Showing 8 results for Driving
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Volume 2, Issue 3 (12-2012)
Abstract
Introduction: Train driving is a high responsibility job in railway industry. Train drivers need different cognitive functions such as vigilance, object detection, memory, planning, decision-making. High level of fatigue is one of the caused factor of accidents among train drivers. Numerous factors can impact train drivers’ fatigue but high level of workload is a key factor. Therefore, the aim of the present study was to investigate workload and its relationship with fatigue among train drivers in Keshesh section of Iranian Railway Company.
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Material and Method: This descriptive analytical study was done among 100 train drivers in Keshesh section of Iranian Railway industry. They were selected by simple random sampling. The NASA-TLX workload scale and Samn-Perelli fatigue scale were respectively used to investigate workload and fatigue. Data were analyzed by Paired t-test and Spearman correlation coefficient.
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Result: According to the NASA-TLX results, effort and mental workload with the mean score of 74/22 and 73/31 were respectively the most important attributes of workload among train drivers. No significant relationship was observed between workload and level of fatigue before departure and half an hour before reaching the destination station (P>0.05). However, the relationship between of workload and level of fatigue half an hour before the end of shift (on the way back to the origin station) was statistically significant (P=0.048) among the sample population.
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Conclusion: Effort and mental workload were the most important attributes of workload among train drivers. By focusing on these two variables and adopting fatigue management programs, fatigue and workload can be controlled and the efficiency of the whole system can be enhanced accordingly.
P. Azad, G. H. Halvani, M. R. Najimi, B. Kouhnavard,
Volume 5, Issue 3 (9-2015)
Abstract
Introduction: Road accidents are of the most important events, which cause death and injury of a large number of people and impose huge economic losses. According to previous studies, human factors are the main cause of traffic accidents. The purpose of this study was to investigate the role of behavioral factors in driving-related non-fatal accidents.
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Material and Method: The present analytical study was carried out among 150 drivers of urban and suburban transportation system in Yazd province. The research tool was Driver Behavior Questionnaire (DBQ) which is consisted of two sections: demographic information and driving behavior.
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Result: 83/9 % of the participants reported to use safety belt nearly always. The highest deliberate violations, slips, and mistakes were belonged to drivers with age group of 18-25. Moreover, deliberate violations had a significant relationship with rage (P < 0.05). Survey of behavioral factors in terms of vehicle ownership type showed that “deliberate violations” and “slips and mistakes” high among personal bus drivers and state-owned bus drivers, respectively, which shows the significant association between these behavioral factors and ownership type. What is more, rates of deliberate and unintentional violations and slips were higher among those with a history of two times incidents (P < 0.004).
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Conclusion: The results revealed that behavioral factors such as age, type of vehicle ownership, and accident history played a significant role in occurrence of traffic accidents.
Narmin Hassanzadeh-Rangi, Yahya Khosravi, Ali Asghar Farshad, Hamed Jalilian,
Volume 7, Issue 1 (4-2017)
Abstract
Introduction: Metro driving is one of the newest jobs in Iran. There are few studies in this field. Therefore, the physical workload and their influencing factors have not been identified in metro driving. The objective of this study was task and physical workload analysis of metro driving to recommend control measures.
Material and Method: In this mixed method study, task analysis and Quick Exposure Check (QEC) were used to assessment of physical workload in metro driving. Different methods and techniques including field investigation, document reviews, individual and focus group interviews, and focus group discussions were used to analysis physical workload to recommend control measures.
Result: Whole body exposure with physical workload was assessed unacceptable in metro driving. Although the exposures in back, shoulder/arm and hand/wrist were under threshold 70%, neck exposure lead to over physical workload in the whole body. Many themes include unsupported body; non-sufficient view on the track and on displays; awkward posture and unsuitable layout were extracted as significant factors influencing on physical workload.
Conclusion: An intervention plan was recommended to a) support body by chair, platform and footplate; b) optimize a sufficient view on the track and on displays; c) maintain body postures in seating position with easy reaching distance and sufficient view; and d) design a suitable layout for driving panel regarding to controls, keys and displays.
Soheil Saadat, Iraj Alimohammadi, Mojgan Karbakhsh, Hassan Ashayeri, Farideh Sadeghian, Shahrbanoo Goli, Mahsa Fayaz,
Volume 8, Issue 2 (6-2018)
Abstract
Introduction: Impairment of alertness, attention and performance associated with sleepiness and fatigue in nurses occur in night and long-term shifts that in the end of night shift reach to the maximum level can lead to traffic accidents when they returning home. The purpose of this study was to determine the effect of night shift on psychomotor abilities of driving in nurses after shiftwork.
Material and Method: A cohort study was carried out on 23 night shift and 24 day shift female nurses aged 20 to 40 at Sina Hospital in Tehran city, using the Vienna Test System (VTS). The concentration and selective attention, reaction time, pheriperal perception, and coordination before and after night and day shifts were measured. A multiple linear regression model and Backward stepwise selection method was used for analyses.
Result: In the concentration and selective attention test, sum hits (p = 0.038) and in the visual perception test , divided attention (p =0.006) and visual field (p =0.019), and in the reaction time test the mean motor time (p =0.034) showed a significant adverse relationship with working in night shift, but the visomotor coordination variables did not show any significant correlation.
Conclusion: The results showed that the concentration and selective attention, peripheral perception, and reaction time of psychomotor ability of driving were significantly adversely impaired in nurses after night shift. These results in evidence of the mechanism of increasing traffic accidents after night shift among nurses added to the previous studies in this subject.
