Fatigue Risk Management

© Cranfield University1

www.cranfield.ac.uk

Fatigue Risk Management: Identification and Mitigation ATCO’s Fatigue

Wen-Chin Li PhD CIHFE

Safety and Accident Investigation Centre,

Cranfield University, U.K.

ATC Fatigue Research in SAM Region 16th-18th September 2019


Overview

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Understanding the Impacts of Fatigue

ICAO’s Regulations on Fatigue Risk Management

Research on Investigating ATCO’s Fatigue

Roster Matrix Impacted to Fatigue

Coherence Training increasing Fatigue Resilience

Innovative Technology of RTO and Fatigue Perception

Complexity of Human Performance and Fatigue

Q&A

Overview


56% of pilots sleep in the cockpit, 29% admitted when they

woke up they found the other pilot asleep as well (BALPA, 2015)

Fatigue is a state of reduced capability of mental and physical

performance resulting from workload/stress

Operators’ fatigue cost employers $136 billions per year by

reduced work performance

ICAO new regulations required ANSP have to establish FRMS

in 2020

Understanding the Impacts of Fatigue


Air Traffic Control Service Provider shall:

• develop a policy for the management of ATCOs’ fatigue;

• establish procedures to identify ATCOs’ fatigue, together with

mitigation strategies;

• provide ATCOs training programmes on prevention of fatigue;

ICAO’s New Regulation of Fatigue Management


Defined by the State

Approved by the State

Both prescriptive and performance-based approaches share

two important features

1. based on scientific principles, knowledge and operational experience

2. has to be a shared responsibility between the State, Service Providers

and individuals


Ripple in the Pond:People did think & act differently

how to provide education and training to deal with fatigue?

how to mitigate negative effect of ATCO’s fatigue?

how to develop fatigue risk management system?

Emotional response is the critical factor to

innovative systems and Safety

There is always a consequence after action


A Further Thought for CRM & ADMA Further Thought of developing CRM, SMS & FRMS

Emotional Response

We didn’t appreciate what we got while compared with others if they got more


Fatigue Resilience Training for Solar

Impulse Pilot: to mitigate fatigue and

improve decision-making under extreme

stress/fatigue situations by coherence

training 1 pilot only Altitude 8,000 to 12,000 ft Cruise speed 43 mph No automation systems No pressurization system Temperature from -40 to +35 117, 71 & 62 hours non-sleep

What is the Biggest Challenge for

117 hours without proper sleep?

Sleep 20 minutes only.mp4


Roster Impacted to ATCO’s Fatigue Levels

Study-1: Subjective self-reported measurement

Shift work and long daily work hours increase the

risk of accidents related to poor sleep quality

Individual ATCO has limited understanding to the

effects and consequences of fatigue

Managing fatigue risk has continually as one of the

“most wanted” safety improvement of NTSB.

It is important to investigate both sleep quality and

circadian rhythm for FRMS


Method

Participants: 36 ATCOs

Ethic approval: CURES/2470/2017

Procedures: Briefing of how to self-record fatigue level by

using SSS, ATCOs self-recording for 2-weeks, then conducting

focus group

Materials: Stanford Sleepiness Scale

Statistics analysis: ATCOs’ preceding sleeping hours with

different ages (4-levels), experiences (4-levels) and gender (2-

levels) were analyzed by a one-way ANOVA. The homogeneity

of variances will be verified by using Levene’s test.

