Control Systems Building Principles for Robotic Vehicles with Autonomous and Remote-Control Mode

Сусарев, С. В.; Sidorenko, Konstantin P.; Morev, A. S.; Gashenko, Julia

doi:10.1109/cscmp45713.2019.8976863

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…Для считывания накопленной информации о неисправностях и дефектах элементов автомобиля необходимо реализовать структуру хранения и обработки информации. Такая структура представлена в виде программно-аппаратного комплекса, который включает в себя сервер хранения данных и систему управления базой данных СУБД [1].…”

Section: бортовая система контроля автомобиляunclassified

“…В статье рассмотрены вопросы организации системы телематики и диагностирования технического состояния автономных автомобилей. Исследования проводились в рамках проекта ФЦП РФ по созданию роботизированных автомобилей КАМАЗ агротехнического назначения [1][2][3]. В пп.…”

Section: Introductionunclassified

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Telematics and diagnosis system for autonomous cargo vehicle

Orlov,

Kosareva

2024

Vestnik of Samara State Technical University. Technical Science

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The article deals with the problem of managing the operation and maintenance of autonomous trucks KAMAZ using a telematics and diagnostics system. The functions and composition of the onboard module of a robotic vehicle are described. The main controlled values are determined. The presence of a developed system for monitoring the state of units and assemblies provides a solution to the problem of controlling the modes of the car operation. The structure of the telematics and diagnostics system has been developed and implemented. The main blocks of the proposed system are shown. The main diagnostic and forecasting functions are performed on a workstation with an analytical module. It is proposed to use an approach based on previous conditions matrixes. An example of matrix analysis for a car engine cooling system is given. Modeling of the engine cooling system was carried out and graphs of transient processes were obtained. The analytical module is designed using artificial neural networks to analyze time series of car parameter values. To conduct virtual tests of a car in various operating modes, a simulation model was developed on a stochastic time colored Petri net. The model simulates both the movement of the vehicle to the point of production operations and the change in the technical condition of the car. The model makes it possible to describe and study the influence of random factors on the time of execution of production tasks, to take into account the probabilistic characteristics of failure events or defects in vehicle components and assemblies. The use of an artificial neural network in the analytical module of the diagnostic system workstation makes it possible to predict the technical condition of vehicle components and systems in real time, followed by verification of the dynamics of processes on a simulation model on a Petri net.

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Section: бортовая система контроля автомобиляunclassified

Section: Introductionunclassified