Commonly Used Assessment Method to Evaluate Mental Workload for Multiple Driving Distractions: A Systematic Review
,
Abstract
Background: We aimed to find the commonly used assessments to evaluate driver’s mental workload and its relationship with driving distraction.
Methods: Academic articles such as journals, books, reports and conference papers that are related to workload measurements methods used in identifying mental workload among drivers that are dated from Jan 2015 to Apr 2020 were used in this paper. Then, PRISMA checklist and flow diagram are being applied.
Results: The few commonly used assessments in evaluating mental workload among drivers are Karolinska Sleepiness Scale (KSS), NASA TLX, Electroencephalogram (EEG), Heart Rate (HR), eye tracking and driving performance. Moreover, different types of driving distractions show to affect the driver’s mental workload in one way or another when being evaluated using these assessments.
Conclusion: The finding of this study can be used to find the gap for future research in vehicle safety by using multimodal monitoring of different types of assessments to increase the validity and robustness in driving assessment.
1. Borghini G, Astolfi L, Vecchiato G et al (2014). Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. Neurosci Biobehav Rev, 44:58-75.
2. World Health Organization (2018). Top 10 causes of death. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
3. Brookhuis KA, Waard DD (2010). Monitor-ing drivers’ mental workload in driving simulators using physiological measures. Accid Anal Prev, 42: 898-903.
4. KongW, Zhou Z, Jiang B et al (2017). As-sessment of driving fatigue based on in-tra/inter-region phase synchronization. Neurocomputing, 219: 474-482.
5. Almahasneh H, Chooi WT, Kamel N et al (2014). Deep in thought while driving: An EEG study on drivers’ cognitive distrac-tion. Transp Res F Traffic Psychol Behav, 26: 218-226.
6. Auberlet JM, Rosey F, Anceaux F et al (2012). The impact of perceptual treat-ments on driver’s behavior: from driving simulator studies to field tests-first re-sults. Accid Anal Prev, 45: 91- 98.
7. Mastrigt HS, Groenesteijn L, Vink P et al (2017). Predicting passenger seat comfort and discomfort on the basis of human, context and seat characteristics: a litera-ture review. Ergonomics, 60(7): 889-911.
8. Rumschlag G, Palumbo T, Martin A et al (2015). The effects of texting on driving performance in a driving simulator: The influence of driver age. Accid Anal Prev, 74: 145-149.
9. Yusoff AR, Deros BM, DaruisDDI et al (2016). Tabialis anterior muscle contrac-tion on driver’s knee angle posture less than 101 deg for foot pressing and re-leasing an automotive pedal. Malaysian Journal of Public Health Medicine, 1: 102-107.
10. Moher D, Liberati A, Tetzlaff J et al (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med, 7(9): e1000097.
11. Shakouri M, Ikuma LH, Aghazadeh F et al (2018). Analysis of the sensitivity of heart rate variability and subjective workload measures in a driving simulator: The case of highway work zones. International Jour-nal of Industrial Ergonomics, 66: 136-145.
12. Belyusar D, Reimer B, Mehler B et al (2016). A field study on the effects of digital bill-boards on glance behavior during high-way driving. Accid Anal Prev, 88: 88-96.
13. Ahlström C, Anund A, Fors C et al (2018). Effects of the road environment on the development of driver sleepiness in young male drivers. Accid Anal Prev, 112: 127-134.
14. Kountouriotis GK, Merat N (2016). Leading to distraction: Driver distraction, lead car, and road environment. Accid Anal Prev, 89: 22-30.
15. Chen J, Wang H, HuacC (2018). Assess-ment of driver drowsiness using electro-encephalogram signals based on multiple functional brain networks. Int J Psychophys-iol, 133: 120-130.
16. Faure V, Lobjois R, Benguigui N (2016). The effects of driving environment com-plexity and dual tasking on drivers’ men-tal workload and eye blink behaviour. Transp Res F Traffic Psychol Behav, 40: 78-90.
17. Farahmand B & Boroujerdian AM (2018). Effect of road geometry on driver fatigue in monotonous environments: A simula-tor study. Transp Res F Traffic Psychol Behav, 58: 640-651.
18. Oviedo-Trespalacios O, Haque MM, King M et al (2017). Effects of road infrastruc-ture and traffic complexity in speed adap-tation behaviour of distracted drivers. Ac-cid Anal Prev, 101: 67-77.
