Prerequisites for Further Deploying ITS Systems: The Case of Greece

Iordanopoulos, Panagiotis; Mitsakis, Evangelos; Chalkiadakis, Charis

doi:10.3311/pptr.11174

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…the information technology, urban development and automotive industries. These aspects are interrelated, therefore, a more efficient Intelligent Transportation System (ITS) could be realized [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Examination of fuel consumption factors, basics of precision and on-board diagnostic measurements

Busznyák¹,

Lakatos²

2020

Hung. J. Ind. Chem.

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In this paper, different factors of fuel consumption are examined. Driveload equitation is used as a basis and the parts that handle energy consumption in particular are analyzed. For the purposes of visibility, it was implemented using MAT-LAB. In statistical works, fuel consumption data require that the energy consumption of vehicles be analyzed correctly. Variables which affect fuel consumption during a given drive are defined. Research is analyzed in the second part of the paper where vehicle diagnostics are combined with global positioning. Examinations are necessary to create on-board diagnostics-based positioning.

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Section: Introductionmentioning

confidence: 99%

Examination of fuel consumption factors, basics of precision and on-board diagnostic measurements

Busznyák¹,

Lakatos²

2020

Hung. J. Ind. Chem.

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“…It can be said that the theoretical foundation and application [12] of IDM models is very good, however, the complexity [7,11] of real-world traffic processes poses serious problems to professionals in the applications. On the one hand, greater error tolerance than the accuracy of traffic parameters is to be expected than in many other dynamical systems.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Dynamic-based Approach for the Optimization of Traffic Parameters of the Intelligent Driver Model (IDM) and for the Support of Autonomous Vehicles’ Driving Ability

2019

APH

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The research identifies the dynamical parameters in the area of mechanics within the base of traffic model parameters used by the Intelligent Driver Model (IDM), which are the highest acceleration parameters set by the vehicle, the desired speed parameters of the vehicle and the distance-keeping parameters of the vehicle. All this facilitates the automatic control of autonomous electric vehicles in certain vehicle groups.

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Prerequisites for Further Deploying ITS Systems: The Case of Greece

Abstract: The deployment of Intelligent Transport Systems (ITS) is a strategic decision for the European Union (EU

Cited by 2 publications

References 2 publications

Examination of fuel consumption factors, basics of precision and on-board diagnostic measurements

Examination of fuel consumption factors, basics of precision and on-board diagnostic measurements

Vehicle Dynamic-based Approach for the Optimization of Traffic Parameters of the Intelligent Driver Model (IDM) and for the Support of Autonomous Vehicles’ Driving Ability

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