Volume 9, Issue 4 (Summer 2024)
Health in Emergencies and Disasters Quarterly 2024, 9(4): 255-264 |
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Askari A, Hosseinpour R, Bakhtiari M, Sepehr P, Ghodrati Torbati A, Salehi Sahlabadi A, et al . Investigating the Relationship Between Subjective and Interpretive drowsiness With Lane Departure in Simulator Driving. Health in Emergencies and Disasters Quarterly 2024; 9 (4) :255-264
URL: http://hdq.uswr.ac.ir/article-1-521-en.html
URL: http://hdq.uswr.ac.ir/article-1-521-en.html
Ali Askari1 
, Robab Hosseinpour2 , Mohammad Bakhtiari3 , Parvin Sepehr4 , Abbas Ghodrati Torbati5 , Ali Salehi Sahlabadi6 , Maliheh Eshaghzadeh7 , Anahita Zandi7 , Javad Vatani * 8, Mohsen Poursadeghiyan9
, Robab Hosseinpour2 , Mohammad Bakhtiari3 , Parvin Sepehr4 , Abbas Ghodrati Torbati5 , Ali Salehi Sahlabadi6 , Maliheh Eshaghzadeh7 , Anahita Zandi7 , Javad Vatani * 8, Mohsen Poursadeghiyan9
1- Department of Occupational Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
2- Students Research Committee, Faculty of Health, Ardabil University of Medical Sciences, Ardabil, Iran.
3- Department of Anesthesiology, Sirjan school of Medical Sciences, Sirjan, Iran.
4- Students Research Committee, Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
5- Department of Nursing, school of Nursing and Midwifery, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran.
6- Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
7- Department of Nursing, School of Nursing and Midwifery, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran.
8- Department of Occupational Health Engineering, Guilan Road Trauma Research Center, School of Health, Guilan University of Medical Sciences, Rasht, Iran. ,jvatani@gmail.com
9- Social Determinants of Health Research Center, Faculty of Health, Ardabil University of Medical Sciences, Ardabil, Iran.
2- Students Research Committee, Faculty of Health, Ardabil University of Medical Sciences, Ardabil, Iran.
3- Department of Anesthesiology, Sirjan school of Medical Sciences, Sirjan, Iran.
4- Students Research Committee, Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
5- Department of Nursing, school of Nursing and Midwifery, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran.
6- Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
7- Department of Nursing, School of Nursing and Midwifery, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran.
8- Department of Occupational Health Engineering, Guilan Road Trauma Research Center, School of Health, Guilan University of Medical Sciences, Rasht, Iran. ,
9- Social Determinants of Health Research Center, Faculty of Health, Ardabil University of Medical Sciences, Ardabil, Iran.
Abstract: (1548 Views)
Background: Driver drowsiness is a significant factor contributing to road accidents and the overall increase in road mortality rates. This study investigates the relationship between lane crossing (LC), the number of lateral position deviations and driver drowsiness. The proposed method, due to precision and convenience, has great potential for developing driver-assistant systems.
Materials and Methods: In this experimental research, 34 sub-urban bus drivers participated in a 2-h driving session in a simulator designed based on visual reality. Sensors attached to the steering recorded right and left deviations and relevant information was matched with the receded videos and the amount of the standard deviation of lane position (SDLP). The number of LC was determined with the designed indicator on the road software. Then, the association between SDLP and the number of LC was compared with the results of the Karolinska sleepiness scale (KSS) and observer rating of drowsiness (ORD), which determined the level of drowsiness, by facial features.
Results: The results of multivariate analysis of variance indicated that the time variable has a significant effect on both ORD and SDLP (P<0.05). These two variables provided over 99% of the variance. The same results were obtained for KSS and SDLP (P<0.05). Meanwhile, the linear combination of these two dependent variables over 12 periods of the research has significant variations. In addition, the results show the progression of KSS and ORD (P<0.05) and an increase in SDLP and LC (P<0.05). In the same manner, LC has a tight association with the level of drowsiness and other factors (P<0.05).
Conclusion: Drowsiness increases the variation in line tracking. However, it is not an appropriate signal for drowsiness detection. The SDLP and the number of line crossings is an appropriate criterion to check drivers’ performance.
Materials and Methods: In this experimental research, 34 sub-urban bus drivers participated in a 2-h driving session in a simulator designed based on visual reality. Sensors attached to the steering recorded right and left deviations and relevant information was matched with the receded videos and the amount of the standard deviation of lane position (SDLP). The number of LC was determined with the designed indicator on the road software. Then, the association between SDLP and the number of LC was compared with the results of the Karolinska sleepiness scale (KSS) and observer rating of drowsiness (ORD), which determined the level of drowsiness, by facial features.
Results: The results of multivariate analysis of variance indicated that the time variable has a significant effect on both ORD and SDLP (P<0.05). These two variables provided over 99% of the variance. The same results were obtained for KSS and SDLP (P<0.05). Meanwhile, the linear combination of these two dependent variables over 12 periods of the research has significant variations. In addition, the results show the progression of KSS and ORD (P<0.05) and an increase in SDLP and LC (P<0.05). In the same manner, LC has a tight association with the level of drowsiness and other factors (P<0.05).
Conclusion: Drowsiness increases the variation in line tracking. However, it is not an appropriate signal for drowsiness detection. The SDLP and the number of line crossings is an appropriate criterion to check drivers’ performance.
Keywords: Lane crossing (LC), Karolinska sleepiness scale (KSS), observer rating of drowsiness (ORD), Standard deviation of lane position (SDLP), Drowsiness, Driving crashes, Transportation safety
Type of Study: Review |
Subject:
Emergency
Received: 2023/04/29 | Accepted: 2024/01/28 | Published: 2024/07/1
Received: 2023/04/29 | Accepted: 2024/01/28 | Published: 2024/07/1
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This is an open access article distributed under the terms of the Creative Commons Attribution License (CC-By-NC), which permits use, distribution, and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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