airport taxi/departure simulation

Piloted Simulation of NextGen Time-based Taxi Clearances and Tailored Departures

David C. Foyle, PhDNASA Ames Research Center

Becky L. Hooey, MScChristina L. Kunkle, BAC st a u e,

Martin F.J. Schwirzke, MADeborah L. Bakowski, MA

San Jose State University Foundation at NASA Ames Research Center

ICNS 2009ICNS 2009

http://humansystems.arc.nasa.gov/groups/HCSL/

Outline

S f ti• Surface operations• 4-D (time-based) taxi clearances• Surface Traffic Management (STM) system• Surface Traffic Management (STM) system

characteristics• Simulation Experiment• Results• Conclusions

Surface Operations• Airport surface congestion results in the largest delay cost in US p g g y

airspace system (Glass & Gawdiak, 1997)• Delays are caused by competition for resources

SolutionsSolutions• Increase taxi efficiency and improve runway coordination (Cheng, Sharma,

& Foyle, 2001)• Coordinated runway crossings can potentially increase traffic throughput• Coordinated runway crossings can potentially increase traffic throughput

of airports(Cheng, Sharma, & Foyle, 2001; Hooey, 2005)

• Surface Traffic ManagementSystems (STMs)– Utilize dynamic algorithms– Precise surface coordination– 4-D (time-based) taxi clearances

Pilot Requirements for 4D Taxi Clearances

Problem: Integrating surface traffic management system 4D taxi clearances with flight deck

Advanced surface traffic management systems

with flight deck information requirements

Human factors pilot-in-the-loop studies to determine pilot operating requirements

- Speed conformance- Route and time conformance- Conceptual (ConOps) development

Advanced surface traffic management systems and ConOps must incorporate pilot operating requirements

- Ability to comply with speed requests- A/C variance of route and time conformance

Conceptual development (e g form of taxi - Conceptual (ConOps) development - Pilot workload, Situation awareness (SA)- Safety impacts due to time pressure

4D Taxi Navigation Issues4D Concepts

- Conceptual development (e.g., form of taxi clearances - continuous, updates, etc.)

- Pilot/Aircraft non-conformance- Rerouting

- Continuous-coupled 4D commands - Progressive taxi/route updates- Endpoint-only 4D commands (push-back, departure queue)

4D Taxi Clearance Display Formats - Speed vs. time displays

C ti ti d di l- Continuous vs. non-continuous command displays- Bandwidth of command updates (pilot display and ATC concept)

Pilot Performance Metrics - Variance of speed, time-of-arrival error- SA, workload impacts

(Surface Traffic Management (STM) Systems)

Development of Time-based STMs

Defining Characteristics • ATC/STM - Number of Traffic Flow Points

ATC/STM Flow Point Time Constraint• ATC/STM - Flow Point Time Constraint• ATC/STM - Refresh/reoptimization (due to traffic changes, pilot

performance)• Flight Deck - Onboard "display" algorithms (e g error nulling)• Flight Deck - Onboard display algorithms (e.g., error nulling)• Flight Deck - Display Bandwidth Speed (bounding conditions)• Speed (bounding conditions)

STM

AlgorithmsPilot A/C

Performance

(Surface Traffic Management (STM) Systems)

Development of Time-based STMs

Defining Characteristics • ATC/STM - Number of Traffic Flow Points

ATC/STM Flow Point Time Constraint• ATC/STM - Flow Point Time Constraint• ATC/STM - Refresh/reoptimization (due to traffic changes, pilot

performance)• Flight Deck - Onboard "display" algorithms (e g error nulling)• Flight Deck - Onboard display algorithms (e.g., error nulling)• Flight Deck - Display Bandwidth Speed (bounding conditions)• Speed (bounding conditions)

STM

AlgorithmsPilot A/C

Performance

Taxi-out Departure

Taxi-out Departure

“Departure is currently the highest workload phase of flight”

