scholarly journals Сontrol of Intelligent Transport System in Minsk

2018 ◽  
Vol 17 (5) ◽  
pp. 401-412
Author(s):  
D. V. Kapskiy ◽  
D. V. Navoy ◽  
P. A. Pegin
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Management System ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Design System ◽  
Intelligent Transport System ◽  
Traffic Management System

The paper considers algorithms for searching a maximum traffic volume of road vehicles in a traffic light cycle with a distributed intensity pulse and optimization of shifts under coordinated traffic flow control. Modeling of traffic flows have been made while using a computer program developed by the authors and it has made it possible to improve efficiency of traffic management by taking into account the distributed pulse of transport intensity. The paper proposes a model for minimizing total losses in road traffic during the integration of an incident control sub-system and route guidance for and an automatic road traffic management system as part of Minsk intelligent transportation system which has been studied as a tool for modeling a computer-aided design system "Backbone management". The model that minimizes vehicle delays, uses an algorithm implementing traffic flow intensity parameters depending on the time of day, days of the week. As a result of the simulation it has been revealed that the most effective parameter is an indicator of vehicle delays which does not always satisfy drivers trying to choose routes of their traffic which are based on a minimum transportation speed. However, from the point of view of managing an intelligent transportation system, it is necessary to choose parameters based on the requirements for minimizing delays on the road traffic network of the largest city in our country. All the proposed algorithms and models are used in the automatic traffic management system of Minsk city and will be used while creating an integrated intellectual transportation system of the city.

scholarly journals Structure of transformation of the road motion parameters in the control system

2019 ◽  
Vol 67 ◽  
pp. 05001
Author(s):  
Liudmyla Abramova ◽  
Yevhen Nahornyi ◽  
Henadii Ptytsia
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Point Of View ◽  
System Structure ◽  
Intelligent Transport System ◽  
Traffic Efficiency ◽  
Traffic Management System ◽  
Transport Problems

Over the past decades, the world has witnessed an increase in the number of vehicles. According to the accident analysis and to the existing transport problems, the development of automated traffic control systems using adaptive management methods is the most optimal way to improve road traffic quality. From the technological point of view, the system must function according to the requirements for the traffic flow level and to the assessment of traffic efficiency, so a clear comparison of systems is impossible under the conditions of various principles for identifying managerial impacts and the designation of management system. The authors’ analysis of the most commonly used traffic management technologies proves that experts choose the system architecture that affects its functions and the ability to implement one or another method of management. In accordance with the ITS approach and management tasks at each hierarchy level, we believe that the traffic management system of the intelligent transport system should be based on the principle of multi-level architecture using ring Ethernet technologies, which corresponds more to the diamond-shaped system structure; it allows to distribute methods of traffic management for purposes and to separate the informational and technological elements of the system.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

scholarly journals 3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing

2021 ◽  
Vol 2083 (3) ◽  
pp. 032022
Author(s):  
Yunpeng Guo ◽  
Kai Zou ◽  
Shengdong Chen ◽  
Feng Yuan ◽  
Fang Yu
Keyword(s):  
Virtual World ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Physical World ◽  
Transportation System ◽  
Traffic Information ◽  
Digital Twin ◽  
Twin System ◽  
Infrastructure System

Abstract Cooperative vehicle-infrastructure is one of the most import developing direction of future intelligent transportation system, while digital twin system can record, reproduce, and even deduce the physical system, which could be helpful for the development of cooperative vehicle-infrastructure. In this study, we proposed a 3D digital twin platform of intelligent transportation system based on road-side sensing, a core component of cooperative vehicle-infrastructure system. This platform consists of real road-side sensing unit,3D virtual environment, and the ROS bridge between them, by receiving the sensing results of physical world in real-time, the virtual world can reproduce the compatible road traffic information, such as the type,3D position and orientation of traffic participants.

scholarly journals IOT Based Traffic Management System

2021 ◽  
pp. 184-187
Author(s):  
Shashank S ◽  
Kiran P ◽  
Nischay D ◽  
Vinay Kumar M ◽  
B R Vatsala ◽  
...  
Keyword(s):  
Traffic Management ◽  
Management System ◽  
Transportation System ◽  
Raspberry Pi ◽  
Urban Residents ◽  
System Of Cities ◽  
Traffic Management System ◽  
Global Population

In 2014, 54% of the total global population was urban residents. The prediction was a growth of nearly 2% each year until 2020 leading to more pressure on the transportation system of cities. Cities should be making their streets run smarter instead of just making them bigger or building more roads. This leads to the proposed system which will use a Raspberry pi and Camera for tracking the number of vehicles leading to time-based monitoring of the system.

Intelligent Transportation System Data Archiving: Statistical Techniques for Determining Optimal Aggregation Widths for Inductive Loop Detector Speed Data

2000 ◽  
Vol 1719 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Byron J. Gajewski ◽  
Shawn M. Turner ◽  
William L. Eisele ◽  
Clifford H. Spiegelman
Keyword(s):  
Traffic Management ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation System ◽  
Monitoring Data ◽  
Statistical Techniques ◽  
Parameter Distribution ◽  
Data Archiving ◽  
Wide Range

Although most traffic management centers collect intelligent transportation system (ITS) traffic monitoring data from local controllers in 20-s to 30-s intervals, the time intervals for archiving data vary considerably from 1 to 5, 15, or even 60 min. Presented are two statistical techniques that can be used to determine optimal aggregation levels for archiving ITS traffic monitoring data: the cross-validated mean square error and the F-statistic algorithm. Both techniques seek to determine the minimal sufficient statistics necessary to capture the full information contained within a traffic parameter distribution. The statistical techniques were applied to 20-s speed data archived by the TransGuide center in San Antonio, Texas. The optimal aggregation levels obtained by using the two algorithms produced reasonable and intuitive results—both techniques calculated optimal aggregation levels of 60 min or more during periods of low traffic variability. Similarly, both techniques calculated optimal aggregation levels of 1 min or less during periods of high traffic variability (e.g., congestion). A distinction is made between conclusions about the statistical techniques and how the techniques can or should be applied to ITS data archiving. Although the statistical techniques described may not be disputed, there is a wide range of possible aggregation solutions based on these statistical techniques. Ultimately, the aggregation solutions may be driven by nonstatistical parameters such as cost (e.g., “How much do we/the market value the data?”), ease of implementation, system requirements, and other constraints.

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