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Presented by David Wing (david.wing@nasa.gov)

Bryan Barmore (bryan.barmore@nasa.gov)NASA Langley Research Center

NASA Research Results for“4D-ASAS” Applications

ASAS Thematic Network 2 Third Workshop, Glasgow, Scotland 11-13 September 2006

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Research Premise: Distributing ATM Functions Results in Scalable ATM System

Strategic functions: ATSPTraffic flow management, resource scheduling

Local functions: 4D-ASAS-capable operatorFlight safety, ATSP-issued constraint conformance, trajectory optimization

Presentation is on Two DAG-TM “4D-ASAS” ConceptsEn-Route: Autonomous Flight ManagementTerminal Arrival: Airborne Precision Spacing

ATSP: Air Traffic Service Provider

Aeronautical

Operational

Control A

ir T

raff

ic

Ser

vice

Pro

vide

rFlightCrew

• Information

• Decision making

• Responsibility

Distributed Air

GroundTraffic

Management

Original 4D trajectory

Modified 4D trajectory, same strategic constraints

RTA unchanged

Distributed 4D Trajectory ManagementATSP sets strategic trajectory constraintsOperator manages trajectory to meet them

Distributed 4D Trajectory ManagementATSP sets strategic trajectory constraintsOperator manages trajectory to meet them

Local situations and “no impact” changes are implemented by 4D-ASAS aircraft

Local situations and “no impact” changes are implemented by 4D-ASAS aircraft

Changes impacting NAS resource usage

are coordinated strategically

Changes impacting NAS resource usage

are coordinated strategically

Example local situationExample local situation

4D-ASAS: Four Dimensional Airborne Separation Assistance SystemsRTA: Required Time of Arrival

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Instrument Flight Rules (IFR) Aircraft

Hazard avoidanceFleet management

Priorityrules

Maneuver restrictions

IFRpriority Distributed

separationassurance

Terminal area

Terminal areaentry constraints

IFR and AFR traffic flow management

IFR trajectory

management

Cost controlPassenger comfort

AFR-managed trajectories

$+

Autonomous Flight ManagementAn En-Route/Transition 4D-ASAS Concept

Levels of 4D-ASASperformance

Integrated Operational Principles• Performance-based operations • 4D trajectory operations• Non-segregated operations

Integrated Operational Principles• Performance-based operations • 4D trajectory operations• Non-segregated operations

Autonomous Flight Rules(AFR) Aircraft

Air Traffic Service Provider

Special Use Airspaceavoidance

David WingNASA Langley Research Center

david.wing@nasa.gov

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AFM Research Accomplishments

NASA project-level accomplishments• Operational concept description• Feasibility assessment of airborne and integrated air/ground operations• Feasibility assessment of ATSP operations • Human factors assessment • Life-cycle cost-benefit analysis • Safety impact assessment • Flight deck technology for autonomous operations • ATSP decision support technology• Experimental evaluation of integrated air/ground operations

Langley contribution highlights1. Developed flight-deck decision support toolset

and supporting flight deck systems-- Autonomous Operations Planner (AOP)

2. Conducted 3 HITL simulation experiments3. Performed 36-issue assessment of concept

feasibility -- application of research analysis and domain expertise

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• Strategic & tactical conflict detection & resolution

• Conflict-free maneuvering support

• Flow constraint conformance

• Airspace restriction avoidance

Principal Functions

Autonomous Operations Planner NASA’s Research Prototype of 4D-ASAS En-Route Toolset

Attributes

• Working software prototype w/ ARINC 429 data-bus & 702a FMS integration

• CD&R alerting is RTCA SC186 ACM-WG compliant

• Simultaneously meets traffic, airspace, user, and flow management constraints (RTA)

• Performs trajectory optimization as part of conflict resolution

• Works within and ‘across’ normal autoflight modes, and within aircraft performance limits

Command conflicts

Planning conflicts

Provisional (FMS/MCP)

conflicts

Blunder protection and collision data

Ownship intent

Conflict alerts and

information

Maneuver restriction

information

Conflict resolutionand

trajectory planning

Intent-basedconflict

detection

State-basedconflict

detection

Priorityrules

ATC flow management constraints and airspace

constraints

AOP

Traffic intent

Ownship state

Traffic state

Crew inputs

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Pilot-Only Simulation Experiments: Study of Tools, Procedures, Hazards

Scenario DesignConventional traffic conflicts

– Lateral & vertical– State & intent

Unconventional traffic conflicts– Blunders– Pop-up separation loss – Meter-fix conflicts

Constraints– ADS-B surveillance limitations– Airspace restrictions– Required Time of Arrival

Variables studied– Traffic density– Use of intent data– Conflict resolution method– Lateral separation standard– Airspace restrictions– Priority rules

Studies resulted in significant gains in understanding of AFR operations feasibility, operational sensitivities, human factors design, and requirements for tools & procedures

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Pilot-Only Simulation Experiments: Sample Results