- Richard L Newman Phd- Richard L. Newman, PhdFormerly FAA

Human Factors Specialist,Commercial Transportp

NextGen Operations- Dynamic, Tightly Coupled

Potential for High Workload & Errors- Potential for High Workload & Errors

Simulation

Medium Fidelity PartMedium Fidelity Part--task Simulatortask Simulator• Human• Human--Centered Systems Centered Systems

L b t (HCSL)L b t (HCSL)Laboratory (HCSL)Laboratory (HCSL)• NASA Ames Research Center• NASA Ames Research Center• Previously validated• Previously validated

DallasDallas--Fort Worth (DFW) airportFort Worth (DFW) airport

Visibility: Clear, distant hazeVisibility: Clear, distant haze

Simple B737 aircraft modelSimple B737 aircraft model

Controls: Tiller, throttle, toe brakes, Controls: Tiller, throttle, toe brakes, rudder pedalsrudder pedals

Pilots: 16 commercial transportPilots: 16 commercial transportAge: 25Age: 25--63 yrs (M=45 5 yrs)63 yrs (M=45 5 yrs)Age: 25Age: 25--63 yrs (M=45.5 yrs)63 yrs (M=45.5 yrs)Flight hours: 1,000Flight hours: 1,000--20,000 (M=5,586)20,000 (M=5,586)

Experiment Overview

Pilot Tasks• Taxi (with speed/time)• Verify departure clearance• Maintain checklistMaintain checklist• Traffic separation

Independent VariablesN tG I l t ti (b t )

Traffic Flow PointsLimited NextGen:

S C• NextGen Implementation (between)- Limited, Advanced• Traffic Flow Points (within)- 1, 3, or 5Ta i Speeds ( ithin)

Speed ChangeAdvanced NextGen:

Speed Change &TND Checkpoint• Taxi Speeds (within)

- 10, 14, 18, 22 kts

Same traffic locations and speeds for Limited NextGen vs. Advanced NextGen

TND Checkpoint

conditions

Dependent Measures• Time of Arrival (TOA) error (at traffic flow points & RWY)

FinalDepartureClearanceflow points & RWY)

• Departure Clearance Verification (Errors and Latency)

DFW Routes

12 Unique DFW Routes• 14,300’ length (avg.)

• Repeated 2x

Traffic Flow Points

Repeated 2x- Different traffic flow points- Other traffic

• Final Departure Clearancepgiven 25-75% into route

Trials• 4 Familiarization trials

(no data collection 1 hr)FinalDepartureClearance

(no data collection, ~1 hr)• 24 NextGen nominal• 2 Departure clearance mismatches• 1 “Current-day” taxi

NextGen Conditions and DisplaysPrimary Flight Display (PFD) Taxi Navigation Display (TND)y g p y ( ) g p y ( )

Limited NextGen• ATC: Speed commands at traffic flow points

• Pilots: Maintain commanded speed (avg.) – 15 kts turn max.

• PFD: Current, commanded speed

• TND: Route, Traffic

NextGen Conditions and DisplaysPrimary Flight Display (PFD) Taxi Navigation Display (TND)y g p y ( ) g p y ( )

Limited NextGen• ATC: Speed commands at traffic flow points

• Pilots: Maintain commanded speed (avg.) – 15 kts turn

• PFD: Current, commanded speed

• TND: Route, Traffic

Advanced NextGen• ATC: Speed commands at traffic flow points

• Pilots: Maintain commanded speed (dynamic) – 15 kts turn

• PFD: Current, commanded speed, Required Time of Arrival (RTA), Elapsed Time, Error-nulling algorithm (for RTA)

• TND: Route, Traffic, Traffic flow point

NextGen Conditions and Displays

Limited NextGen• ATC: Speed commands at traffic flow points

Error nulling algorithm (for RTA):• Pilots: Maintain commanded speed (avg.) – 15 kts turn max.

