Human Factors evaluation of Automation

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• Human Factors evaluation of Automation
• Karel Brookhuis

University of Groningen Delft
University of Technology
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Ward Brookhuis(Driving Assessment, 2001)

• Crashes 85 directly attributable to the driver
• Costs 7-10 Billion
• in the Netherlands

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Advanced Driver Assistance Systems (Intelligent
Transport Systems)

• Could ADAS applications, help then ??
• Yes, benefits are to be expected (Van Arem, 2003)
• 10 15 crash reduction ? saving 1 Billion
• But, there is a potential problem
• The human factor, i.e. the driver
  ? behaviour, needs acceptance

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ADAS benefits

• Better drivers, leading to
• Considerable accident reduction (10-15)
• Optimising road capacity
• Reduction in fuel usage and pollution (..?)
• Decrease in societal (financial, human,
  environmental) cost

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Potential ADAS problem ? driver

• Change in task (supervising i.s.o. driving)
• Shifting the driver out-of-the-loop
• Distraction
• Behavioural adaptation / change
• Attitudes acceptance
• Complacency
• Individual differences
• Liability issues

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Advanced Driver Assistance Systems (Intelligent
Transport Systems)

• Systems operation modes - functionalities
• advisory - information provision
• Route Guidance, RDS-TMC, ISA
• semi-automatic - active support, taking over part
  of the control
• ACC, ICC, ISA
• automatic - taking over control completely
• Path, Phileas

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active support semi-automaticexample ACC

• Adaptive Cruise Control (ACC)
• Field studies and modelling
• Simulator studies

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Benefits ACC

• Decrease human error, probably accidents
• Increasing efficiency (decreasing headway)
• Reduction in fuel use of 10 (Van Arem, 2003)

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Problems ACC

• Liability in case of accident
• Complacency
• Behavioural change

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Simulator study (Hoedemaeker, 1999)

• 40 drivers, different types
• high low speed preference
• high low focus (ability)

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Driving Simulator
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ACC Minimum Time Headway
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Results

• Reduction in minimum time headway
• Specifically for low speed drivers
• High speed drivers show (behavioural change)
• More left lane driving
• More overtaking
• More weaving

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Opinion about ACC system

• Before After
• positive It increases traffic safety 65 55
• positive It enhances traffic flow 30 50
• negative No control of driving 40 55
• negative Sudden braking 60 55

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So, make driving automatic ? Vehicle taking over
control

• Path vehicles
• automated vehicles (San Diego N11)
• simulator experiment in Groningen
• Demonstrations in the Netherlands
• driving over magnetic nails (Path vehicles)
• Phileas Automatic Public Transport System

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Benefits

• No (active) driver involved
• No human error
• (Saving costs)

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Problems

• Acceptance
• Loss of skills
• Liability in case of serious accident

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Report AVG onderweg Bart van Arem
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Study emergency situation on an automated highway
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Driving Simulator
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Emergency situation on automated highway
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Reactions of subjects to emergency situation
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Expectations
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• Automatic Public Transport ?
• Phileas
• (automated PT, in Eindhoven)
• Handing over control to a vehicle

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Phileas by Advanced Public Transport Systems
(APTS bv)
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So, make transport automatic ? Vehicle taking
over control

• Phileas (automated PT)
• Automated bus ? metro
• Twice as fast as normal bus transport
• Cheaper than metro
• 120 - 180 passengers
• Reduction in fuel use by 20
• Pollution reduction by 90 !!!

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Pictures of the Phileas(look at www.phileas.nl)
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• Relevant aspects of
• Automatic Bus Driving
• Different task, supervising i.s.o. driving
• Need of trust, believe, acceptance
• mistrust leads to misuse or non-use
• too much trust leads to complacency

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So, make transport automatic ? Vehicle taking
over control

• Simulator study
• 25 drivers
• 12 drivers from Hermes, 3 trips
• 13 drivers from Arriva, 8 trips

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• Route

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• Route

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• Acceptance Questionnaire
• factors useful and satisfactory

1.6
1.4
1.2
1
Acceptance score
Arriva usef
0.8
Hermes usef
Arriva satisf
0.6
Hermes satisf
0.4
0.2
0
Pre test
Post test
-0.2
-0.4
2x
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Incident 1 car blocking the road ? braking
ample in time ? returning to half-automatic

• Incident 2 cyclist running red light
• ? 1st time 72 okay, but 28 not !
• ? 2nd time 100 okay !

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Conclusions experiment

• System well accepted by the ordinary bus drivers
• Effects with respect to unexpected events
• Supervising meant in principle patiently awaiting
  in the beginning, complacency
• Training on unexpected events seems feasible
• Training is necessary, preferably in simulator
• Special driving license
• Periodic training and licensing (cf. pilots in
  airplanes)

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General problems with technology

• HMI
• rate, timing, mode (behaviour)
• acceptance (compliance)
• Adaptation
• acceptance (self judgement vs technology)
• reliance ? operator complacency
• Misuse
• technology as management tool (owner)
• acceptance (tampering)

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Automation Traffic TransportConcern
acceptance behaviour

• Who would like a master in the car
• some would ? elderly for certain
• some should ? multi-convicted
• Dangerous goods haulage
• high risk
• high responsibilty

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SummaryAutomation in Traffic

• Change in task (supervising i.s.o. driving)
• Problem shifting the driver out-of-the-loop
• Results so far
• Driver is inclined to sit back
• Active involvement can be trained
• Adapt configuration to keep the driver active
• Licensing should be adapted, specific, and not
  ever-lasting

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Final conclusions

• Efforts are multi-method, multi-disciplinary,
  multi-institutional and multi-national.
• Key is the development of practical methods with
  valid tolerance levels.
• Problem is (still) finding criteria for
  (un)safety.
• Definitely integration of systems !!!
• GIDS (Michon, 1993)
• AIDA (Van Arem, 2003)

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