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Bücher Wissen & Bildung Englische Bücher Naturwissenschaft, Medizin, Informatik, Technik Technik Elektronik, Elektro- und Nachrichtentechnik A multi-sensor intelligent assistance system for driver status monitoring and intention prediction
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A multi-sensor intelligent assistance system for driver status monitoring and intention prediction
Li Li (Taschenbuch, Englisch)
Optischer Zustand
Beschreibung
Abstract
Advanced sensing systems, sophisticated algorithms, and increasing computational
resources continuously enhance the advanced driver assistance systems (ADAS). To date,
despite that some vehicle based approaches to driver fatigue/drowsiness detection have been
realized and deployed, objectively and reliably detecting the fatigue/drowsiness state of driver
without compromising driving… experience still remains challenging. In general, the choice of
input sensorial information is limited in the state-of-the-art work. On the other hand, smart and
safe driving, as representative future trends in the automotive industry worldwide, increasingly
demands the new dimensional human-vehicle interactions, as well as the associated
behavioral and bioinformatical data perception of driver. Thus, the goal of this research work
is to investigate the employment of general and custom 3D-CMOS sensing concepts for the
driver status monitoring, and to explore the improvement by merging/fusing this information
with other salient customized information sources for gaining robustness/reliability. This thesis
presents an effective multi-sensor approach with novel features to driver status monitoring
and intention prediction aimed at drowsiness detection based on a multi-sensor intelligent
assistance system – DeCaDrive, which is implemented on an integrated soft-computing
system with multi-sensing interfaces in a simulated driving environment. Utilizing active
illumination,the IR depth camera of the realized system can provide rich facial and body
features in 3D in a non-intrusive manner. In addition, steering angle sensor, pulse rate
sensor, and embedded impedance spectroscopy sensor are incorporated to aid in the
detection/prediction of driver’s state and intention. A holistic design methodology for ADAS
encompassing both driver- and vehicle-based approaches to driver assistance is discussed in
the thesis as well. Multi-sensor data fusion and hierarchical SVM techniques are used in
DeCaDrive to facilitate the classification of driver drowsiness levels based on which a warning
can be issued in order to prevent possible traffic accidents. The realized DeCaDrive system
achieves up to 99.66% classification accuracy on the defined drowsiness levels, and exhibits
promising features such as head/eye tracking, blink detection, gaze estimation that can be
utilized in human-vehicle interactions. However, the driver’s state of ”microsleep” can hardly
be reflected in the sensor features of the implemented system. General improvements on the
sensitivity of sensory components and on the system computation power are required to
address this issue. Possible new features and development considerations for DeCaDrive are
discussed as well in the thesis aiming to gain market acceptance in the future. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
01.02.2017
Sprache
Englisch
EAN
9783959740418
Herausgeber
RPTU Rheinland-Pfälzische Technische Universität Kaiserslautern Landau
Serien- oder Bandtitel
Forschungsberichte Integrierte Sensorsysteme
Sonderedition
Nein
Autor
Li Li
Seitenanzahl
169
Einbandart
Taschenbuch
Bandzählung
08
Schlagwörter
sensor fusion, depth sensing, impedance spectroscopy
Thema-Inhalt
TJ - Elektronik, Nachrichtentechnik
Höhe
210 mm
Breite
14.8 cm
-.-
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