Vehicle control and drowsiness - VTI

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AcknowledgementThis report was produced under a contract with Autoliv Research. We would liketo express our gratitude to Jan-Erik Källhammer at Autoliv Research who hassupported the work not just financially but also provided very valuable feedbackand guiding ideas for the production of this report.VTI meddelande 922A
ContentPageSummary 7Sammanfattning 9Part one: Literature Study 111 Introduction 111.1 Exposure to accidents due to drowsiness (statistics) 121.2 Individual driving behaviour and incompleteness of onesingle measure of fatigue 121.3 Validation 131.4 Day and night driving 131.5 Requirements for drowsiness warning systems 141.6 Means of research 142 Terms and definitions 153 Variables looked at to detect drowsiness 164 Methods to identify drowsiness in drivers 174.1 Physiological measures 174.2 Ocular dynamics 184.3 Steering wheel movements and steering wheel variability 204.4 Lateral position 224.5 Time-to-line crossing (TLC) 294.6 Combination of different methods 325 Commercially available fatigue monitors 355.1 SAM 355.2 DAS 2000 Road Alert System 365.3 SafeTRAC 365.4 TravAlert 365.5 Companies that are planning to introduce drowsiness orfatigue detection and warning systems in vehicles 376 Patents 387 Problems related to automatic drowsiness detection 397.1 Detecting vs. predicting drowsiness 397.2 Gender and age of the driver 397.3 Overtaking and road curvature 408 Further literature of interest 419 Summary 429.1 Eyelid closure 429.2 Brain activity – EEG 429.3 Other physiological measures 439.4 Driving performance measures 439.5 Observations of body motions 439.6 Mathematical models 43VTI meddelande 922A
Page 1 and 2: VTI meddelande 922A • 2002Vehicle
Page 3 and 4: Publisher:Publication:VTI Meddeland
Page 5: ForewordThis study was commissioned
Page 9 and 10: Vehicle Control and Drowsinessby Al
Page 11 and 12: Part one: Literature Study1 Introdu
Page 13 and 14: 1.3 ValidationA relevant problem in
Page 15 and 16: 2 Terms and definitions“Fatigue:
Page 17 and 18: 4 Methods to identify drowsiness in
Page 19 and 20: ight light conditions, when people
Page 21 and 22: Micro-correction in steeringMicro-c
Page 23 and 24: in response to conditions in the ro
Page 25 and 26: driving performance measures. Some
Page 27 and 28: SD lateral positionFigure 10 Standa
Page 29 and 30: Different measures have been used i
Page 31 and 32: Figure 12 Prediction results for 50
Page 33 and 34: 1: AVEOBS, which is an observer rat
Page 35 and 36: 5 Commercially available fatigue mo
Page 37 and 38: 5.5 Companies that are planning to
Page 39 and 40: 7 Problems related to automatic dro
Page 41 and 42: 8 Further literature of interestThe
Page 43 and 44: 9.3 Other physiological measuresPhy
Page 45 and 46: Note: the summary only illustrates
Page 47 and 48: Figure 16 Lateral position of a dri
Page 49 and 50: Example 2, subject number 17Figure
Page 51 and 52: 11 Analysis of drowsiness ratingIn
Page 53 and 54: 0,60,5SDLP (meters)0,40,30,2TiredAl
Page 55 and 56: As described in the previous sectio
Page 57 and 58:
109Tiredness876Predicted YTiredAler
Page 59 and 60:
14 Times driver change directionA s
Page 61 and 62:
A large number of previous studies
Page 63 and 64:
The two groups where compared in or
Page 65 and 66:
16 Frequency AnalysisAn analysis of
Page 67 and 68:
The large power variation between i
Page 69 and 70:
Fourier transform on the two groups
Page 71 and 72:
16.2 Power Spectrum estimate via Bu
Page 73 and 74:
Table 9 Average value of dependent
Page 75 and 76:
18.4 Time to Line Crossing - TLCIn
Page 77 and 78:
19 References1. Wierwille, WW & Wre
Page 79 and 80:
29. PERCLOS: A Valid Psychophysiolo
Page 81 and 82:
54. Chiu-Geng, Lin: Lane Sensing an
Page 83 and 84:
87. Haworth, NL & Vulcan, AP: Testi
Page 85 and 86:
Appendix 1Page 1 (2)TLC formulaeVTI
Page 87 and 88:
TLC calculationAppendix 2Page 1 (1)
Page 89 and 90:
Appendix 4Page 1 (2)Definition of t
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