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Pre-crash control strategy of driver assistance system

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23210%2F21%3A43961964" target="_blank" >RIV/49777513:23210/21:43961964 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.nnw.cz/doi/2021/NNW.2021.31.004.pdf" target="_blank" >http://www.nnw.cz/doi/2021/NNW.2021.31.004.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.14311/NNW.2021.31.004" target="_blank" >10.14311/NNW.2021.31.004</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Pre-crash control strategy of driver assistance system

  • Original language description

    The aim of the article is the optimisation process of the ADAS (Advanced Driver Assistance Systems) control. The methodology is based on the classi-fication of ADAS systems according to the situations of unavoidable accidents. Theevaluation of expected consequences uses injury biomechanics, which represents theextended definition of HMI (Human-Machine Interaction). The evaluation of injury mechanism and the machine intervention enables to control this process withthe target to minimise the consequent injuries. Then the decision making takesnew inputs to the control process and it enriches the multiparametric control ofthe system with the target to minimise the consequences.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20301 - Mechanical engineering

Result continuities

  • Project

    <a href="/en/project/TN01000026" target="_blank" >TN01000026: Josef Bozek National Center of Competence for Surface Vehicles</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Neural Network World

  • ISSN

    1210-0552

  • e-ISSN

  • Volume of the periodical

    31

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    12

  • Pages from-to

    77-88

  • UT code for WoS article

    000670424400004

  • EID of the result in the Scopus database

    2-s2.0-85111877584