Application of Artificial Neural Networks to Streamline the Process of Adaptive Cruise Control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F29142890%3A_____%2F21%3A00041385" target="_blank" >RIV/29142890:_____/21:00041385 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2071-1050/13/8/4572/htm" target="_blank" >https://www.mdpi.com/2071-1050/13/8/4572/htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/su13084572" target="_blank" >10.3390/su13084572</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of Artificial Neural Networks to Streamline the Process of Adaptive Cruise Control

Popis výsledku v původním jazyce

This article deals with the use of neural networks for estimation of deceleration model parameters for the adaptive cruise control unit. The article describes the basic functionality of adaptive cruise control and creates a mathematical model of braking, which is one of the basic functions of adaptive cruise control. Furthermore, an analysis of the influences acting in the braking process is performed, the most significant of which are used in the design of deceleration prediction for the adaptive cruise control unit using neural networks. Such a connection using artificial neural networks using modern sensors can be another step towards full vehicle autonomy. The advantage of this approach is the original use of neural networks, which refines the determination of the deceleration value of the vehicle in front of a static or dynamic obstacle, while including a number of influences that affect the braking process and thus increase driving safety.

Název v anglickém jazyce

Application of Artificial Neural Networks to Streamline the Process of Adaptive Cruise Control

Popis výsledku anglicky

This article deals with the use of neural networks for estimation of deceleration model parameters for the adaptive cruise control unit. The article describes the basic functionality of adaptive cruise control and creates a mathematical model of braking, which is one of the basic functions of adaptive cruise control. Furthermore, an analysis of the influences acting in the braking process is performed, the most significant of which are used in the design of deceleration prediction for the adaptive cruise control unit using neural networks. Such a connection using artificial neural networks using modern sensors can be another step towards full vehicle autonomy. The advantage of this approach is the original use of neural networks, which refines the determination of the deceleration value of the vehicle in front of a static or dynamic obstacle, while including a number of influences that affect the braking process and thus increase driving safety.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Sustainability

ISSN

2071-1050

e-ISSN

—

Svazek periodika

13

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

25

Strana od-do

1-25

Kód UT WoS článku

000645367400001

EID výsledku v databázi Scopus

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