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

Tomislav Petrović, Miloš Milosavljević, Milan Božović, Danislav Drašković, Milija Radović

The Effects of ITS Application in Speed Management on State Road From Mali Pozarevac to Kragujevac

Original scientific paper

DOI: 10.7251/JTTTP1601046P

Abstract

The application of intelligent transport systems (hereinafter ITSs) on roads enables continu- ous monitoring of road users during a whole year with the aim to collect good-quality data based on which the more complex analyses could be done, such as monitoring of certain traffic safety indicators. Automatic traffic counters are one of the most commonly implemented ITSs for collecting traffic flow parameters that are relevant for traffic management on state roads in Republic of Serbia. This paper presents one of the possible ways to collect, analyze and present data on road users’ speeds using automatic traffic counters, where certain traffic safety indicators are analyzed in terms of road users’ compliance with the speed limit on the road section from Mali Pozarevac to Kragujevac. Based on the analyses of data downloaded from automatic traffic counters, it is observed that an extremely high percentage of vehicles drive at speed higher than the speed limit, indicating clearly to higher traffic ac- cident risk, as well as to the need for a tendency to implement speed management on roads using ITS in the forthcoming period.

Keywords: ITS, speed, automatic traffic counters, traffic safety, indicator.

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.