scholarly journals FACTORS DETERMINING THE DEVELOPMENT OF INTELLIGENT TRANSPORT SYSTEMS

2021 ◽  
Vol 19 (02) ◽  
pp. 229-243
Author(s):  
Laima Okunevičiūtė Neverauskienė ◽  
Marta Novikova ◽  
Eglė Kazlauskienė

Purpose – foreign and Lithuanian researchers analyse the benefits of ITS (Intelligent transport systems) application and development opportunities in various aspects. Due to the rapid development of technology, most authors emphasise the need for new or at least repeated research on intelligent transport systems ITS. The aim of this article is to evaluate the factors determining the development of ITS after theoretical substantiation. Research methodology – the primary data was collected from the following databases: Eurostat, OECD, World Bank. This study uses the analysis of scientific literature, expert survey, multicriteria assessment (SAW and COPRAS methods). Findings – the results of this article indicate which factors determine the development of ITS the most: investments, the aim to increase road safety, well-developed infrastructure. It also identifies which of the chosen for analaysis countries has the greatest potential for developing of ITS – Germany. Research limitations – firstly, due to the lack of statistics only eight countries are included and the period of analysis is only two years. Another limitation is that experts from only two countries completed the survey. Practical implications – research on the development of ITS is carried out in order to analyse the country that has the biggest opportunity to develop ITS and the factors affecting the mentioned development. The results can be beneficial for ministries of transport in different countries for planning the application of ITS. Originality/Value – current study contributes to the existing literature by examining the specific factors affecting the development of ITS that were not analysed earlier. This article differs from others as includes some Northern ,Western European and Baltic countries. Findings can be used by government in planning the installation of ITS to get the maximum benefit from it.


2021 ◽  
Vol 18 (4) ◽  
pp. 156-173
Author(s):  
E. V. Budrina ◽  
A. S. Lebedeva ◽  
L. I. Rogavichene ◽  
K. B. Kvitko

The article examines the prospects for organizing a cluster as an effective tool for ensuring connectivity of territories of the Russian Federation through the systematic and integrated implementation of intelligent transport technologies, which corresponds to strategic directions of development of transport in the Russian Federation and determines the relevance of the topic. The objective of the study is to determine the features of organisation of the transport and logistics cluster prioritising development of intelligent transport technologies by analysing the prospects for their development, studying variability of characteristics and structure of the cluster under various conditions of its formation based on the methods of formal logic, grouping, analysis of statistical data, normative-legal information, information synthesis. The study resulted in identification of prerequisites for the most rapid development and effective implementation of intelligent transport systems within the cluster. The expediency of using this approach has been substantiated, despite its labour intensity and cost. The study suggests definitions of an innovative transport and logistics cluster, as wells as characteristics of the transport and logistics cluster prioritising intelligent transport technologies. The study revealed the specifics of organisation of this cluster, which is primarily determined by the presence of dual characteristics. The peculiarities of cluster formation are reflected in the proposed structure of the cluster under study. The role of the state in organizing an innovative transport and logistics cluster is also defined



2019 ◽  
Vol 70 (3) ◽  
pp. 214-224
Author(s):  
Bui Ngoc Dung ◽  
Manh Dzung Lai ◽  
Tran Vu Hieu ◽  
Nguyen Binh T. H.

Video surveillance is emerging research field of intelligent transport systems. This paper presents some techniques which use machine learning and computer vision in vehicles detection and tracking. Firstly the machine learning approaches using Haar-like features and Ada-Boost algorithm for vehicle detection are presented. Secondly approaches to detect vehicles using the background subtraction method based on Gaussian Mixture Model and to track vehicles using optical flow and multiple Kalman filters were given. The method takes advantages of distinguish and tracking multiple vehicles individually. The experimental results demonstrate high accurately of the method.



2020 ◽  
Vol 70 (3) ◽  
pp. 64-71
Author(s):  
A.S. BODROV ◽  
◽  
M.V. KULEV ◽  
D.S. DEVYATINA ◽  
O.A. LOBYNTSEVA ◽  
...  


Sign in / Sign up

Export Citation Format

Share Document