Aircraft B

Aircraft A

SUA

SUA

SUA

SUA

Crossing AssignmentRTA <30 seconds

Altitude < 500 ftPosition < 2.5 nm

Identical crossing assignments

Second generation

conflictSecond generation

conflict

Planned conflict

Planned conflict

Ove

r-C

on

stra

ined

T

raje

cto

ries

Co

nfl

ict

Pro

pag

atio

n

0%

20%

40%

60%

80%

100%

Leftaircraft

Co

ns

tra

int

Co

nfo

rma

nc

e

missed multiplemissed onemet all

Rightaircraft

No priority rules With priority rules

Leftaircraft

Rightaircraft

Go

al

Go

al

Res

ult

: B

ett

er

pre

dic

tab

ilit

y

Resolution MethodTactical: open loop

Strategic: closed loopModified: pilot override

No

Eve

nts

59 data runs

Resolution method

Res

ult

: D

om

ino

eff

ec

t p

rev

en

ted

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Integrated Air-Ground Experiment: Langley-Ames Experimental Evaluation

Addressed 2 key feasibility issues:– Mixed Operations: Investigate safety and efficiency in high density sectors

compared to all managed operations– Scalability: Investigate ability to safely increase total aircraft beyond controller

manageable levels. Number of managed aircraft remains at or below current high-density levels.

• T0: ≈ current monitor alert parameter• T1: approximate threshold above which managed only

operations will definitely fail (determined by Ames study)• Only overflights were increased (arrivals held constant)

Autonomous

Managed

T1 L2

L3

L1 L1

T0

C1 C2 C3 C4

4 test conditions3 traffic levels

Fort Worth Center (ZFW)

Ghost DFW TRACON

Ghost South

Ghost North

Wichita FallsHigh

Ardmore High

Amarillo High

Bowie Low

OverflightsArrivals

BAMBEFort Worth Center (ZFW)

Ghost DFW TRACON

Ghost South

Ghost North

Wichita FallsHigh

Ardmore High

Amarillo High

Bowie Low

OverflightsArrivalsOverflightsArrivals

BAMBE

• 22 commercial airline pilots (20 single pilots + 2 pilot crew in high fidelity simulator)

• 5 professional air traffic controllers (1 per sector + 1 tracker)

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Langley Aircraft and Ames ControllerSample Results

• Pilots mainly able to meet constraints• Some pilot entry error (RTA into FMS)• No apparent performance degradation

as traffic level increased

0

20

40

60

80

100

C1 C2 C3 C4

Condition

Per

cen

t C

on

form

ance

Time Altitude Speed

Increasing Traffic

Meter fix conformance for arrivals

• Lower workload for all mixed conditions• Traffic levels at C3 and C4 not considered

manageable if all aircraft IFR

1

2

3

4

5

6

7

Amarillo Ardmore Wichita Falls Bowie

ControllerW

ork

load

Rat

ing

C1 C2 C3 C4

Controller workload assessment

Low

High

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AFM Feasibility Assessment Activity

• Team analysis of 36 feasibility questions – Distributed operations, air/ground integration, strategic & local TFM, flight crew

responsibilities, airborne equipage, CNS– Evaluations based on literature search, research results, operational experience

and judgment

• Sample questions:– Is the distributed AFR network vulnerable to system-level or cascading component

failures?– Within what limits do AFR aircraft have the ability to adapt to changes in the airport

acceptance?– Can airborne conflict management be performed in all ownship flight guidance

modes?– Can AFR operations accommodate a range of RNP capabilities?

• Conclusion: – Feasible at the integrated-system / laboratory-simulation maturity level– Further technical progress requirements identified– Sample challenges:

Accommodating prediction uncertainties Flow-constrained descents Convective weather interaction Failure modes Traffic complexity management Complex AFR/IFR interactions

Dr. Bryan BarmoreNASA Langley Research Center

bryan.barmore@nasa.gov

A Terminal Arrival 4D-ASAS Concept

Airborne Precision Spacing

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Airborne Precision Spacing

ADS-B-enabled operation in which the ATSP assigns speed management for spacing to the aircraft

Goal is to increase runwaycapacity by increasing the precision and predictability of runway arrivals

ATSP manages traffic flow, ensures separation and determines the landing sequence

Pilots precisely fly their aircraft to achieve ATSP-specified spacing goal

A single strategic clearance reduces radio congestion and workload for both ATSP and pilots

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APS Flight Deck Automation

Computes relative ETA at threshold Provides speed guidance to

achieve desired relative ETASafe merging is a consequence of

beginning spacing operations early

Spacing interval can be customized pair-wise to account for wake vortex hazard and other constraints

Adjusts for dissimilar final approach speeds

Corrects speed if necessary to prevent separation violations

Gain scheduling to enhance stability of a aircraft stream

Respects aircraft configuration limits for speed changes

Ownship:time to go = 23:15

Lead:time to go = 22:15

30 seconds early at threshold

Slow down 5 knots

Target: 90 secs

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Human-in-the-Loop Evaluation of APS