19. Siam MFM, Isa MHM, Borhan N et al (2015). Measurement of Driver Distrac-tion in Malaysia’s Traffic Environment: A Driving Simulator Study. Journal of Mechani-cal Engineering and Sciences, 8: 1472-1480.
20. Tarabay R, Abou-Zeid M (2018). Assessing the effects of auditory-vocal distraction on driving performance and physiologi-cal measures using a driving simulator. Transp Res F Traffic Psychol Behav, 58: 351-364.
21. Perrier J, Jongen J, Vuurman E et al (2016). Driving performance and EEG fluctua-tions during on-the-road driving follow-ing sleep deprivation. Biol Psychol, 121(Pt A):1-11.
22. Ahn S, Nguyen T, Jang H et al (2016). Ex-ploring Neuro-Physiological Correlates of Drivers’ Mental Fatigue Caused by Sleep Deprivation Using Simultaneous EEG, ECG, and fNIRS Data. Front Human Neursci, 10:219.
23. Wen H, Sze NN, Zeng Q (2019). Effect of Music Listening on Physiological Condi-tion, Mental Workload, and Driving Per-formance with Consideration of Driver Temperament. Int J Environ Res Public Health, 16(15):2766.
24. Guo M, Li S, Wang L et al (2016). Research on the Relationship between Reaction Ability and Mental State for Online As-sessment of Driving Fatigue. Int J Environ Res Public Health, 13(12):1174.
25. Mohid IAM, Khamis NK, Noh NA et al (2019). Driver’s Response towards Dif-ferent Road Complexity: A Preliminary Study. The Japanese Journal of Ergonomics, 55 (Supplement): 1H3-6-1H3-6.
26. Sugiono S, Denny W, Andriani DP (2018). The Impact of Road Complexity on the Psychophysiological Load Experienced by Car DriversUsing Electroencephalog-raphy (EEG) Measurement of Brain-waves. Acta Neuropsychologica, 16(4) 361-374.
27. Kim SL, Yang JH (2018). Evaluation of the Effects of Driver Distraction Part 1: Based on Simulator Experiments. IEEE International Conference on Systems, Man, and Cybernetics, 2018: 1081-1086
28. Kim SL, Yang JH (2018). Evaluation of the Effects of Driver Distraction Part 2: Based on Real Vehicle Experiments. IEEE International Conference on Systems, Man, and Cybernetics, 2018: 1087-1092.
29. He D, Donmez B, Liu CC et al (2019). High Cognitive Load Assessment in Drivers through Wireless Electroencephalography and the Validation of a Modified N-Back Taska. IEEE Transactions on Human-Machine Systems, 49(4): 362-371.
30. Diaz-Piedra C, Gomez-Milan E, Stasi LLD (2019). Nasal skin temperature reveals changes in arousal levels due to time on task: An experimental thermal infrared imaging study. Appl Ergon, 81 :102870.
31. Getzmann S, Arnau S, Karthaus M et al (2018). Age-Related Differences in Pro-active Driving Behavior Revealed by EEG Measures. Front Human Neurosci, 12:321.
32. Foy HJ, Chapman P (2018). Mental work-load is reflected in driver behaviour, physiology, eye movements and prefron-tal cortex activation. Appl Ergon, 73: 90-99.
33. Sugiono S, Widhayanuriyawan D, Andriani DP (2017). Investigating the Impact of Road Condition Complexity on Driving Workload Based on Subjective Measure-ment using NASA TLX. MATEC Web of Conferences, 136 (2017): 02007.
34. Sugiono S, Widhayanuriyawan S, Andriyani DP (2018). Mental Stress Evaluation of Car Driver in Different Road Complexity Using Heart Rate Variability (HRV) Anal-ysis. Proceedings of the 2018 5th Interna-tional Conference on Bioinformatics Research and Applications, 2018: 90-94.
35. Strayer DL, Turrill J, Cooper JM et al (2015). Assessing Cognitive Distraction in the Automobile. Hum Factors, 57 (8): 1300-1324.
36. Alrefaie MT, Summerskill S, Jackon TW (2019). In a heartbeat: Using driver’s physiological changes to determine the quality T of a takeover in highly automat-ed vehicles. Accid Anal Prev, 131:180-190.
