INTRODUCTION OF INFORMATION AND TELECOMMUNICATION SYSTEMS MANAGEMENT MECHANISM VEHICLES

The analysis of the intensity of the development of intelligent transport systems. The efficiency of information and telecommunications systems in the mechanism of driving. Designed chart of the events occurrence dangerous situation in case of failure of controls on the example of the lighting system

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The study of intelligent transport systems management of convoy of unmanned vehicles with a lead vehicle with the purpose of increase of efficiency of cargo transportation

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/431/1/012052 ◽

2020 ◽

Vol 431 ◽

pp. 012052

Author(s):

D. Endachev ◽

A. Kolbasov ◽

K. Karpukhin

Keyword(s):

Unmanned Vehicles ◽

Transport Systems ◽

Systems Management ◽

Intelligent Transport Systems ◽

Intelligent Transport ◽

Cargo Transportation ◽

Lead Vehicle

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Cooperative Intelligent Transport Systems: Towards high-level automated driving

10.1049/pbtr025e ◽

2019 ◽

Keyword(s):

Transport Systems ◽

Automated Driving ◽

Intelligent Transport Systems ◽

Intelligent Transport ◽

High Level

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Multiple vehicles detection and tracking for intelligent transport systems using machine learning approaches

Transport and Communication Science Journal ◽

10.25073/tcsj.70.3.7 ◽

2019 ◽

Vol 70 (3) ◽

pp. 214-224

Author(s):

Bui Ngoc Dung ◽

Manh Dzung Lai ◽

Tran Vu Hieu ◽

Nguyen Binh T. H.

Keyword(s):

Machine Learning ◽

Gaussian Mixture ◽

Research Field ◽

Transport Systems ◽

Learning Approaches ◽

Subtraction Method ◽

Intelligent Transport Systems ◽

Intelligent Transport ◽

Detection And Tracking ◽

Multiple Vehicles

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.

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