Preliminary investigation of sleep-related driving fatigue experiment in Indonesia

Kadek Heri Sanjaya, Yukhi Mustaqim Kusuma Sya'Bana, Shaun Hutchinson, Cyriel Diels


Sleep-related driving fatigue has been recognised as one main cause of traffic accidents. In Indonesia, experiment-based driving fatigue study is still very limited, therefore it is necessary to develop laboratory-based experiment procedure for sleep-related fatigue study. In this preliminary study, we performed a literature review to find references for the procedure and three pilot experiments to test the instruments and procedure to be used in measuring driving fatigue. Three subjects participated, both from experienced and inexperienced drivers. Our pilot experiments were performed on a driving simulator using OpenDS software with brake and lane change test reaction time measurement. We measured sleepiness by using Karolinska Sleepiness Scale (KSS) Questionnaire. The conditions of the experiment were based on illumination intensity as well as pre- and post-lunch session. We found that lane change reaction time is more potential than brake reaction time to measure driving performance as shown by the more fluctuating data. Post-lunch seems to induce drowsiness greater than illumination intensity. KSS questionnaire seems non-linear with driving performance data. We need to test further these speculations in the future studies involving a sufficient number of subjects. We also need to compare the effect of circadian rhythm and sleep deprivation on driving fatigue. The use of eye closure and physiological measurement in further study will enable us to measure driving fatigue more objectively. Considering the limitations, more preliminary experiments are required to be performed before conducting the main experiment of driving fatigue.


driving fatigue; sleepiness; experiment procedure; driving simulation

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K. H. Sanjaya et al., “Review on the application of physiological and biomechanical measurement methods in driving fatigue detection,” J. Mechatronics, Electr. Power, Veh. Technol., vol. 7, no. 1, p. 35, Jul. 2016. crossref

“Kecelakaan Lalu Lintas Menjadi Pembunuh Terbesar Ketiga | BADAN INTELIJEN NEGARA REPUBLIK INDONESIA.” [Accessed: 25-Feb-2016]. online

W. Sun et al., “Blink Number Forecasting Based on Improved Bayesian Fusion Algorithm for Fatigue Driving Detection,” Math. Probl. Eng., pp. 1–13, 2015. crossref

J. F. May and C. L. Baldwin, “Driver fatigue: The importance of identifying causal factors of fatigue when considering detection and countermeasure technologies,” Transp. Res. Part F Traffic Psychol. Behav., vol. 12, no. 3, pp. 218–224, 2009. crossref

A. Sahayadhas et al., “Detecting driver drowsiness based on sensors: A review,” Sensors (Switzerland), vol. 12, no. 12, pp. 16937–16953, 2012. crossref

M. Mahachandra et al., “Sleepiness Pattern of Indonesian Professional Driver Based on Subjective Scale and Eye Closure Activity,” Int. J. Basic Appl. Sci., vol. 11, no. 6, pp. 87–96, 2011. online

O. D. Sutrisno, “Peristiwa | Dalam 16 Bulan, 140 Kecelakaan Terjadi di….” [Accessed: 16-Jan-2017]. online

M. L. Lee et al., “High risk of near-crash driving events following night-shift work.,” Proc. Natl. Acad. Sci. U. S. A., vol. 113, no. 1, pp. 176–81, 2016. crossref

L. L. Di Stasi et al., “Microsaccade and drift dynamics reflect mental fatigue.,” Eur. J. Neurosci., vol. 38, no. 3, pp. 2389–2398, 2013. crossref

X. Fan et al., “Electroencephalogram assessment of mental fatigue in visual search,” Biomed. Mater. Eng., vol. 26, no. 37, pp. 1455–1463, 2015. crossref

I. N. Isnainiyah et al., “Analysis of sleep deprivation effect to driving performance using reactiontest simulation,” in Proceedings of 2014 International Conference on Information, Communication Technology and System, ICTS 2014, 2014, vol. 4, pp. 7–12. crossref

P. Green and H. Jeong, “SAE and ISO Standards for Warnings and Other Driver Interface Elements: A Summary,” 2013.


S. Pournami et al., “Comparing the NHTSA and ISO Occlusion Test Protocols : How Many Participants are Sufficient ?,” in Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2015, no. November, pp. 110–116. crossref

I. Organization for Standardization, Road vehicles — Ergonomic aspects of transport information and control systems — Simulated lane change test to assess in- vehicle secondary task demand. 2010, p. 52. online

Daimler Chrysler AG Research and Technology, “Lane Change Test 1 . 2 User Guide,” Test. DaimlerChrysler AG Research and Technology, pp. 1–11, 2005. online