37. Prabhakar G, Madhu, Biswas P (2018). Comparing Pupil Dilation, Head Move-ment, and EEG for Distraction Detec-tion of Drivers. Proceedings of the 32nd Inter-national BCS Human Computer Interaction Conference (HCI), 69: 1-5.
38. Papantoniou P, Tannis G, Antoniou C et al (2016). Investigating the effect of area type and traffic conditions on distracted driving performance. Transp Res Proc, 14: 3839-3848.
39. Niu J, Wang X, Liu et al (2019). Effects of mobile phone use on driving perfor-mance in a multiresource workload sce-nario. Traffic Inj Prev, 20(1): 37-44.
40. Nowosielski RJ, Trick LM, Toxopeus R (2018). Good distractions: Testing the ef-fects of listening to an audiobook on driving performance in simple and com-plex road environments. Accid Anal Prev, 111: 202-209.
41. Paxion J, Galy E, Berthelon C (2015). Over-load depending on driving experience and situation complexity: Which strategies faced with a pedestrian crossing? Appl Ergon, 51: 343-349.
42. Rahman NIA, Dawal SZM, Yusoff N (2020). Driving mental workload and per-formance of ageing drivers. Transp Res F Traffic Psychol Behav, 69: 265-285.
43. Jeong H, Liu Y (2019). Effects of non-driving-related-task modality and road geometry on eye movements, lane-keeping performance, and workload while driving. Transp Res F Traffic Psychol Behav, 60:157-171.
44. Merat N Jamson AH (2013). The effect of three low-cost engineering treatments on driver fatigue: A driving simulator study. Accid Anal Prev, 50: 8-15.
45. Lansdown TC, Stephens AN, Walker GH (2015). Multiple driver distractions: A sys-temic transport problem. Accid Anal Prev, 74: 360-364.
46. Horberry T, Anderson J, Regan MA (2006). Driver distraction: The effects of concur-rent in-vehicle tasks, road environment complexity and age on driving perfor-mance. Accid Anal Prev, 38: 185- 191.
47. Zhao C, Zhao M, Liu J (2012). Electroen-cephalogram and electrocardiograph as-sessment of mental fatigue in a driving simulator. Accid Anal Prev, 45: 83-90.
48. Mohid IAM, Khamis NK (2018). Implica-tion of driving disturbance and road condition towards driver’s performance in simulated condition. Jurnal Kejuruteraan, 1(6): 33-39.
49. Lansdown TC, Stephens AN, Walker GH (2015). Multiple driver distractions: A sys-temic transport problem. Accid Anal Prev, 74: 360-367.
50. Schmidt E, Bullinger AC (2019). Mitigating passive fatigue during monotonous drives with thermal stimuli: Insights into the effect of different stimulation dura-tions. Accid Anal Prev, 126: 115-121.
51. Khamis NK, Deros BM, Schramm D et al (2016) Subjective and indirect methods to observe driver’s drowsiness and alert-ness: An overview. Journal of Engineering Science and Technology, 11(Sp. Iss. on ICE & ICIE 2015):28-39.
52. Gharagozlou F, Saraji GN, Mazloumi A et al (2015). Detecting driver mental fatigue based on EEG alpha power changes during simulated driving. Iran J Public Health, 44(12): 1693-1700.
53. Khamis NK, Ismail FR, Hesse B et al (2016). Suitability of heart rate as physio-logical measures tool to determine driv-ers’ performance impairment: A prelimi-nary study. Jurnal Teknologi, 78: 25-30.
54. Antonson A, Ahlström C, Mårdh S (2014). Landscape heritage objects’ effect on driving: A combined driving simulator and questionnaire study. Accid Anal Prev, 62: 168-177.
55. Gastaldi M, Rossi R, Gecchele G (2014). Ef-fects of driver task-related fatigue on driving performance. Procedia Social and Behavioral Sciences, 111: 955-964.
56. Naurois CJ, Bourdin C, Bougard C (2018). Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness. Accid Anal Prev, 121: 118-128.
57. Davenne D, Lericollais R, Sagaspe P (2012). Reliability of simulator driving tool for evaluation of sleepiness, fatigue and driv-ing performance. Accid Anal Prev, 45: 677- 682.
58. Hallvig D, Anund A, Fors Ca et al (2013). Sleepy driving on the real road and in the simulator—A comparison. Accid Anal Prev, 50: 44-50.
59. Otmani S, Pebayle T, Roge J et al (2005). Ef-fect of driving duration and partial sleep deprivation on subsequent alertness and performance of car drivers. Physiol Behav, 84: 715-724.
