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

Milenko Džever, Danislav Drašković, Milija Radović, Zoran Injac

Analysis of road safety before and after road safety assessment carried out on the road section no. 16 Banja luka – Celinac, intersection “Groblje-Vrbanja“

Original scientific paper

DOI: 10.7251/JTTTP1701046DZ

Abstract

The Republic of Srpska implemented three procedures provided by the Directive 2008/96/EC, namely: road safety audit for infrastructure projects (Road Safety Audit, RSA), road safety impact assess- ment (Road Safety Assessment RSI), as well as the procedures of identifying, ranking and remedying and black spots management (BSM).

This paper presents a concrete road safety inspection of intersection on the primary road (major road) M4 in the place Vrbanja near Banja Luka. The said intersection is where the major road and access road to newly constructed cemetery in Banjaluka intersect. After the inspection, the Public Company “Republic of Srpska Motorways“ as road administration implemented some recommendations from the final Report on road safety inspection in order to improve these procedures.

Also, an analysis was carried out to identify the conditions before and after the audit and partial imple- mentation of recommendations.

Keywords : 2008/96/EC, Republic of Srpska, RSA, RSI, BSM.

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.