ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 1 No. 1 (2016): TTTP - APEIRON

Valentina Mandić, Danislav Drašković

Management of High Risk Road Sections of Sarajevo - Romanija Region (Case Study)

Original scientific paper

DOI: 10.7251/JTTTP1601053M

Abstract

Road traffic, as a part of the entire transport system, is an important factor of social growth and development, which is necessary to create conditions for its safe operation, bearing in mind that all the benefits of this phenomenon are still paying a high price of unnecessary human suffering. In a contemporary society, there is a large number of institutions that play a role in the functioning of the transport system, but they stand out as the holders of activities and measures to improve traffic safety. Given that the number of accidents in recent years has reached a worrying level, in the interest of so- ciety is to reduce the number of accidents, or to increase traffic safety, because the consequences that the society is submitting in the form of human casualties and material damage are large. The model for the absolute traffic safety does not exist, but a permanent analytical monitoring of the status of road safety, control and regulation of traffic and taking measures to eliminate the risk factors can greatly increase the level of traffic safety.

Keywords: traffic safety, road accident, high-risk road sections.

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.