Mohammad-Javad Jafari, Narmin Hassanzadeh-Rangi, Yahya Khosravi, Soheila Khodakarim,
Volume 8, Issue 4 (12-2018)
Abstract
Introduction: Driving a train is one of the high demand job due to high vigilance task requiring the ability to long periods monitor surrounding environment and recognizing signals. The aim of this study was to assess train drivers’ mental workload using heart rate (HR) and heart rate variability (HRV) indices.
Material and Method: An experimental design was conducted among 12 well-trained subjects to induce two different levels of mental demands in a metro simulator and to monitor mental workload levels while driving the train. The HR and HRV parameters were recorded and analysis using ECG signals.
Result: The HRV parameters including SDNNIX (p-value=0.01), RMSSD (p-value=0.00), %PNN50 (p-value=0.01), SDNN (p-value=0.07) and LF/HF Ratio (p-value=0.04) were significantly reduced in a normal operation task comparing to the abnormal one.
Conclusion: The HR and HRV (SDNN, SDNNIX, RMSSD, %PNN50 and LF/HF Ratio) were found to be sensitive to mental workload in metro train driving .It is recommended to include the HRV parameters for mental workload assessment of train drivers.
Saeid Najafi, Shirazeh Arghami, Maryam Khazaee-Pool,
Volume 10, Issue 4 (11-2020)
Abstract
Introduction: Road traffic accidents (RTAs) have always a major concern and human factor has been recognized as their leading cause. Since taxi drivers play a significant role in accidents, the main purpose of this study was to provide a valid and reliable version of the Dula Dangerous Driving Index (3DI) for taxi drivers working in the city of Zanjan, Iran.
Material and Methods: Based on the convenience sampling method, 316 taxi (including taxi, internet taxi, etc.) drivers were recruited in this descriptive study. The 3DI contained 28 items within three factors related to dangerous driving behavior. After linguistic validation, qualitative and quantitative face validity was determined for the given questionnaire. Consequently, content validity index (CVI) and content validity ratio (CVR) were assessed by a panel of 10 experts. Internal reliability was further calculated based on Cronbach’s alpha coefficient and test-retest method.
Results: The results revealed that face validity (1.60-3.82.), CVR (0.8-1), and CVI (0.891-1) were acceptable. Cronbach’s alpha coefficient was also 0.896 for the total reliability of the instrument and 0.95, 0.89, and 0.94 for each factor, respectively. In addition, Spearman’s rank correlation coefficient was 0.871 (P-value<0.001).
Conclusion: The results ultimately demonstrated that the Persian version of the 3DI had adequate reliability, as well as, face and content validity. However, construct validity remains.
Naser Nik Afshar, Mostafa Kamali, Elham Aklaghi Pirposhteh, Hesamedin Askai Majabadi, Nasir Amanat, Mohsen Poursadeqiyan,
Volume 13, Issue 1 (3-2023)
Abstract
Introduction: In recent years, driver’s drowsiness has been one of the leading causes of road accidents, which can lead to physical injuries, death, and significant economic losses. Statistics show that an efficient system is needed to detect the driver’s drowsiness, that gives the necessary warning before an unfortunate event occurs. Therefore, this review study was conducted to investigate the studies on driver’s drowsiness sensors and to present a combination of diagnostic methods and an efficient model design.
Material and Methods: This narrative review study was conducted through a systematic search using “driver” and “drowsiness detection” as search keywords in indexing databases including Scopus, PubMed, and Web of Sciences. The search encompassed the latest related research conducted in this field from 2010 to September 2020. The reference lists were also reviewed to find further studies.
Results: In general, researchers evaluate driver’s drowsiness using three methods including vehicle-based measurement, behavioural measurement, and physiological measurement. The details and how these measurements are made make a big difference to the existing systems. In this study, which is a narrative review, the three mentioned measurements were examined using sensors and also the advantages and limitations of each were discussed. Real and simulated driving conditions were also compared. In addition, different ways to detect drowsiness in the laboratory were examined. Finally, after an analytical comparison of the methods of diagnosing drowsiness, a diagram was presented based on which an efficient and combined model was developed.
Conclusion: Taking into account the limitations of each of the methods, we need a combination of behavioural, performance, and other measures to have an efficient drowsiness diagnosing model. Such model must be tested using simulations and in real world situations.
Jamal Biganeh, Vanoushe Kalantari, Soqrat Omari Shekaftik, Mohammad Javad Sheikhmozafari, Seyedeh Solmaz Talebi, Mohammad Hossein Ebrahimi,
Volume 14, Issue 2 (6-2024)
Abstract
Introduction: Driving has various harmful factors due to its nature, which affect drivers’ health directly and indirectly. Therefore, it is necessary to know the situation and prevalence of these factors in drivers to implement preventive measures.
Material and Methods: This cross-sectional study is a part of a cohort study conducted (2016 to 2018) among the professional drivers of Shahroud, Iran. Data related to background information, blood pressure, height, weight, waist circumference, body mass index, blood factors, hearing loss (dB), respiratory performance indicators, sleep disorders, and accidents were collected from the participants with standard tools and methods.
Results: This study examined 1461 male professional drivers with an average age of 37.30±6.96 years. A total of 426 participants had metabolic syndrome. 797 and 942 people had different degrees of hearing loss, respectively, in the right and left ear. About 129 people had obstructive sleep apnea, and 1330 people had insomnia. Investigations showed that 351 drivers had at least one accident.
Conclusion: This study showed the prevalence of health risk factors in professional drivers at the examined time point. Considering the vital role of drivers in transportation and the country’s economy, it seems necessary to pay more attention to the health of this occupational group. Regular health screening, healthy lifestyle training, improvement of working conditions, and stress management are some interventions that can effectively improve drivers’ health.
