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

Mirsad Kulović, Slavko Davidović

The Effect of Countdown Pedestrian Signals on Pedestrian Behavior in Various Weather Conditions - Case Study in Banja Luka

Original scientific paper

DOI: 10.7251/JTTTP1801022K

Abstract

Pedestrians represent the most vulnerable category of participants in traffi More and more com- plex traffi conditions in citi across Europe, and therefore BiH, threaten traffi to become a challenge for pedestrians, and pedestrians often experience traffi as a challenge. Studies of behavior of pedestrians at signalized pedestrian crossings conclude that there is a high level of insecurity and a high percentage of unsafe crossings by pedestrians. Timers that add pedestrian signals indicate the length of the red light, the remaining time to the beginning of the green light for the safe crossing of pedestrians across the street. This paper analyzes the effect of the countdown pedestrian signals- CPSs in different weather conditions, ie the comparison of pedestrian behavior (switching to red light) without CPSs and with CPSs in different weather conditions (sun, snow, rain, no precipitation with a temperature of 0 degrees) was performed. The paper analyzes a traffi  light pedestrian crossing over the road that consists of four traffi  lanes in Banja Luka, BiH.

Keywords : pedestrians, countdown pedestrian signals- CPSs, pedestrian behavior, crossing the street to red light.

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.