DEVELOPMENT OF PASSENGER CAR SAFETY

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F23%3A00002651" target="_blank" >RIV/75081431:_____/23:00002651 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.magnanimitas.cz/ADALTA/1302/papers/J_kovac.pdf" target="_blank" >https://www.magnanimitas.cz/ADALTA/1302/papers/J_kovac.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

DEVELOPMENT OF PASSENGER CAR SAFETY

Popis výsledku v původním jazyce

The goal of the paper was to assess safety of passenger cars sold in the Czech Republic in terms of the development of both active and passive safety features of cars sold between 2020-2022. Using content analysis aimed at collecting secondary data, the sales of passenger cars and their safety ratings were examined. Cluster analysis and neural networks were subsequently used to classify vehicles into self-organizing Kohonen maps, within which the movement between individual clusters was monitored. It was found that more than 25 % of vehicles sold between 2021 and 2022 changed their position compared to the year 2020. When taking into account vehicles newly introduced to the market, the average level of safety of vehicles sold compared to the year 2020. Further research could focus on a more detailed analysis of factors affecting safety on roads and their quantification for making better predictions and prevention of road accidents. It should be considered that vehicle safety ratings are based on a specific methodology and criteria and can vary significantly.

Název v anglickém jazyce

DEVELOPMENT OF PASSENGER CAR SAFETY

Popis výsledku anglicky

The goal of the paper was to assess safety of passenger cars sold in the Czech Republic in terms of the development of both active and passive safety features of cars sold between 2020-2022. Using content analysis aimed at collecting secondary data, the sales of passenger cars and their safety ratings were examined. Cluster analysis and neural networks were subsequently used to classify vehicles into self-organizing Kohonen maps, within which the movement between individual clusters was monitored. It was found that more than 25 % of vehicles sold between 2021 and 2022 changed their position compared to the year 2020. When taking into account vehicles newly introduced to the market, the average level of safety of vehicles sold compared to the year 2020. Further research could focus on a more detailed analysis of factors affecting safety on roads and their quantification for making better predictions and prevention of road accidents. It should be considered that vehicle safety ratings are based on a specific methodology and criteria and can vary significantly.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

50200 - Economics and Business

Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Ad Alta - Journal of Interdisciplinary Research

ISSN

1804-7890

e-ISSN

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Svazek periodika

13

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

7

Strana od-do

361-367

Kód UT WoS článku

001143971400044

EID výsledku v databázi Scopus

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