60. Ismail FR, Nuawi MZ, Schramm D et al (2016). Suitability of driving simulators as a tool to study driving fatigue due to vibration and environment: A review. Ma-laysian Journal of Public Health Medicine, Spe-cial Volume (1): 95-101.
2. World Health Organization (2018). Top 10 causes of death. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
3. Brookhuis KA, Waard DD (2010). Monitor-ing drivers’ mental workload in driving simulators using physiological measures. Accid Anal Prev, 42: 898-903.
4. KongW, Zhou Z, Jiang B et al (2017). As-sessment of driving fatigue based on in-tra/inter-region phase synchronization. Neurocomputing, 219: 474-482.
5. Almahasneh H, Chooi WT, Kamel N et al (2014). Deep in thought while driving: An EEG study on drivers’ cognitive distrac-tion. Transp Res F Traffic Psychol Behav, 26: 218-226.
6. Auberlet JM, Rosey F, Anceaux F et al (2012). The impact of perceptual treat-ments on driver’s behavior: from driving simulator studies to field tests-first re-sults. Accid Anal Prev, 45: 91- 98.
7. Mastrigt HS, Groenesteijn L, Vink P et al (2017). Predicting passenger seat comfort and discomfort on the basis of human, context and seat characteristics: a litera-ture review. Ergonomics, 60(7): 889-911.
8. Rumschlag G, Palumbo T, Martin A et al (2015). The effects of texting on driving performance in a driving simulator: The influence of driver age. Accid Anal Prev, 74: 145-149.
9. Yusoff AR, Deros BM, DaruisDDI et al (2016). Tabialis anterior muscle contrac-tion on driver’s knee angle posture less than 101 deg for foot pressing and re-leasing an automotive pedal. Malaysian Journal of Public Health Medicine, 1: 102-107.
10. Moher D, Liberati A, Tetzlaff J et al (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med, 7(9): e1000097.
11. Shakouri M, Ikuma LH, Aghazadeh F et al (2018). Analysis of the sensitivity of heart rate variability and subjective workload measures in a driving simulator: The case of highway work zones. International Jour-nal of Industrial Ergonomics, 66: 136-145.
12. Belyusar D, Reimer B, Mehler B et al (2016). A field study on the effects of digital bill-boards on glance behavior during high-way driving. Accid Anal Prev, 88: 88-96.
13. Ahlström C, Anund A, Fors C et al (2018). Effects of the road environment on the development of driver sleepiness in young male drivers. Accid Anal Prev, 112: 127-134.
14. Kountouriotis GK, Merat N (2016). Leading to distraction: Driver distraction, lead car, and road environment. Accid Anal Prev, 89: 22-30.
15. Chen J, Wang H, HuacC (2018). Assess-ment of driver drowsiness using electro-encephalogram signals based on multiple functional brain networks. Int J Psychophys-iol, 133: 120-130.
16. Faure V, Lobjois R, Benguigui N (2016). The effects of driving environment com-plexity and dual tasking on drivers’ men-tal workload and eye blink behaviour. Transp Res F Traffic Psychol Behav, 40: 78-90.
17. Farahmand B & Boroujerdian AM (2018). Effect of road geometry on driver fatigue in monotonous environments: A simula-tor study. Transp Res F Traffic Psychol Behav, 58: 640-651.
18. Oviedo-Trespalacios O, Haque MM, King M et al (2017). Effects of road infrastruc-ture and traffic complexity in speed adap-tation behaviour of distracted drivers. Ac-cid Anal Prev, 101: 67-77.
19. Siam MFM, Isa MHM, Borhan N et al (2015). Measurement of Driver Distrac-tion in Malaysia’s Traffic Environment: A Driving Simulator Study. Journal of Mechani-cal Engineering and Sciences, 8: 1472-1480.
20. Tarabay R, Abou-Zeid M (2018). Assessing the effects of auditory-vocal distraction on driving performance and physiologi-cal measures using a driving simulator. Transp Res F Traffic Psychol Behav, 58: 351-364.
21. Perrier J, Jongen J, Vuurman E et al (2016). Driving performance and EEG fluctua-tions during on-the-road driving follow-ing sleep deprivation. Biol Psychol, 121(Pt A):1-11.
