that were added since 2006 and then reviews at a high level the main activities and findings in the different research focus areas. Nomenclature AAC = Advanced Airspace Concept ADS-A/B = Automatic Dependent Surveillance-Addressed/Broadcast ADRS = Aeronautical Data link and Radar Simulator ANSP = Air Navigation Service Provider AOL = Airspace Operations Laboratory at NASA Ames ATM = Air Traffic Management ATOL = Air Traffic Operations Laboratory at NASA Langley BC = Boundary Change CD&R = Conflict Detection and Resolution CDTI = Cockpit Display of Traffic Information CPDLC = Controller Pilot Data Link Communication DAC