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Background: Driver fatigue as a leading cause of death in the transportation industry can impair the driving performance in long-distance driving task. Studies on the links of driver subjective fatigue and the bus lateral position are still an exploratory issue that requires further investigation. This study aimed to determine the correlation between the driver subjective fatigue and the bus lateral position in a driving simulator., Methods: This descriptive-analytical research was conducted on 30 professional male bus drivers participated in a two-hour driving session. The driver subjective fatigue was assessed by the Fatigue Visual Analogue Scale (F-VAS) at 10-min intervals. Simultaneously, the performance measures of lane drifting as the mean and standard deviation of the bus lateral position (SDLP) were calculated during the simulated driving task. Descriptive statistics and the Spearman correlation coefficient were used to describe and analyze the data., Results: Fatigue levels had an increasing trend as the time-on-task of driving increased. Time-on-task of driving had the greatest effect on the fatigue self-evaluation (r = 0.605, p < 0.0001). The results showed a significant correlation between fatigue self-evaluation and bus lateral position (r = 0.567, p < 0.0001)., Conclusion: As the time of driving increased, driving performance was affected adversely, as shown by the increase in the SDLP. Even so, the effect of individual differences on driving performance should not be overlooked. This work concludes that predicting the state of a driver fatigue based on the group mean data has some complications for any application.

Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving.

Background: Workers are more susceptible to stress disorder for several reasons. The aim of this study was to investigate occupational stress among workers and other personnel at the ZardjinBaft Workshop in Ilam, Iran, and to examine the relationship between occupational stress and several parameters, such as age, gender, marital status, educational level, work experience, tobacco use, body mass index (BMI), and the type of work., Method: This was a descriptive, cross-sectional study that was performed in June 2010. The sample population that was studied consisted of all of the workers and other personnel (130 people) at ZardjinBaft Workshop in Ilam, Iran. They were studied using Cooper's standard questionnaire for stress in the work environment, and we examined the relationship between stress, as the dependent variable, and the eight independent variables mentioned in the Abstract., Results: In the sample population that was studied, severe stress was not observed in most of the sections of the workshop. In addition, using the analysis of variance test (ANOVA), no significant relationship was observed between the average degree of stress and the average demographic characteristics. However, the average stress level had significant relationships with the level of education, work experience, and the type of work, suggesting that stress increases as the level of education increases. In addition, in the beginning and early years of employment, medium levels of stress were observed, and the prevalence of stress decreased after the first 10 years of employment. In addition, workers in the ventilation section of the factory had the highest stress levels. The fear of losing their jobs was the main factor that caused stress among the workers at ZardjinBaft Workshop in Ilam., Conclusion: We suggest that managers consider the high importance of stress in the work environment. They should be able to recognize when workers are stressed and offer them assistance and training. They also can eliminate the factors that cause stress in the work environment by taking preventive action. In parallel, workers should try to interact well with their managers and talk to her or him about the conditions of their jobs.

Background: Human factors cause 60-70 percent of automobile accidents. Everything related to people that is involved in and interacting with a system is considered to be a human factor. These factors can be psychological, biological, or social, and all of them can affect drivers' behaviors. Therefore, one of the negative and unfavorable effects of these factors is that they cause accidents. According to previous research, increases in the job stresses result in increases in the incidence of car accidents. Drivers who feel stressed often do not to observe the rules, and they may not even notice the warning signs. By measuring the job stress among drivers and its adverse effects, this research aimed to provide an appropriate managerial solution to reduce these problems., Methods: The sample in this descriptive-analytical study consisted of 250 drivers who were selected and investigated. A job stress questionnaire was used as a means for collecting data. Health conditions were assessed by referring to clinical documents provided for the drivers. Accident data were included in the study using accident-related documentation. Two hundred and fifty drivers from Ilam, Iran participated and were analyzed in this study. This research is a cross-sectional study that was performed by dossiers and personal memoirs. Data were analyzed by SPSS16 and the chi-squared test., Results: The study showed that the main factors that cause medium- to high-level stress are the physical environment, workload and ambiguity of duties. It also showed that the incidence and severity of accidents increased as stress levels increased., Conclusion: This study shows high prevalence of job stress amongst drivers in Ilam. The main causes of the prevalence of stress among drivers in Ilam City are physical environment, workload and ambiguity of duties, responsibility.