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Human Factors evaluation of Automation Karel Brookhuis. University of Groningen Delft University of Technology. Ward & Brookhuis (Driving Assessment, 2001). Crashes: 85% directly attributable to the driver Costs: 7-10 Billion € in the Netherlands. - PowerPoint PPT Presentation
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Experimental & Work Psychology Transport Policy & Logistics 1
Human Factors evaluation of Automation
Karel Brookhuis
University of Groningen Delft University of Technology
Experimental & Work Psychology Transport Policy & Logistics 2
Ward & Brookhuis(Driving Assessment, 2001)
Crash Feature
59%26%
12%3%
Driver Error Driver Impairment
Environment Vehicle
Crashes: 85% directly attributable to the driver
Costs: 7-10 Billion €
in the Netherlands
Experimental & Work Psychology Transport Policy & Logistics 3
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 problemThe human factor, i.e. the driver
behaviour, needs & acceptance
Experimental & Work Psychology Transport Policy & Logistics 4
ADAS benefitsADAS 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
Experimental & Work Psychology Transport Policy & Logistics 5
Potential ADAS problem driver 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
Experimental & Work Psychology Transport Policy & Logistics 6
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
Experimental & Work Psychology Transport Policy & Logistics 7
active support: semi-automaticexample: ACC
active support: semi-automaticexample: ACC
Adaptive Cruise Control (ACC)
Field studies and modelling Simulator studies
Experimental & Work Psychology Transport Policy & Logistics 8
Benefits ACCBenefits ACC
Decrease human error, probably accidents Increasing efficiency (decreasing headway) Reduction in fuel use of 10% (Van Arem,
2003)
Experimental & Work Psychology Transport Policy & Logistics 9
Problems ACCProblems ACC
Liability in case of accident Complacency Behavioural change
Experimental & Work Psychology Transport Policy & Logistics 10
Simulator study (Hoedemaeker, 1999) 40 drivers, different “types”:
high & low speed preference high & low focus (ability)
Experimental & Work Psychology Transport Policy & Logistics 11
Driving Simulator
Experimental & Work Psychology Transport Policy & Logistics 12
ACC: Minimum Time Headway
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
highspeed/
highfocus
lowspeed/
highfocus
highspeed/
lowfocus
lowspeed/
lowfocus
Min
imal
Tim
e H
ead
way
(s) without ACC
with ACC
Experimental & Work Psychology Transport Policy & Logistics 13
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
Experimental & Work Psychology Transport Policy & Logistics 14
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%
Experimental & Work Psychology Transport Policy & Logistics 15
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
So, make driving automatic ? Vehicle taking over control
Experimental & Work Psychology Transport Policy & Logistics 16
BenefitsBenefits
No (active) driver involved No human error (Saving costs)
Experimental & Work Psychology Transport Policy & Logistics 17
ProblemsProblems
Acceptance Loss of skills
Liability in case of serious accident
Experimental & Work Psychology Transport Policy & Logistics 18
Report “AVG onderweg” Bart van Arem
Experimental & Work Psychology Transport Policy & Logistics 19
Study: emergency situation on an automated highway
Experimental & Work Psychology Transport Policy & Logistics 20
Driving Simulator
Experimental & Work Psychology Transport Policy & Logistics 21
Emergency situation on automated highway
Experimental & Work Psychology Transport Policy & Logistics 22
Reactions of subjects to emergency situation
Reacties Tijd Proportie bestuurdersGeen reactie - 50 %Remde Laat > 14 s 15 %Remde Niet zo snel 9-14 s 30 %Remde Vroeg < 9 s 5 %
Experimental & Work Psychology Transport Policy & Logistics 23
PerceptionDecision and
response selection
Response
execution
workingmemory
long-termmemory
Memory
Short-term storeStimuli Responses
Feedback
Attentionresources
Expectations
Experimental & Work Psychology Transport Policy & Logistics 24
Automatic Public Transport ?
Phileas
(automated PT, in Eindhoven)
Handing over control to a vehicle
Experimental & Work Psychology Transport Policy & Logistics 25
Phileas by Advanced Public Transport Systems (APTS bv)
Experimental & Work Psychology Transport Policy & Logistics 26
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% !!!
So, make transport automatic ? Vehicle taking over control
Experimental & Work Psychology Transport Policy & Logistics 27
Pictures of the Phileas(look at www.phileas.nl)
Experimental & Work Psychology Transport Policy & Logistics 28
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
Experimental & Work Psychology Transport Policy & Logistics 29
Simulator study 25 drivers:
12 drivers from Hermes, 3 trips13 drivers from Arriva, 8 trips
So, make transport automatic ? Vehicle taking over control
Experimental & Work Psychology Transport Policy & Logistics 30
Route
Experimental & Work Psychology Transport Policy & Logistics 31
Route
Experimental & Work Psychology Transport Policy & Logistics 32
Experimental & Work Psychology Transport Policy & Logistics 33
Experimental & Work Psychology Transport Policy & Logistics 34
Acceptance Questionnaire
factors “useful” and “satisfactory”
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Pre test Post test
2x
Acc
epta
nce
scor
e
Arriva usef
Hermes usef
Arriva satisf
Hermes satisf
Experimental & Work Psychology Transport Policy & Logistics 35
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 !
Experimental & Work Psychology Transport Policy & Logistics 36
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)
Experimental & Work Psychology Transport Policy & Logistics 37
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)
Experimental & Work Psychology Transport Policy & Logistics 38
Automation Traffic & Transport:Concern 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
Experimental & Work Psychology Transport Policy & Logistics 39
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
Experimental & Work Psychology Transport Policy & Logistics 40
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)
Experimental & Work Psychology Transport Policy & Logistics 41