Intelligent transport systems - eSafety - eCall for automated and autonomous vehicles

The article presented a mathematical analysis of a double-circuit parametric circuit of ferroresonance nature at the fundamental frequency, performed by the harmonic balance method. The adjustment, current-voltage, and load characteristics of the circuit are given. The possibility of using this circuit in voltage regulators with direct current output is proved. Parametric sources of secondary power supply, in particular voltage stabilizers of ferromagnetic and ferroresonance nature, are used in autonomous vehicles (for example, in spacecraft, some types of intelligent transport systems) and in renewable energy sources due to their ability to operate in heavy environments (high and low temperatures, radiation, strong magnetic or electric fields).

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Road Design Criteria and Capacity Estimation Based on Autonomous Vehicles Performances. First Results from the European C-Roads Platform and A22 Motorway

Transport and Telecommunication Journal ◽

10.2478/ttj-2021-0018 ◽

2021 ◽

Vol 22 (2) ◽

pp. 230-243

Author(s):

Marco Guerrieri ◽

Raffaele Mauro ◽

Andrea Pompigna ◽

Natalia Isaenko

Keyword(s):

Autonomous Vehicles ◽

Theoretical Models ◽

Transport Systems ◽

Automated Vehicles ◽

Automated Driving ◽

Intelligent Transport Systems ◽

Intelligent Transport ◽

Road Design ◽

First Results ◽

New Criteria

Abstract Several European road operators and authorities joined the C-Roads Platform with the aim of harmonising the deployment activities of cooperative intelligent transport systems (C-ITS). C-ITS research is preliminary to future automated-driving vehicles. The current conventional highways were designed on traditional criteria and models specifically developed for traffic flows of manually guided vehicles. Thus, this article describes some new criteria for designing and monitoring road infrastructures on the basis of performance features of autonomous (or self-driving) vehicles. The new criteria have been adopted to perform an accurate conformity control of the A22 Brenner motorway, included in the C-Roads Platform, and also to ascertain whether in future it may be travelled by automated vehicles in safety conditions. Always in accordance with the technical and scientific insights required by the C-Roads Platform, a traffic model has been implemented to estimate how the A22 capacity increases compared to current values, by taking various percentages of automated or manual vehicles into consideration. The results given by theoretical models indicate that the highway will be able to be travelled by automated vehicles in safety conditions. On the other hand, the lane capacity is due to increase up to 2.5 times more than the current capacities, experimentally determined through traffic data collected from 4 highway sections by means of Drake’s flow model.

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STRUCTURE OF THE STREET ROAD NETWORK IN THE FREIGHT TRANSPORTATION SYSTEM

Bulletin of the Angarsk State Technical University ◽

10.36629/2686-777x-2021-1-15-155-159 ◽

2022 ◽

Vol 1 (15) ◽

pp. 155-159

Author(s):

Ol'ga Lebedeva ◽

Vasilisa Kuzminykh

Keyword(s):

Transport System ◽

Autonomous Vehicles ◽

Road Network ◽

Road Transport ◽

Transport Systems ◽

Intelligent Transport Systems ◽

Intelligent Transport ◽

The Road ◽

Transportation Process ◽

Important Design

The road network constitutes the main part of the transport system for both passenger and freight traffic. Achieving a sustainable road transport system including multimodal terminals, autonomous vehicles, intelligent transport systems, infrastructure are considered to be important design areas. The efficient use of the transport system is essential in terms of economic, environmental and social sustainability. Therefore, it is necessary to develop methods for optimizing the transportation process

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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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