22. Ahn S, Nguyen T, Jang H et al (2016). Ex-ploring Neuro-Physiological Correlates of Drivers’ Mental Fatigue Caused by Sleep Deprivation Using Simultaneous EEG, ECG, and fNIRS Data. Front Human Neursci, 10:219.
23. Wen H, Sze NN, Zeng Q (2019). Effect of Music Listening on Physiological Condi-tion, Mental Workload, and Driving Per-formance with Consideration of Driver Temperament. Int J Environ Res Public Health, 16(15):2766.
24. Guo M, Li S, Wang L et al (2016). Research on the Relationship between Reaction Ability and Mental State for Online As-sessment of Driving Fatigue. Int J Environ Res Public Health, 13(12):1174.
25. Mohid IAM, Khamis NK, Noh NA et al (2019). Driver’s Response towards Dif-ferent Road Complexity: A Preliminary Study. The Japanese Journal of Ergonomics, 55 (Supplement): 1H3-6-1H3-6.
26. Sugiono S, Denny W, Andriani DP (2018). The Impact of Road Complexity on the Psychophysiological Load Experienced by Car DriversUsing Electroencephalog-raphy (EEG) Measurement of Brain-waves. Acta Neuropsychologica, 16(4) 361-374.
27. Kim SL, Yang JH (2018). Evaluation of the Effects of Driver Distraction Part 1: Based on Simulator Experiments. IEEE International Conference on Systems, Man, and Cybernetics, 2018: 1081-1086
28. Kim SL, Yang JH (2018). Evaluation of the Effects of Driver Distraction Part 2: Based on Real Vehicle Experiments. IEEE International Conference on Systems, Man, and Cybernetics, 2018: 1087-1092.
29. He D, Donmez B, Liu CC et al (2019). High Cognitive Load Assessment in Drivers through Wireless Electroencephalography and the Validation of a Modified N-Back Taska. IEEE Transactions on Human-Machine Systems, 49(4): 362-371.
30. Diaz-Piedra C, Gomez-Milan E, Stasi LLD (2019). Nasal skin temperature reveals changes in arousal levels due to time on task: An experimental thermal infrared imaging study. Appl Ergon, 81 :102870.
31. Getzmann S, Arnau S, Karthaus M et al (2018). Age-Related Differences in Pro-active Driving Behavior Revealed by EEG Measures. Front Human Neurosci, 12:321.
32. Foy HJ, Chapman P (2018). Mental work-load is reflected in driver behaviour, physiology, eye movements and prefron-tal cortex activation. Appl Ergon, 73: 90-99.
33. Sugiono S, Widhayanuriyawan D, Andriani DP (2017). Investigating the Impact of Road Condition Complexity on Driving Workload Based on Subjective Measure-ment using NASA TLX. MATEC Web of Conferences, 136 (2017): 02007.
34. Sugiono S, Widhayanuriyawan S, Andriyani DP (2018). Mental Stress Evaluation of Car Driver in Different Road Complexity Using Heart Rate Variability (HRV) Anal-ysis. Proceedings of the 2018 5th Interna-tional Conference on Bioinformatics Research and Applications, 2018: 90-94.
35. Strayer DL, Turrill J, Cooper JM et al (2015). Assessing Cognitive Distraction in the Automobile. Hum Factors, 57 (8): 1300-1324.
36. Alrefaie MT, Summerskill S, Jackon TW (2019). In a heartbeat: Using driver’s physiological changes to determine the quality T of a takeover in highly automat-ed vehicles. Accid Anal Prev, 131:180-190.
37. Prabhakar G, Madhu, Biswas P (2018). Comparing Pupil Dilation, Head Move-ment, and EEG for Distraction Detec-tion of Drivers. Proceedings of the 32nd Inter-national BCS Human Computer Interaction Conference (HCI), 69: 1-5.
38. Papantoniou P, Tannis G, Antoniou C et al (2016). Investigating the effect of area type and traffic conditions on distracted driving performance. Transp Res Proc, 14: 3839-3848.
39. Niu J, Wang X, Liu et al (2019). Effects of mobile phone use on driving perfor-mance in a multiresource workload sce-nario. Traffic Inj Prev, 20(1): 37-44.
40. Nowosielski RJ, Trick LM, Toxopeus R (2018). Good distractions: Testing the ef-fects of listening to an audiobook on driving performance in simple and com-plex road environments. Accid Anal Prev, 111: 202-209.
