ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 2 No. 1-2 (2017): TTTP - APEIRON

Darko Petrović, Dragoslav Kukić, Nenad Džagić, Milan Lončar

Analisys of the influence of alcohol on the motor skills and attention of a driver

Original scientific paper

DOI: 10.7251/JTTTP1701028P

Abstract

Alcohol is recognized as one of the factors in the occurrence of traffic accidents, which sig- nificantly affects the occurrence of accidents and the severity of their consequences. In this paper, the results of the pilot survey present the measures of influence of intoxicated drivers on the status of their motor skills and attention in traffic. The effect of alcohol is simulated using the “drunk glasses” that simulate the effects of the alcohol on the human body: reduced alertness, slowed reactions, confusion, distortion of the visual field, change of distance and depth perception, narrowing of peripheral vision, poor judgment and decision making, image duplication, lack of muscle coordination and the like. Mo- tor skills were tested using the “Vienna test” system which measures the reaction speed, motor skills, attention, concentration and the assessment of traffic situations. For the purposes of this study the results of the “Vienna test” were analyzed -a driver without “drunk glasses” and wearing the glasses. Glasses for alcoholic level of 0,6 – 0,8 ‰ were used in the study. Through a comparative analysis ob- tained by this research we point to the impact that alcohol has on the perceptual skills of drivers.

Keywords : alcohol, perceptual skills, attention, drivers, impact.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

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.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

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.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.