Method

0

0.5

1

1.5

2

2.5

3

3.5

1 2 3 4 5 6 7 8

Fat

igue

level

Hour

Workday 1

Workday 2

Workday 3

Workday 4

Workday 5


ATCO’s Alertness Rating Scale


Fatigue level NWorkday 1 Workday 2 Workday 3 Workday 4 Workday 5 Hourly average

M SD M SD M SD M SD M SD M SD

Working hour 1 36 1.55 0.70 1.42 0.64 1.69 0.80 1.86 1.06 1.77 0.79 1.66 0.07

Working hour 2 36 1.55 0.70 1.37 0.53 1.67 0.89 1.69 0.98 1.92 1.02 1.64 0.07

Working hour 3 36 1.36 0.56 1.53 0.66 1.70 0.82 1.78 0.92 2.33 1.24 1.74 0.08

Working hour 4 36 1.41 0.58 1.48 0.68 1.44 0.70 1.76 0.91 2.41 1.22 1.70 0.08

Working hour 5 36 1.45 0.62 1.52 0.75 1.48 0.73 1.66 0.83 2.33 1.48 1.69 0.09

Working hour 6 36 1.73 0.68 1.65 0.85 1.65 0.89 1.67 0.87 2.48 1.42 1.84 0.10

Working hour 7 36 2.31 1.04 1.78 0.86 1.70 0.92 2.00 0.95 2.62 1.34 2.08 0.10

Working hour 8 36 2.00 0.91 1.94 0.91 1.69 0.80 2.43 0.94 3.16 1.31 2.29 0.10

Daily average 36 1.67 0.53 1.59 0.56 1.65 0.67 1.86 0.75 2.38 1.03 1.66 0.07

Sleeping time 36 7.21 1.21 7.53 0.83 5.07 0.96 7.74 0.79 4.88 0.78 6.48 1.55

Result: Participants’ fatigue levels among eight working hours on five

consecutive workdays


ATCO’s average fatigue level among roster of five workdays

7.21 7.53

5.07

7.74

4.88

1.67 1.59

1.65

1.86

2.38

0.00

0.50

1.00

1.50

2.00

2.50

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

1 2 3 4 5

SS

S r

atin

g

Sle

epin

gti

me

(ho

ur)

Workday

Sleeping time

SSS rating


Discussion

Fatigue risk management has to consider individualdifferences (such as age, experiences and gender)

Fatigue related to disruption of circadian rhythm(both day-3 and day-5starting at early morning and late night, inducing sleeploss, resulted in both acute fatigue and cumulative fatigue)

Scientific principles for developing roster to reflect FRM(collecting objective and subject data, analyzing its risk and developing fatigue

intervention to mitigate these risks)

Changing the fifth shift to the first shift (further investigation needed to validate the strength and consequences)

Developing Fatigue management training and education for both ATCOs and management(poor understanding of the effects and impacts of fatigue and the consequences)

Discussion


Conclusion

ATCOs like extra rest-day by compressed roster but complain

the fatigue

Different individuals have different preferences

High levels of fatigue were noted during the last hours of the

final duty period, might consider moving shift-5 to shift-1

The research of FRM also an education processes to the

participated ATCOs

FRMS must consider scientific principles, knowledge,

operational experience and industrial relations

Study-1Conclusion


Study-2: Quick Coherence Training to Mitigate Fatigue

HRV: Heart rhythms and emotions

Human mind is a wandering mind, wandering mind is an unhappy

mind, pay attention to Here and Now (killingsworth & Gilbert, 2010)

Stimulus independent thought allows human to think, learn and

plan, but it may have an emotional cost


Coherence: Understanding Autonomic

Nervous System (ANS)


Auto rhythm not

required signal

from brain.

Beats 100,000 times

a day, 35m per year,

3b per lifetime.

Listen to your heart,

not your mind.


Quick Coherence training

increasing monitoring performance

M=5.8, SD= 7.4 vs M=3.2, SD=5.9


Method

Participants: 36 ATCOs

Ethic approval: CURES/2470/2017

Procedures: Briefing of how to self-record fatigue level by

using SSS, ATCOs self-recording for 2-weeks, then conducting

focus group

Materials: Stanford Sleepiness Scale

Statistics analysis: ATCOs’ preceding sleeping hours with

different ages (4-levels) and gender (2-levels) were analyzed by

a one-way ANOVA. The homogeneity of variances will be

verified by using Levene’s test.

Method


1. Heart Focus: Focus your attention in the area of heart

2. Heart Breathing: While breathing, feel your breath is flowing in and out through the

heart (slower & deeper than usual)

3. Freeze Frame: Activating the feeling of appreciation to someone in your life, and

freeze this image/feeling in your heart.

By generating the feelings of Appreciation,

Care & Love to achieve Quick Coherence

: Quick Coherence


Professional Certifications

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Results of the Generalized estimating equations model in coherence ratio

Parameter B Mean

Error

95% Wald CI Hypothesis Testing

lower Upper Wald

Chi-

square

df P-value

(Intercept） 29.452 5.4384 18.793 40.111 29.328 1 0.000

[section=3] $ 40.889 1.6059 37.741 44.036 648.306 1 0.000

[section=2] $ -2.333 1.7985 -5.858 1.192 1.683 1 .194

[unhappy=5.00] † -5.100 1.5844 -8.206 -1.995 10.361 1 .001

[unhappy=3.00] † -5.480 1.9003 -9.205 -1.756 8.317 1 .004

[gender=2.00]# -.586 1.0156 -2.577 1.405 .333 1 .564

age .295 .1964 -.089 .680 2.264 1 .132

experience -.597 .1805 -.951 -.243 10.938 1 .001

[section=3] *

[unhappy=5.00] ^

4.894 2.3339 .320 9.469 4.398 1 .036

[section=3] *

[unhappy=3.00] ^

.611 3.1629 -5.588 6.810 .037 1 .847

[section=2] *

[unhappy=5.00] ^

.127 2.2138 -4.211 4.466 .003 1 .954

[section=2] *

[unhappy=3.00] ~

3.033 2.2794 -1.434 7.501 1.771 1 .183


77.37

75.42

65.85 26.90 25.47

70.56

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

60.00

62.00

64.00

66.00

68.00

70.00

72.00

74.00

76.00

78.00

80.00

Before QCT at rest Before QCT at working After QCT at rest

Mean Heart rate and High coherence ratio before QCT ( quick coherence training) at rest , before QCT at work and after QCT at rest

