Human Factors evaluation of Automation Karel Brookhuis

1. Human Factors evaluation of Automation Karel Brookhuis University of Groningen Delft University of Technology

2. Ward & Brookhuis(Driving Assessment, 2001) • Crashes: 85% directly attributable to the driver • Costs: 7-10 Billion € in the Netherlands

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 problem • The human factor, i.e. the driver  behaviour, needs & acceptance

4. 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

5. 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

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

7. active support: semi-automaticexample: ACC Adaptive Cruise Control (ACC) Field studies and modelling Simulator studies

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

9. Problems ACC • Liability in case of accident • Complacency • Behavioural change

10. Simulator study (Hoedemaeker, 1999) • 40 drivers, different “types”: • high & low speed preference • high & low focus (ability)

11. Driving Simulator

12. ACC: Minimum Time Headway

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

14. Opinion about ACC system BeforeAfter • 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%

15. 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

16. Benefits • No (active) driver involved • No human error • (Saving costs)

17. Problems • Acceptance • Loss of skills • Liability in case of serious accident

18. Report “AVG onderweg” Bart van Arem

19. Study: emergency situation on an automated highway

20. Driving Simulator

21. Emergency situation on automated highway

22. Reactions of subjects to emergency situation

23. Attentionresources Short-term store Stimuli Responses Decision and response selection Response execution Perception workingmemory long-termmemory Memory Feedback Expectations

24. Automatic Public Transport ? Phileas (automated PT, in Eindhoven) Handing over control to a vehicle

25. Phileas by Advanced Public Transport Systems (APTS bv)

26. 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% !!!

27. Pictures of the Phileas(look at www.phileas.nl)

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

29. So, make transport automatic ? Vehicle taking over control • Simulator study • 25 drivers: • 12 drivers from Hermes, 3 trips • 13 drivers from Arriva, 8 trips

30. Route

31. Route

34. 1.6 1.4 1.2 1 Acceptance score Arriva usef 0.8 Hermes usef Arriva satisf Acceptance Questionnaire factors “useful” and “satisfactory” 0.6 Hermes satisf 0.4 0.2 0 Pre test Post test -0.2 -0.4 2x

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 !

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)

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)

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

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

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)

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