Steering wheel motion analysis for detection of the driver's drowsiness

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F11%3APU95748" target="_blank" >RIV/00216305:26220/11:PU95748 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Steering wheel motion analysis for detection of the driver's drowsiness

Popis výsledku v původním jazyce

Reliable system for driver's drowsiness recognition is the aim of many studies. Unfortunately, majority of researchers work with data acquired in laboratory with ideal or simulated conditions. Therefore it is difficult to implement their results to realvehicle and prove its reliability and accuracy. The analyzed data in this paper is acquired from real traffic and therefore it contains all uncertainty partially modeled in laboratory. For data acquisition has been chosen in-direct measurement from vehicle CAN bus in order to not affect the driver. All data are preprocessed according to assumptions about driver's behavior and transformed to frequency domain by means of orthogonal transform (STFT, CWT and DWT). Subsequently, data is analyzed by data mining methods including features extraction and filter feature selection. The performance of the features is measured by the area under the receiver operating characteristic.

Název v anglickém jazyce

Steering wheel motion analysis for detection of the driver's drowsiness

Popis výsledku anglicky

Reliable system for driver's drowsiness recognition is the aim of many studies. Unfortunately, majority of researchers work with data acquired in laboratory with ideal or simulated conditions. Therefore it is difficult to implement their results to realvehicle and prove its reliability and accuracy. The analyzed data in this paper is acquired from real traffic and therefore it contains all uncertainty partially modeled in laboratory. For data acquisition has been chosen in-direct measurement from vehicle CAN bus in order to not affect the driver. All data are preprocessed according to assumptions about driver's behavior and transformed to frequency domain by means of orthogonal transform (STFT, CWT and DWT). Subsequently, data is analyzed by data mining methods including features extraction and filter feature selection. The performance of the features is measured by the area under the receiver operating characteristic.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/GA102%2F09%2F1897" target="_blank" >GA102/09/1897: Bezpečnost automobilové dopravy - BAD</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Mathematical Models and Methods in Modern Science

ISBN

978-1-61804-055-8

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

256-261

Název nakladatele

WSEAS Press

Místo vydání

Puerto de la Cruz, Tenerife, Spain

Místo konání akce

Puerto de la Cruz, Tenerife, Španělsko

Datum konání akce

10. 12. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—