Vol 6, No 6 (2015) > Industrial Engineering >

Fatigue Measurement of Driving Activity on Male Motorcycle Drivers based on Cognitive, Physiological, and Subjective Approaches

Erlinda Muslim, Boy Nurtjahyo Moch, Maya Arlini Puspasari, Raja Alfredo Siregar


Abstract: Driver
fatigue is one of the major causes of serious road accidents. The purpose of
this research is to measure the effect of cognitive, physiological, and
subjective approaches towards fatigue, while driving a motorcycle for 2 hours. Another objective of this
research is to determine the differences in the level of fatigue in the studied
age category. In this
study, there were two
age categories, namely the productive
age category (16-35 years old) and the adult age category (35-60 years old). This research implemented three approaches:  cognitive, physiological, and subjective. In the cognitive approach, levels of concentration and stress (tension)
were measured by using Design
Tools, such as Simple
Reaction Time and Stroop Test. In the physiological
approach, two measurements were taken:
measurement of heart rate using Polar Heart Rate and measurement of blood
pressure (systole and diastole) using the Omron Blood Pressure test.
Meanwhile, the subjective approach was calculated using the
9-scale Karolinska Sleepiness Scale (KSS). Also, the correlation between the
subjective approach and two other approaches (cognitive and physiological) used the Spearman-Rank test. Results obtained from this study on the
influence of heart rate on the level of fatigue are significantly found in both age categories (productive and adult age
category). Meanwhile, the significance (influence) of blood pressure on the level
of fatigue is found only in the adult
age category. Simple Reaction Time measurement results were found to be significant
on the level of fatigue in the adult
age category. Thus, it can be said that in the adult age category, there
is a
influence between the level of fatigue and concentration level.
Keywords: Cognitive; Fatigue, KSS; Motorcycle driver; Psychophysical; Subjective

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Baulk, S.D., Biggs, S.N., Reid, K.J., van den Heuvel, C.J., Dawson, D., 2008. Chasing the Silver Bullet: Measuring Driver Fatigue using Simple and Complex Tasks. Accident Analysis and Prevention, Volume 40(1), pp. 396–402

Dawson, D., Searle, A.K., Paterson, J.L., 2014. Look Before You (S)leep: Evaluating the use of Fatigue Detection Technologies within a Fatigue Risk Management System for the Road Transport Industry. Sleep Medicine Review, Volume 18, pp. 141–152

Desai, A.V., Haque, M.A., 2006. Vigilance Monitoring for Operator Safety: A Simulation Study on Highway Driving. Journal of Safety Research, Volume 37, pp. 139–147

Dinges, D.F., Powell, J.W., 1985. Microcomputer Analyses of Performance on a Portable, Simple Visual RT Task during Sustained Operations. Behavior Research Methods, Instruments, & Computers, Volume 17, pp. 652–655

Egelund, N., 1982. Spectral Analysis of Heart Rate Variability as an Indicator of Driver Fatigue. Ergonomics, Volume 25(7), pp. 663–672

Gastaldi, M., Rossi, R., Gecchele, G., 2014. Effects of Driver Task Related Fatigue on Driving Performance. Procedia - Social and Behavioral Sciences, Volume 111, pp. 955–964

Indonesia Statistics Agency, 2012. Available online at http://www.bps.go.id/linkTabelStatis/view/id/1415

Jagannath, M., Balasubramanian, V., 2014. Assessment of Early onset of Driver Fatigue using Multimodal Fatigue Measures in a Static Simulator. Applied Ergonomic, Volume 45(4), pp. 1140–1147

Jakarta Globe, 2015. Indonesia’s Traffic Deaths on Rise: WHO, Available at: http://jakartaglobe.beritasatu.com/news/indonesias-traffic-deaths-on-rise-who

Kaida, K., Takahashi, M., Akerstedt, T., Nakata, A., Otsuka, Y., Haratani, T., Fukasawa, K., 2006. Validation of the Karolinska Sleepiness Scale against Performance and EEG Variables. Clin Neurophysiol, Volume 117(7), pp. 1574–1581

May, J., Baldwin, C.L., 2009. Driver Fatigue: The Importance of Identifying Causal Factors of Fatigue when Considering Detection and Countermeasure Technologies. Transportation Research Part F: Traffic Psychology and Behaviour, Volume 12(3), pp. 218–224

State Intelligence Agency, 2011. Available online at: http://www.bin.go.id/awas/detil/ 197/4/21/03/2013/kecelakaan-lalu-lintas-menjadi-pembunuh-terbesar-ketiga

Ministry of Health in Republic of Indonesia (Depkes RI), 2009. Profil Kesehatan Indonesia. Jakarta: Departemen Republik Indonesia

Verwey, W.B., Zaidel, D.M., 2000. Predicting Drowsiness Accidents from Personal Attributes, Eye Blinks and ongoing Driving Behaviour. Personality and Individual Differences, Volume 28, pp. 123–142

Williamson, A., Lombardi, D.A., Folkard, S., Stutts, J., Courtney, T.K., Connor, J.L., 2011. The Link between Fatigue and Safety. Accident Analysis and Prevention, Volume 43, pp. 498–515

World Life Expectancy, 2015. Health Profile : Indonesia, Available at: http://www.worldlifeexpectancy.com/country-health-profile/indonesia