Download - Free-Flight & Air Traffic Control - ACCS
FreeFree--Flight & Air Traffic ControlFlight & Air Traffic ControlProf Peter LindsayBoeing Professor of Systems EngineeringDirector, ACCS
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Outline of talk
Some terminology & conceptsThe future of Air Traffic ControlATC as a complex system– Multi Agent System models– Boids & flocking behaviour
Evaluation of ATC design optionsThe ATC Workload project– Modelling operators
Summary & conclusions
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ATC trends & challenges
Changing nature of Air Traffic Control:– Australian system now entirely computer-based– Datalink will (partially) replace radio communications– ADSB + GPS will enable radar-like surveillance of whole
continentAutomated Dependent Surveillance - Broadcast
Massive savings possible if airlines can choose own trajectories (“free flight”)Free flight is a fundamental change to operational conceptHow do we ensure that safety is not compromised, & objectives are achieved?
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Terminology & concepts
En-route flight phase: > 200km from airportsDifferent separation standards apply:– Lateral: 5NM horizontal distance– Vertical: 1000’– Longitudinal (aka “in trail”): 30NM when on same path– Also “soft standards”: eg 10NM intervention standard
separation violation: the separation standard is not metFlight plan: 4D trajectory, including time at waypoints
Free Flight & Air Traffic Control
ATC: The Australian contextAustralian ATM Strategic Plan released 2002– Plan through to 2017 & beyond
Stakeholders include:– AirServices Aust (ASA): ATM providers– CASA: regulators– Airlines – international, domestic, regional,…– Airports– International standards bodies: IATA, ICAO– Dept of Transport & Regional Services (DOTAR)– Lobby groups: Aviation Industry Forum (ASTRA),…
Free Flight & Air Traffic Control
Key drivers for changeReduced infrastructure costs– eg use GPS & satellite comms instead of radar
Reduced flight times, fuel use, noise,…More flexible airline operations– eg negotiate slots on day
Desire for increased system predictability– eg more reliable arrival times;
know how much fuel to carryATM service market becoming global– increased flight ranges– sector charge differentials
Free Flight & Air Traffic Control
Australian ATM Strategic Plan7 key strategies including– User Preferred Trajectories (UPTs)
User = airline– Flexible Use of Airspace (FUA)
civilian use of military airspacereservation system
– Conflict ManagementMove from distance & time separation standards to more flexible risk management approach
– Decision Information NetworkIncreased information sharing, more negotiation
15 year lead times:– 5 ConOps, 5 functional architecture, 5 test & prove
Free Flight & Air Traffic Control
User Preferred Trajectories (UPTs)Goal is to optimise for flight distance, time, fuel usage, weather,…Applies to en-route control rather than airport vicinity– Mainly for international & long domestic (E/W) flights
Plan is for staged introduction– Flex tracks: to take advantage of jet streams
(seasonal)– Full freedom (eg great circle routes) will require total
rethink of separation paradigmNote findings of Tasman simulator trial
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Outline of talk
Some terminology & conceptsThe future of Air Traffic ControlATC as a complex system– Multi Agent System models– Boids & flocking behaviour
Evaluation of ATC design optionsThe ATC Workload project– Modelling operators
Summary & conclusions
Free Flight & Air Traffic Control
ATC as a complex systemA non-linear system– Changes at one level can have unanticipated effects
at other levels– Eg conflict alert– Propagation of delays– Effect of weather
Free Flight & Air Traffic Control
Future National Air-Space (NAS) model
Flight parameters
Flight trajectories
Regional traffic patterns
NAS-wide traffic patterns
Flight Deck
AOC
ATC
Traffic Management
Free Flight & Air Traffic Control
Tackling the free flight problem (2)Approach to Free Flight ATM:– Agents: aircraft(/airlines), weather, airport controllers,
traffic controllers, flow controllers…– Behaviour: flight plans, procedures,…– Connections: proximity, communications,…– Emergent properties: safety, congestion, throughput,…
System safety “managed” primarily through off-line negotiation of flight plans (+ design of procedures etc)– Optimise system “robustness” in pre-flight planning
Free Flight & Air Traffic Control
Tackling the free flight problem (2)Provide tools for situation awareness & decision support – eg visualise downstream effect of changes
Understand how local decisions cascade to global consequences
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Flocks of aircraft?
One way to reduce controller workload would be to have aircraft fly in a cluster– “Moving sectors”– Aircraft do their own separation assurance within the cluster– Possible application of flocking behaviour?
Flocking behaviour follows from 3 simple rules– See Craig Reynolds on Boids
www.red3d.com/cwr/boids
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3 simple steering behaviours
Separation: steer to avoid crowding local flockmates
Alignment: steer towards the average heading of local flockmates
Cohesion: steer to move toward the average position of local flockmates
From Reynolds
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Predator & school of fish
Can add a 4th rule: steer away from predator
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Outline of talk
Some terminology & conceptsThe future of Air Traffic ControlATC as a complex system– Multi Agent System models– Boids & flocking behaviour
Evaluation of ATC design optionsThe ATC Workload project– Modelling operators
Summary & conclusions
Free Flight & Air Traffic Control
Evaluation of ATC design optionsNeed a way of evaluating & predicting risk associated with new operational conceptsHuman operator will play a role in ATC for a long time to come– Role of ground-based controller will change from
active control to passive monitoring– But what exactly should the role be?
How to divide responsibility between ground & air?
– What tools will they need?
Free Flight & Air Traffic Control
How to evaluate HCI design choices?Challenge with existing systems is to evaluate safety of different Human Computer Interaction design choices: eg– Which software tools to make available & when?