Mean HR high_coherence


Study-2 Conclusion

Improve vagal activity (reduce stress & improve mood)

Improve physical and mental performance

Increase employees’ feeling of well-being

Increase safety & cost-efficiency

Reduce high blood pressure

Reduce inflammation

Reduce absence

Reduce cost

ICAO’s Regulations

Cranfield are keen to provide assistances to mitigate fatigue, and develop FRM

training program to comply ICAO’s new regulations

The benefits of Quick coherence training


Innovative Technology of RTO Impacted to ATCO’s Fatigue

Study-3 Qualitative and Quantitative Approaches

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2020+

Implementation

R&D

Available

Implementation

R&D

Available

Implementation

R&D

Available

Single Aerodrome

ATC/AFIS

Contingency TWR

Multiple Aerodrome

ATC/AFIS

SE

SA

R A

TM

Op

era

tio

na

l S

tep

s

12

3


Sweden had certified a Saab-built remote tower and RTC

Germany worked with Frequentis under a program with DFS

Australia install RTC control Alice Springs Airport from Adelaide (1500 km)

FAA conducted experiments for safety and efficiency of RTC

Singapore Changi airport initiated digital tower

Budapest airport’s remote tower is ready for take-off in HungaroControl

Jersey Airport becomes the first British airport using digital tower in 2019

Irish Aviation Authority operated Multiple remote tower operations

Cranfield University has installed Remote tower for applied research

Application of RTO


OverviewWhy developing Remote Tower Technology?

The Comparison of Operational Costs between Local Tower and Remote TowerBuild Equipment Manpower

Existing

Tower

Roughly cost £12M to Build.

To assume 10% annual running

cost for the building is

reasonable e.g. £1.2M a year.

Usual Communications,

Navigation, Surveillance and

Flight Data Processing

Systems.

Typical manning is 8 to 10

staff per H24 position.

Remote

Tower

Build costs will reduce

significantly as only a Mast

needed to house the cameras.

They could be put on the roof of

terminal or other building

potentially. Estimated cost of

mast £2M saving £10M.

To assume 10% annual running

cost for the Mast is reasonable

e.g. £200K a year saving £1M a

year.

There should be potential to

save on Communications,

Navigation, Surveillance and

Flight Data Processing

Systems Costs via

centralisation which will offset

some of the increase in

network costs.

Remote Towers will

facilitate staffing

efficiencies.

For the IAA example of

Cork and Shannon

controlled from Dublin we

anticipated a saving of 4

ATCO’s or €400K a year.

Capacity, Cost-efficiency, Human Performance and Safety


Certification Processes by Demonstration for MRTO

DublinAirport

ShannonAirport

CorkAirport


Overview

Augmented visualization integrated real and virtual

environments increasing SA

Simply highlighting the borders and dynamic targets

Eye-tracking technology can identify HCI issues

Fixation durations and scan patterns reflect to SA

Pupil dilation related to perceived workload

../../../../../My Vedio/Demo/Voice_control.wmv


Overview

• Participants: 22 qualified ATCOs, ages between 31 and 53

years old (M=42.07, SD=7.76)

• Apparatus:

Eye Tracker

Remote Tower Module

SART-10D

NASA-TLX

System Usability Scale

Method


Overview

• Briefing research objectives

• Calibration eye tracker on RTM

• Shadowing operation wearing eye tracker for data collection

including the percentage of attention on AOIs

• Evaluating SA on interacting with RTM comparing with

physical tower operations by SART-10D, SUS and NASA-TLX

• Debriefing

• Comments to HCI issues on system design of RTM

Procedures


ResultThe comparison of ATCO’s Perceived workload between

physical tower and RTO


OverviewResult

Variables Design Mean SD N

T-Test

t df p Cohen’s d

SART-10D

Remote Tower 33.53 3.04

15 -1.18 14 0.258 -0.30

Physical Tower 34.67 4.17

Supply


15 2.69 14 0.018 0.69


Understanding


15 -3.45 14 0.004 -0.89


The comparison of ATCO’s SA between physical tower and RTO


OverviewResultThe comparison of ATCO’s subjective and objective visual

attention distributions

../../../../Research Project/Jersey Airport - Remote Tower HF Assessment/001 Final Report/000-0032-0054-OTW.mp4


OverviewDiscussion Same task of providing air traffic services by RTO and Physical Tower