• PFD: Current, commanded speed

Error-nulling algorithm (for RTA):

CRemaining Distance

• TND: Route, TrafficCurrent commanded speed =g

Remaining Time

Advanced NextGen• ATC: Speed commands at traffic flow points

• Pilots: Maintain commanded speed (dynamic) – 15 kts turn

• PFD: Current, commanded speed, Required Time of Arrival (RTA), Elapsed Time, Error-nulling algorithm (for RTA)

• TND: Route, Traffic, Traffic flow point

Checklist, Datalink, Nav DisplayTaxi Navigation Display (TND)

Pre-trial• TND overview mode

• At DFW ramp spot

Datalink TextDeparture ClearanceWindow

• ATC verbal route clearance

• Navigation Display (ND): Pre-loaded predeparture clearance

N i ti Di l (ND)

Checklist Window

• Pilot: “Ready to taxi”Navigation Display (ND)

Taxi trial• TND: Track-up, perspective

• Checklist scan task (~2 min)

• Datalink text departure clearance: Predeparture clearanceclearance

• Navigation Display (ND): Pre-loaded predeparture clearance

Departure Clearance Verification TaskNOMINAL

Pending• Departure clearance sent 25-75% into route

Chi ACCEPT/REJECT• Chime, ACCEPT/REJECT flashing

• Pilot must verify match between:1) D t li k t t d1) Datalink text, and2) ND

- Route ID number- Last leg direction

Departure Clearance Verification TaskNOMINAL

Pending• Departure clearance sent 25-75% into route

Chi ACCEPT/REJECT• Chime, ACCEPT/REJECT flashing

• Pilot must verify match between:1) D t li k t t d1) Datalink text, and2) ND

- Route ID number- Last leg direction

Accepted• Accept or Reject clearance (button press)

• Loads into FMS/ND

• If incorrectly rejected, ATC re-sent

Departure Clearance Verification TaskOFF-NOMINAL

2 Mismatch Trials• 1st – ID number and route direction

2 d ID b• 2nd – ID number

• If incorrectly accepted –loaded

• If correctly rejected – correctIf correctly rejected correct clearance sent

Departure Clearance Verification TaskOFF-NOMINAL

2 Mismatch Trials• 1st – ID number and route direction

2 d ID b• 2nd – ID number

Rejected• If incorrectly accepted –loaded

• If correctly rejected –correct clearance sent

Time of Arrival (TOA) ErrorTOA error calculation• Actual TOA - Required TOA (RTA)• Limited NextGen: No explicit RTA

(Calculated using segment length and ATC-commanded speed)

p=.001

TOA error results1. Limited vs. Advanced NextGen (3-way, p<.01)

Advanced NextGen (speed error-nulling avionics)

Ear

lyLa

te

( p g )allows reduced TOA error for all speeds and number of traffic flow points

2. Limited NextGen (Quadratic x Linear, p<.01)Speed commands only (without speed errorSpeed commands only (without speed error-nulling avionics):• Increase number of traffic flow points yields exponential reduction in TOA error• 14 kts best (turns typical taxi speed)

p=.01

• 14 kts best (turns, typical taxi speed)• Replicated Williams, Hooey, & Foyle, 2006

3. Advanced NextGen (Linear x Linear, p=.058)Speed error-nulling avionics:E

arly

Late

p g• Overall reduction in TOA error• 14 kts best (turns, typical taxi speed) • Linear improvement with more traffic flow points

TOA Error Distributions

TOA error distribution results

Advanced NextGen (error-nulling avionics) much less variable TOA error than Limited NextGen (speed commands)

Departure Clearance Verification Errors

Departure clearance verification resultsIncorrect rejections: 3 / 400 nominal clearances, p(error)=.008Incorrect rejections: 3 / 400 nominal clearances, p(error) .008

- Likely due to heading text readout (N vs. NE)

Incorrect acceptances: 2 / 32 off-nominal (mismatched), p(error)=.06- Both 2nd mismatch, 1 in each NextGen implementation