What settings?– What procedures & protocols to use?– How to train operators?
Note: existing Human Reliability Assessment techniques are inadequate for this purpose– Mostly designed for well-designed sequences of
essentially independent activities– ATC task is highly interleaved, concurrent &
memory-based
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ATC software tools include…
Short route probe: indicates predicted position of aircraft at selected time intervals into the futureBearing & range lines: shows aircraft's distance & bearing from selected points– can be another aircraft
Estimated time of passing: shows time & point where aircraft will come closestConflict alert warning: indicates that separation violation will occur if aircraft maintain current speed & bearing…
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Overview of SafeHCI approach
Our approach to comparing HCI design choices: understand & model operator’s cognitive processes as stochastic processes– hypothesize what factors affect likelihood and
duration of activities within the task– conduct experiments to calibrate the models
hypothesize effects of design interventions on individual activitiespredict system-level effects of the design interventions
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Calculating system risk
Design individual experiments to calibrate the different parts of the model as functions of the environment & history (= memory)– probability of transitions – duration of transitions
Have developed tool that will calculate overall likelihood of user-specified indicators for user-supplied scenarios– e.g. whether a separation violation occurs
Use to estimate system-level effect of proposed design interventions– vary task & predict/estimate effect on individual transitions– calculate effect on indicators
Free Flight & Air Traffic Control
Modelling the conflict detection taskA conflict is a pair of aircraft that will come within 5NM while “at same Flight Level” unless controller intervenesWhat follows is a “proof of concept” study still underwayObjective is to develop a model that emulates operator performance & effect of different tools
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The different tools
The 4 operational concepts being modelled:– Baseline: unaided– Conflict alert: automated tool that indicates conflict
when 50NM apart– DOMS Predictor tool: user-invoked tool that
calculates Distance Of Minimum Separation (DOMS)– Both tools in use
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Operators as stochastic processes
Model probability & duration of transitions, & probability of outcomes– Use experiments to develop formulae for the above– Main factors: DOMS, angle,
time to min separation (ttms)Eg Timing for the baseline model (in minutes):
scan attendi
classifyi
0.25
1 if IC0 if NC
0.1
0.25
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Postulated effect of tools on timingTiming for the Conflict Alert case:
scan attendi
classifyi
0.25
1 if IC0 if NC
0.1
0.1 if alerting0.25 otherwise
Timing for the DP tool case:scan attendi
classifyi0.5
Free Flight & Air Traffic Control
Postulated effect of ttms on accuracyttms = time to minimum separation– Roughly corresponds to urgency
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0.2
0.4
0.6
0.8
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ttms:2, 5, 10
DOMS=5DOMS=0 DOMS=10
Free Flight & Air Traffic Control
Predicted effect on operator performance
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0.2
0.4
0.6
0.8
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0 2 4 6 7 8 9
baseline conflict_alert doms both
DOMS
model
Likelihood that operator will classify the pair as being in conflict
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Outline of talk
Some terminology & conceptsThe future of Air Traffic ControlATC as a complex system– Multi Agent System models– Boids & flocking behaviour
Evaluation of ATC design optionsQuick introduction to the ATC Workload project– Modelling operators
Summary & conclusions
Free Flight & Air Traffic Control
The ATC Workload projectCollaboration with UQ’s Key Centre for Human Factors & Applied Cognitive Psychology & Airservices AustraliaAim: To develop a model that can:– Measure the flow of traffic through an air sector– Predict the level of workload that an average
controller will experienceThe challenge: model the effect of controller interventions on traffic– Also, controllers adapt their behaviour to moderate
future workload
Free Flight & Air Traffic Control
Agent-based modellingWe are developing stochastic agent-based models of the full task
Free Flight & Air Traffic Control
ATC simulator architectureATCSimulator- updates the position of aircraft over time according to their specified flight plans
Aircraft characteristics
Flight plans
Prerecordedaircraft
positions
ATC Engine
Aircraft Agents
Controller Agents
Workload and Traffic Flow metrics Visualisations
Track data and amended flight plans
Pre-recorded Controller
outputs
Sector, route and Waypoint database
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Summary & conclusions
Air Traffic Control is undergoing fundamental changes– Free flight has the potential for substantial savings &
efficiency gains, provided it can be made safe– The technology is available, but a lot of research is
still needed before a workable operational concept can be implemented
Nature can give us inspirationsModelling & simulation has advantages over than experimentationBut how can we be sure our models are valid?
Free Flight & Air Traffic Control
Summary & conclusions (2)
ARC Centre for Complex Systems– Theme: computation in and by networks
Simple agent behaviour+ connection topology = complex system behaviour (emergent properties)Emergent properties in this case are safety, efficiency, orderliness, predictabilty,…
– Methods & tools for understanding, managing & controlling complex systems
Evaluation of system design optionsLater: decision support systems
– Application of complex systems science to ATCeg flocking behaviour
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AcknowledgementsAir Traffic Control program:– ATC Workload project is a collaboration between ACCS, UQ’s
Key Centre for Human Factors & Applied Cognitive Psychology & Airservices Australia (Andrew Neal, Project Leader)
– Simon Connelly & Junhua Wang– stochastic modelling tool– Scott Boland – traffic replay tool– Penny Sanderson & Martijn Mooij – hi-fi simulator experiments– Katie Duzcmal & Peter Robinson – agent model in Prolog– Colin Ramsay – trajectory modelling– Tim Rudge – 3D visualiser– Jacki Wicks & Rachel Chitoni – calibration of conflict detection
models– Ariel Liebman – risk-based conflict management
Plus many more