For decades, around the world is developing a fatigue detection system to alert drivers when they reach the state of fatigue that threatens them in traffic. Most of the research on the impact of fatigue on drivers based on driving simulators mainly because it is a controlled environment, cheap and safe approach. Since the nineties of the last century, many surveys were conducted in which the survey method was applied, while examining the subjective attitudes of drivers about the impact of fatigue on traffic safety. The beginning of the 21st century is characterized by the development of a fatigue detec- tion system based on modern technologies, and a number of experiments were conducted. However, it not yet in use tools that can be easily detected drivers fatigue, in order to respond quickly and prevent them from operating the vehicle in such condition.
The aim of this paper is to demonstrate the importance and implementation of a new fatigue identifica- tion model for commercial vehicle drivers in selected transport companies. Based on the results of this research, it is possible to determine which company is the safest from the aspect of fatigue, which is least safe. Also, the analysis of the results can determine which influencing factor is “the weakest link” among the drivers in the transport company, or where to direct measures in order to improve the road safety of the company, and therefore the local community.
The study included five transport companies in Serbia, three of which are engaged in the carriage of passengers, and two transport goods. The survey used the survey method, the face face model, and 265 drivers of commercial vehicles participated, 16.6% of whom were found fatigued before the start of the shift.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
