operationalization of norms in aircraft approach/departure decision support
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Operationalization of Norms in Aircraft Approach/Departure Decision Support. Laura Savi čienė , Vilnius University. Problem statement. - PowerPoint PPT PresentationTRANSCRIPT
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Operationalization of Norms in Aircraft
Approach/Departure Decision Support
Laura Savičienė, Vilnius University
July 9, 2012
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Problem statement
• To develop a conception for operationalization of the aircraft approach/departure norms in a decision support system, taking into consideration the use of lidar (laser radar) for aircraft tracking
• Tasks:1. Modeling norm violation risk in the airport
traffic zone2. Modeling radar and lidar data fusion3. Development of a prototype decision support
system
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Context
• The SKY-Scanner project: using lidar to track aircraft in the airport traffic zone– Part of the SKY-Scanner project was the
DSS for the air traffic controller
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Assumptions
• Assumption 1: lidar, used together with the primary radar, provides aircraft position with a high degree of accuracy
• Assumption 2: the DSS simply informs the controller, who takes the decision on actions
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Normative rules in aircraft
approach/departure• Norms in the following areas are examined:
– Air traffic control (ATC) separation rules: horizontal sep. (in nautical miles) and vertical sep. (in feet)
– Airport approach/departure procedures: norms are presented as maps, charts, tables, and textual descriptions
– Wake turbulence separation rules: time-based separation
– Rules for avoiding volcanic ash: zones of restricted operations depending on particle concentration
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Approach/departure procedures
• Each airport has a unique set of the approach/departure procedures
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Related works
• Current aviation-related systems do not model norms comprehensively, but there is some research in that direction
• Conflict detection and resolution process structure is adapted to aircraft separation conflicts, but can be expanded to cover other normative rules
• Study in real-time decision making suggests to facilitate the encoding step of the user’s cognitive process, possibly, by providing more intuitive visualizations
• 2D visualizations in ATC are no longer sufficient, and 3D visualizations have drawbacks; possible strategy to overcome this is to augment the 3D screens with auxiliary 2D elements
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Decision support process
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Modeling of norms
• Geometrical norms, i.e. those concerning aircraft position and speed, are identified
• Norms are modeled from the perspective of violating them
• Two norm types are identified: limit-based and deviation-based
• Each norm is modeled with a factor, a pattern, and a normative value vNJuly 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Modeling of risk
• Each normative rule is represented as a risk definition in the decision support system
• Risk definition associates the modeled norm with a set of thresholds and discrete risk levels
• Risk evaluation maps the observed value of the norm factor to a discrete risk level:– For L risk levels, L-1 thresholds (or pairs of th.)
are needed– A separate indicator can be created for each
normJuly 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Risk definition example: indicated airspeed
Norm factor: “indicated airspeed”;Norm type: “limit”;Norm patter: “<= vN”;
Expected value: 210 kt.;Thresholds: v0 = 202 kt., v1 = 206 kt., v2 = 214 kt.;
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Risk definition example: altitude
Norm factor: “altitude”;Norm type: “deviation”;Norm pattern: “= vN”;
Expected value: 3900 ft. at 6 DME (deviation 0);Thresholds: dn0=-0.5, dp0=2, dn1=-1, dp1=3.5, dn2=-1.5, dp2=5;
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Visualization of the approach procedure: 2D-
in-3D example
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Visualization of the approach procedure: pure-3D with “rings”
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Results (1)
• A conception for norm operationalization and norm violation risk model– Each norm is modeled with a factor, a pattern,
and a normative value vN
– Each norm is represented as a risk definition– Risk evaluation maps the observed value of
the norm factor to a discrete risk level– The solution combines well known models
(piecewise linear risk model and traffic light decision making principle)
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Results (2)
• Prototype decision support system – Demonstrates modeling of several norms– Adapts advanced visualization ideas– Provides real-time demonstration of the
solution
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Conclusions
• The proposed norm operationalization conception enables to represent a subset of aircraft approach/departure normative rules (geometrical norms) in a decision support system for the air traffic controller
• The prototype decision support system provides an integrated solution to facilitating the controller: risk indicators automate detection of possible norm violations, and 2D-in-3D visualizations help comprehend conformance to the approach/departure procedure
• Phases, needed to operationalize the norms, are identified, but the process cannot be fully automated
July 9, 2012 Vilnius University, Faculty of Mathematics and Informatics
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Thank You for Your Attention!
July 9, 2012Vilnius University, Faculty of Mathematics and Informatics