May be indicative of increased workload with time-based taxi clearances

Departure Clearance Verification Latency

Limited NextGen vs. Advanced NextGen (interaction, p=.005)

p=.005

Correct = “Accept” Correct = “Reject”Correct = “Accept”

Departure Clearance Verification Latency

*Limited NextGen – Speed commands only, no error-nulling avionics: (overall, p<.05)

**

*

*= Significant

n.s.Advanced NextGen – Error-nulling

avionics: (overall, p<.001)

**

Correct = “Accept” Correct = “Reject”Correct = “Accept”

Departure Clearance Verification Latency

Compared to “current-day” baseline taxi,

Advanced NextGen (error-nulling avionics) had longer latencies to:avionics) had longer latencies to:

- Correctly accept correct clearances- Correctly reject incorrect clearances

Compared to Limited NextGen (speedCompared to Limited NextGen (speed commands only),

Advanced NextGen (error-nulling avionics) had longer latencies to:

- Correctly reject incorrect clearances

Correct = “Accept” Correct = “Reject”Correct = “Accept”

Correctly reject incorrect clearances

May be indicative of increased workload in Advanced NextGen implementationimplementation

Post-study Questions

How many ‘speed changes’ (Limited NextGen) or ‘traffic flow points’ (Advanced NextGen) per route are acceptable?are acceptable?

All: “2-3”

Were there too many ‘speed changes’ (Limited NextGen) or ‘traffic flow(Limited NextGen) or traffic flow points’ (Advanced NextGen)? (1, 3, or 5)

Limited NextGen: 0% “yes”Advanced NextGen: 88% “yes”Advanced NextGen: 88% yes

(p<.001)

Post-Study Structured Interviews1.5 hr Post-study Structured Interview Findings

Time-based Taxi Clearances• Improve airport efficiency• Pilot acceptance likely (efficiency gains)• Pilot acceptance likely (efficiency gains)• Some concern for safety (“eyes in”)• Ground speed on PFD reasonable• Suggestions for TND to show nearby traffic and taxi holds• Possible increase in crew coordination need for speed “callouts”• Possible increase in crew coordination – need for speed callouts

NextGen Tailored Departures (Datalinked flexible 4-D departures)• Improve system-level efficiency (routing)p y y ( g)• Improve individual aircraft efficiency (fuel, time)• Decrease flight deck workload (direct upload of clearances into FMS)• General acceptance of concept

- Terrain/traffic cleared by ATCy- No issue with unique routes (may help with complacency)- Cross-check of datalink and route loaded required; Reasonable as implemented

• Some concern about how to “back up” unique complex routes- Pre-departure briefings (how do you describe to each other, manually fly?)p g ( y , y y )- Emergency or off-nominal fall-back procedures (avionics failure, engine out)- Requires future research

ConclusionsCommanded Speed• TOA compliance most accurate with moderate taxi

- Arrive early for slower speeds; Late for faster speeds

Segment Distance• TOA error largest with single (long) route segments

NextGen Taxi Implementation• Requirement for Advanced NextGen error-nulling avionicsq g

- Limited NextGen speed commands TOA error too high/variable (could limit optimization by STMs)

- Advanced NextGen error-nulling avionics substantially improves TOA compliancecompliance

• However, Advanced NextGen error-nulling avionics:- May induce increased flight deck workload- Need to investigate procedures and aids to offset

- Required conformance levels of speed and TOA ‘windows’

NextGen Tailored Departures• No major concept issues• Need for cross-check, verification• How to ‘back up’ unique complex routes (for briefing, emergency, off-nominal)

Piloted Simulation of NextGen Time-based Taxi Clearances and Tailored Departures

David C. Foyle, PhDNASA Ames Research Center

Becky L. Hooey, MScChristina L. Kunkle, BAC st a u e,

Martin F.J. Schwirzke, MADeborah L. Bakowski, MA

San Jose State University Foundation at NASA Ames Research Center

ICNS 2009ICNS 2009

http://humansystems.arc.nasa.gov/groups/HCSL/