No significance on ATCOs’ SA between RTO and Physical Tower

Significant differences on Demand, Supply and Understanding

SA = Understanding - (Demand - Supply)

System design can shape human operator’s perceived workload,cognitive processes and performance

5.93

21.80 18.80

34.67

7.73

23.80

17.47

33.53

0

5

10

15

20

25

30

35

40

Demand Supply Understanding Situation Awareness

Physical Tower

Remote Tower


OverviewDiscussionThe integration of OTW and PTZ to RTM can facilitate ATCO‘s SA

and Task Performance, but increasing head down time

../../../../Research Project/Jersey Airport - Remote Tower HF Assessment/001 Final Report/000-0017-0030-ATM.mp4


OverviewDiscussionThe HCI issues related to remote tower operations

../../../../Research Project/Jersey Airport - Remote Tower HF Assessment/001 Final Report/001-0223-0230-PTZ.mp4


OverviewDiscussion

Understanding types of visible perception for HCI design

Visual presentation on the interface design is the key factor for HCI

Fixation duration reflect to the challenging on the understanding theinformation present

Implemented augmented visualization of RTM can increase cost-efficiency with no safety concerns


id start_timestampduration start_frame end_frame norm_pos_x norm_pos_y dispersion avg_pupil_size

573 3014.941939 0.503868936 10002 10017 0.278804852 0.852836201 0.729429076 68.01141677

574 3015.561777 0.100026093 10021 10024 0.325941324 0.84755132 0.694512836 70.27764675

575 3015.67776 0.204162303 10024 10030 0.343714776 0.833663896 0.728412777 70.71376448

576 3015.981802 0.755963498 10033 10056 0.330946664 0.848127428 0.675597781 69.81811789

577 3016.821868 0.236007037 10058 10065 0.480940256 0.437300234 0.840945383 70.65122223

578 3017.073772 0.116070778 10066 10069 0.486784966 0.372566526 0.318097916 70.24827003

579 3017.35783 0.304141703 10072 10081 0.310579764 0.860638079 0.974568611 68.03125803

580 3017.845752 0.204119755 10087 10093 0.488767716 0.431226557 0.22682772 70.99253845

581 3018.181758 0.23599643 10097 10103 0.300781718 0.864303747 0.985861822 67.90190531

582 3018.433802 0.639923911 10103 10122 0.298320942 0.857623573 0.964772757 68.67274319

583 3019.273849 0.167996906 10128 10133 0.620288222 0.44606725 0.225319309 73.83171844

584 3019.457749 0.188092421 10134 10139 0.607438413 0.452046891 0.13482616 74.20645523

585 3019.729736 0.888026571 10142 10168 0.339685342 0.845358523 0.993711896 71.57090364

586 3020.633913 0.235876166 10169 10176 0.348861263 0.831064678 0.469168505 70.89900258

587 3021.105797 0.991989838 10183 10213 0.511361609 0.326177476 0.753531936 71.77721974

588 3022.213739 0.120002863 10216 10220 0.326912348 0.843385698 0.282958277 71.49476242

589 3022.349765 0.215967862 10220 10227 0.310454811 0.843413722 0.793050221 70.04965155

590 3022.669734 1.376019281 10230 10271 0.509813299 0.339278866 0.969203005 71.73194959

591 3024.130123 0.219631139 10273 10280 0.312612861 0.837820428 0.949995642 69.90789032

592 3024.365736 6.515982085 10280 10475 0.310961194 0.846723473 0.953165473 70.51739049


Increasing Human Resilience for Digital Aviation

Human-System Integration (HIS) is the core concept related

to Safety in Digital Aviation

The benefits of increasing human resilience

Improve physical and mental performance

Increase capacity of accident investigation

Increase safety & cost-efficiency

Reduce stress & high blood pressure

Reduce costs of operations

Applied new technologies can increase human performance,

but… we have to know how to use it properly


Overview

ATCO’s attention, SA, performance, workload and fatigue levels

can be affected by innovative technology

No critical SA and HCI issues on RTO though there are some

approaches can be adapted to increase HP

Be aware of the new AR technology may induce new HF issues

by increasing ATCO’s workload and induced fatigue

The findings are valuable for both ATCO’s training and system

design on RTM in the future

ATCO’s perception and fatigue levels while interacted with new

technologies needed further research, such as roster, break time…

Conclusion

Cranfield has remote tower, airport, aircraft, ATCOs which are

the best resources for cooperative research


Q & A

Happiness only Real

When Shared

Wen-Chin Li PhD. CErgS.

Safety and Accident Investigation Centre

Transport Theme

Cranfield University, U.K.

E-mail: [email protected];

Tel:+44 1234 758527

mailto:[email protected]

tel:+44

Fatigue Risk Management

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