Chicago O’Hare Flight Evaluation

Three equipped aircraft including NASA B757

Wind shifts of 230º or more seen on base and final

Flight performance – 8 sec

Simulation performance – 2 sec

Medium fidelity simulation Merging and in-trail operations

9 aircraft stream (6 subject pilots)

No dependence on airspace design, type of operation or location in stream

15-20 minute flight times

Medium fidelity simulation results

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Fast-time Simulations

DFW airspace with three merging streams

Each data run had a stream of 100 aircraft / 40 repetitions per condition

Wide range of aircraft types and performance (BADA model)

Precision of approximately 2 sec under nominal conditions

Challenges for significant initial spacing deviation; wind forecast errors and limited ADS-B range

Knowing final approach speed gives significant improvement in spacing precision

Improvements being made for wind updating and setting initial spacing requirements

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CDA with Spacing

Continuous Descent Approaches offer a fuel and time efficient descent while reducing ground noise and environmental pollutants

However, ATSP must be largely “hands-off” resulting in loss of capacity to maintain safety

By including airborne spacing we can realize the majority of the CDA benefits while maintaining capacity levels

The ability to make only minor speed adjustments during the procedure allows the flight crew to stay close to the optimal CDA while maintaining spacing with other aircraft

NASA is currently working with the FAA, other research organizations, a major airline and avionics vender to develop and implement merging & spacing

This is seen as a first step to implementing airborne spacing in large, complex terminal environments

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Preliminary Merging and Spacing Simulation Results

Separation at merge point

Four CDA routes into DFW350 nm routesMerges at cruise, downwind, baseNominal winds, initial spacing deviationStudied several disruptive events

(not presented here)Results for nominal case: 0.21.3 sec

for disturbances: -0.94.3 sec

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Current and Future NASA ResearchRelated to 4D-ASAS

• Safety assessments of distributed airborne separation– Batch study on distributed strategic conflict management

• Traffic complexity management through distributed control of trajectory flexibility– Development of flexibility metric, preservation function– Trajectory constraint minimization

• Early implementation applications– Oceanic In Trail Procedure– Merging and spacing with continuous descents

• Airborne Precision Spacing in super-density terminal arrival operations

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Thanks for your attention.

(Back-up charts follow)

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En-RouteSafety Impact Assessment

• Study performed by Volpe National Transportation Systems Center, Oct. 2004– To provide NASA with information on potential safety impacts and risks that can be

addressed during concept development, simulation, and testing– Approach: (1) Task-based analysis and (2) Simulation results analysis

• Findings– Identified no safety showstoppers, several positive safety impacts, and several safety issues

recommended for further research– Concept at early stages of R&D, too soon to determine safety relative to the current system – Ultimate assessment requires iterative safety analyses, determination of safety and

performance requirements for systems and operators, and extensive testing

• Safety Issues Recommended for Further Research (highlights)– Roll of automation: Need stringent criteria for availability, integrity, and accuracy– Unambiguous identification (air & ground) of AFR vs. IFR status– Determine need for ATSP awareness of AFR traffic, AFR-IFR conflicts– AFR awareness of AFR-IFR conflicts; AFR/ATSP coordination for short-term alerts– Upper limit of distributed authorities (AFR) for safe operations – complexity management*– AFR-to-IFR transition in non-normal situations; significant rates of metering non-

conformance– Impact of degraded or erroneous intent information– Flight crew workload in descent– Preclusion of conflict propagation* * New R&D activities currently in progress

or planned to address these issues

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L2 alert(conflict alert)

L3 alert(NMAC alert)

Display filteringConflict prevention

Flexibility preservation L1 alert(low level alert)

Additional Protective Factors• Long look-ahead time horizon• On-condition intent-change broadcast• Intent-based automated conflict detection• Alert-based procedures• Rapid-update state surveillance• Human/automation redundancy

L0 alert(traffic point out)

XXXX

Safety DesignAOP’s Layered Approach to Distributed Separation Assurance

Level 1 (L1) alert(low level alert)

L2 alert(conflict alert)

L3 alert(NMAC alert)

Continuoussurveillance

Right-of-wayrules

Strategic & tactical CR

ACAS

Maneuver restriction alerting

Protection layers

Implicit coordination

Nearby aircraft

Pre-alert

Pre-alert

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4D-ASAS Issues of Concern For Discussion and Possible Study

• Socio-political acceptability– Social acceptance that a distributed-authority system is safe regardless of technical proof? – Political resistance to implementation of distributed system (users and service providers)?

• Destabilization from gaming– Can this be mitigated using slot management?

• Performance-achievement incentive– Is there sufficient incentive for users to always want to equip for higher ATM performance?

• Short-distance flight benefits– Are there sufficient degrees of freedom?

• Departure constraints impact on performance– Will users have sufficient departure-time control to achieve benefits?

• Retrofit potential– Does forward-fitting meet the demand?– Are retrofit options technically feasible, cost-effective, and beneficial?

• Mandate impact– What is the user cost/benefit impact if 4D-ASAS is mandated?