ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 9 No. 1 (2024): TTTP - APEIRON

Siniša Macan, Slaviša Paunović

Use of video surveillance systems for detecting seat belt usage, mobile device usage, or vehicle registration

Original scientific paper

DOI: 10.7251/JTTTP2401016G

Abstract

The concept of smart traffic or smart cities involves the use of a large amount of data col- lected in real-time and processed using available tools. Data is collected from various sources. One common source for traffic control is video or imagery. In many countries, camera systems are installed to monitor traffic, track speed, or oversee intersections. Data is collected and processed in operational centers, allowing for insights into vehicle registration, vehicle speed, and passengers. At the same time, significant risks in traffic arise from the use of mobile phones or smart devices while driving. Further- more, research indicates that wearing seat belts significantly reduces the risks of traffic accidents. A common occurrence in traffic is that vehicles are unregistered and uninsured. At the same time, the use of video surveillance systems is associated with the protection of privacy and personal data, necessitat- ing the need to find an optimal balance between the right to privacy and the right to a secure environ- ment, including safe participation in public traffic. The aim of this study is to explore the possibility and analyze the use of video surveillance to analyze the use of video surveillance in detecting mobile phone usage and seat belt compliance while driving. The systems for detecting mobile phone usage or seat belt usage during driving can instantly provide information on a prominently displayed screen near the roadside for preventive action. The paper analyzes the use of such systems for prevention purposes, along with an analysis of the potential application of penalties to reduce identified risks in traffic.

Keywords: Artificial Intelligence, Deep Learning, Machine learning, Smart Systems, Violations, Preven- tive Action

Vol. 9 No. 1 (2024): TTTP - APEIRON

Vladimir Gatarić, Tanja Marjanac, Vuk Bogdanović

The influence of the corona virus pandemic on the characteristics of vehicle flow on the e-661 highway

Original scientific paper

DOI: 10.7251/JTTTP2401016G

Abstract

In this work, the characteristics of the traffic flow on the section of the Gradiška- Banja Luka highway, which is part of the European road route E-661, were analyzed in the period from 2019 to 2022. Data on the size of flow requests were taken from the database of the toll station “Jakupovci” on the Gradiška- Banja Luka highway. When defining the size of the flow request, the structure of the traffic flow was also taken into account, in accordance with the categories according to which the toll is collected. The period in which the analysis of flow characteristics was performed also includes the period in which the coronavirus pandemic reigned, when certain travel rules and prohibitions were in force. In accordance with that, the work will specifically analyze the impact of the COVID 19 pandemic on the characteristics of the traffic flow on the Gradiška- Banja Luka highway section. Given that the

„Jakupovci“ toll station is the busiest toll station on the Gradiška- Banja Luka highway, the results of the analysis can be applied to other sections of highways in the Republic of Srpska.

Keywords: Traffic flow characteristics, vehicle flow, COVID 19 pandemic, Gradiška- Banja Luka highway

Vol. 9 No. 1 (2024): TTTP - APEIRON

Siniša Macan, Slaviša Paunović

Use of video surveillance systems for detecting seat belt usage, mobile device usage, or vehicle registration - penalty or prevention

Original scientific paper

DOI: 10.7251/JTTTP2401022M

Abstract

The concept of smart traffic or smart cities involves the use of a large amount of data col- lected in real-time and processed using available tools. Data is collected from various sources. One common source for traffic control is video or imagery. In many countries, camera systems are installed to monitor traffic, track speed, or oversee intersections. Data is collected and processed in operational centers, allowing for insights into vehicle registration, vehicle speed, and passengers. At the same time, significant risks in traffic arise from the use of mobile phones or smart devices while driving. Further- more, research indicates that wearing seat belts significantly reduces the risks of traffic accidents. A common occurrence in traffic is that vehicles are unregistered and uninsured. At the same time, the use of video surveillance systems is associated with the protection of privacy and personal data, necessitat- ing the need to find an optimal balance between the right to privacy and the right to a secure environ- ment, including safe participation in public traffic. The aim of this study is to explore the possibility and analyze the use of video surveillance to analyze the use of video surveillance in detecting mobile phone usage and seat belt compliance while driving. The systems for detecting mobile phone usage or seat belt usage during driving can instantly provide information on a prominently displayed screen near the roadside for preventive action. The paper analyzes the use of such systems for prevention purposes, along with an analysis of the potential application of penalties to reduce identified risks in traffic.

Keywords : Artificial Intelligence, Deep Learning, Machine learning, Smart Systems, Violations, Preven- tive Action