41. Paxion J, Galy E, Berthelon C (2015). Over-load depending on driving experience and situation complexity: Which strategies faced with a pedestrian crossing? Appl Ergon, 51: 343-349.
42. Rahman NIA, Dawal SZM, Yusoff N (2020). Driving mental workload and per-formance of ageing drivers. Transp Res F Traffic Psychol Behav, 69: 265-285.
43. Jeong H, Liu Y (2019). Effects of non-driving-related-task modality and road geometry on eye movements, lane-keeping performance, and workload while driving. Transp Res F Traffic Psychol Behav, 60:157-171.
44. Merat N Jamson AH (2013). The effect of three low-cost engineering treatments on driver fatigue: A driving simulator study. Accid Anal Prev, 50: 8-15.
45. Lansdown TC, Stephens AN, Walker GH (2015). Multiple driver distractions: A sys-temic transport problem. Accid Anal Prev, 74: 360-364.
46. Horberry T, Anderson J, Regan MA (2006). Driver distraction: The effects of concur-rent in-vehicle tasks, road environment complexity and age on driving perfor-mance. Accid Anal Prev, 38: 185- 191.
47. Zhao C, Zhao M, Liu J (2012). Electroen-cephalogram and electrocardiograph as-sessment of mental fatigue in a driving simulator. Accid Anal Prev, 45: 83-90.
48. Mohid IAM, Khamis NK (2018). Implica-tion of driving disturbance and road condition towards driver’s performance in simulated condition. Jurnal Kejuruteraan, 1(6): 33-39.
49. Lansdown TC, Stephens AN, Walker GH (2015). Multiple driver distractions: A sys-temic transport problem. Accid Anal Prev, 74: 360-367.
50. Schmidt E, Bullinger AC (2019). Mitigating passive fatigue during monotonous drives with thermal stimuli: Insights into the effect of different stimulation dura-tions. Accid Anal Prev, 126: 115-121.
51. Khamis NK, Deros BM, Schramm D et al (2016) Subjective and indirect methods to observe driver’s drowsiness and alert-ness: An overview. Journal of Engineering Science and Technology, 11(Sp. Iss. on ICE & ICIE 2015):28-39.
52. Gharagozlou F, Saraji GN, Mazloumi A et al (2015). Detecting driver mental fatigue based on EEG alpha power changes during simulated driving. Iran J Public Health, 44(12): 1693-1700.
53. Khamis NK, Ismail FR, Hesse B et al (2016). Suitability of heart rate as physio-logical measures tool to determine driv-ers’ performance impairment: A prelimi-nary study. Jurnal Teknologi, 78: 25-30.
54. Antonson A, Ahlström C, Mårdh S (2014). Landscape heritage objects’ effect on driving: A combined driving simulator and questionnaire study. Accid Anal Prev, 62: 168-177.
55. Gastaldi M, Rossi R, Gecchele G (2014). Ef-fects of driver task-related fatigue on driving performance. Procedia Social and Behavioral Sciences, 111: 955-964.
56. Naurois CJ, Bourdin C, Bougard C (2018). Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness. Accid Anal Prev, 121: 118-128.
57. Davenne D, Lericollais R, Sagaspe P (2012). Reliability of simulator driving tool for evaluation of sleepiness, fatigue and driv-ing performance. Accid Anal Prev, 45: 677- 682.
58. Hallvig D, Anund A, Fors Ca et al (2013). Sleepy driving on the real road and in the simulator—A comparison. Accid Anal Prev, 50: 44-50.
59. Otmani S, Pebayle T, Roge J et al (2005). Ef-fect of driving duration and partial sleep deprivation on subsequent alertness and performance of car drivers. Physiol Behav, 84: 715-724.
60. Ismail FR, Nuawi MZ, Schramm D et al (2016). Suitability of driving simulators as a tool to study driving fatigue due to vibration and environment: A review. Ma-laysian Journal of Public Health Medicine, Spe-cial Volume (1): 95-101.
| Files | ||
| Issue | Vol 51 No 3 (2022) | |
| Section | Review Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v51i3.8924 | |
| Keywords | ||
| Mental workload Fatigue Driving distraction Electroencephalogram (EEG) Heart rate | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Kabilmiharbi N, Khamis N, Noh N. Commonly Used Assessment Method to Evaluate Mental Workload for Multiple Driving Distractions: A Systematic Review. Iran J Public Health. 2022;51(3):482-494.
