ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 3 No. 1-2 (2018): TTTP - APEIRON

Danislav Drašković, Dragoslav Mihajlović, Ljubo Glamočić, Samir Hrnjić

Passive Road Safety Systems – Case Study of Road Section Prnjavor- Doboj (M16.1, R474, R474a)

Original scientific paper

DOI: 10.7251/JTTTP1801060D

Abstract

The European Parliament and the European Council have adopted the Directive 2008/96/EC relating to the safety of traffic infrastructure. This Directive binds the EU Member States to implement the guidelines on roads comprising the parts of the Trans-European traffic network, regardless of the stage those roads are in. EU Member States have a possibility to adopt the guidelines and regulations from the Directive and build them into the national regulations on parts of the roads that are not a part of the Trans-European roads. Based on the facts stated above, there is a research problem in a form of a question “Can the Directive 2008/96/EC be applied in the traffic in Bosnia and Herzegovina?” i.e. are its guidelines implemented as a manner of approximation with the EU regulations, and what are the effects of its implementation. This is a traffic problem in its nature, closely related to road traffic safety, and we find the answer to the research problem in theoretical and empirical research in this area.

Keywords : inspection, road, traffic safety.

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.