“OpenDS - ConTRe Task (OpenDS Pro).” [Accessed: 05-Jan-2017]. online

“Stanford Sleepiness Scale.” [Accessed: 26-Jan-2017]. online

S. J. Frenda et al., “Sleep deprivation and false memories.,” Psychol. Sci., p. First online view, 2014. crossref

R. Atchley et al., “Event-related potential correlates of mindfulness meditation competence,” Neuroscience, vol. 320, no. November, pp. 83–92, 2016. crossref

S. Lee et al., “Effect of simultaneous exposure to extremely short pulses of blue and green light on human pupillary constriction,” J. Physiol. Anthropol., vol. 35, no. 1, p. 20, 2016. crossref

C. Ahlstrom et al., “Fit-for-duty test for estimation of drivers’ sleepiness level: Eye movements improve the sleep/wake predictor,” Transp. Res. Part C Emerg. Technol., vol. 26, pp. 20–32, 2013. crossref

M. E. Howard et al., “Specific sleepiness symptoms are indicators of performance impairment during sleep deprivation,” Accid. Anal. Prev., vol. 62, pp. 1–8, 2014. crossref

A. Å. Miley et al., “Comparing two versions of the Karolinska Sleepiness Scale (KSS),” Sleep Biol. Rhythms, vol. 14, no. 3, pp. 257–260, 2016. crossref

T. Åkerstedt et al., “Subjective sleepiness is a sensitive indicator of insufficient sleep and impaired waking function,” J. Sleep Res., vol. 23, no. 3, pp. 240–252, 2014. crossref

I. Organization for Standardization, Road vehicles — Measurement of driver visual behaviour with respect to transport information and control systems Part 1: Definitions and parameters, no. June. 2014. online

N. Reed et al., “SCOTSIM : An Evaluation Of The Effectiveness Of Two Truck Simulators For Professional Driver Training,” Wokingham, 2007.


M. M. Lorist et al., “The influence of mental fatigue and motivation on neural network dynamics; an EEG coherence study,” Brain Res., vol. 1270, pp. 95–106, 2009. crossref

B.G Simon-Morton et al., “Keep your eyes on the road: young driver crash risk increases according to duration of distraction,” J. Adolesc. Health, vol. 54, no. 5, pp. S61–S67, 2014. crossref

R. D. Foss and A. H. Goodwin, “Distracted driver behaviors and distracting conditions among adolescent drivers: findings from a naturalistic driving study,” J. Adolesc. Health, vol. 54, no. 5, pp. S50–S60, 2014. crossref

A.K. Pradhan et al., “Peer passenger influences on male adolescent drivers’ visual scanning behavior during simulated driving,” J. Adolesc. Health, vol. 54, no. 5, pp. S42–S49, 2014. crossref

E. Kasneci et al., “Driving with binocular visual field loss? A study on a supervised on-road parcours with simultaneous eye and head tracking,” PLoS One, vol. 9, no. 2, 2014. crossref

J. Paone et al., “Baseline face detection, head pose estimation, and coarse direction detection for facial data in the SHRP2 naturalistic driving study,” in IEEE Intelligent Vehicles Symposium, Proceedings, 2015, vol. 2015–Augus, pp. 174–179. crossref

A. Dasgupta et al., “A vision-based system for monitoring the loss of attention in automotive drivers,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 4, pp. 1825–1838, 2013. crossref

X. Wu et al., “Pilot’s visual attention allocation modeling under fatigue,” Technol. Heal. Care, vol. 23, no. s2, pp. S373–S381, 2015. crossref

C. Diels et al., “Full Time Through Junction Running Simulation Study,” Wokingham, 2010. online

R. O. Phillips and F. Sagberg, “Road accidents caused by sleepy drivers: Update of a Norwegian survey,” Accid. Anal. Prev., vol. 50, no. May 2014, pp. 138–146, 2013. crossref

L. A. Reyner et al., “‘Post-lunch’ sleepiness during prolonged, monotonous driving — Effects of meal size,” Physiol. Behav., vol. 105, no. 4, pp. 1088–1091, 2012. crossref

S. Garbarino et al., “Sleepiness, Safety and Transport,” J. Ergon., vol. S3, no. 1, pp. 0–6, 2014. crossref

T. H. Monk, “The post-lunch dip in performance,” Clin. Sports Med., vol. 24, no. 2, pp. 15–23, 2005. crossref

V. van der Vinne et al., “Timing of Examinations Affects School Performance Differently in Early and Late Chronotypes,” J. Biol. Rhythms, vol. 30, no. 1, pp. 53–60, 2015. crossref

D. Hallvig et al., “Real driving at night – Predicting lane departures from physiological and subjective sleepiness,” Biol. Psychol., vol. 101, pp. 18–23, 2014. crossref

Y. Shimomura and T. Katsuura, “Sustaining biological welfare for our future through consistent science.,” J. Physiol. Anthropol., vol. 32, no. 1, p. 1, 2013. crossref

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