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2014 | OriginalPaper | Chapter

6. Monitoring Driver’s State and Predicting Unsafe Driving Behavior

Author : Hang-Bong Kang

Published in: Algorithm & SoC Design for Automotive Vision Systems

Publisher: Springer Netherlands

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Abstract

In recent years, driver drowsiness and distraction have been important factors in a large number of accidents because they reduce driver perception level and decision making capability, which negatively affect the ability to control the vehicle. One way to reduce these kinds of accidents would be through monitoring driver and driving behavior and alerting the driver when they are drowsy or in a distracted state. In addition, if it were possible to predict unsafe driving behavior in advance, this would also contribute to safe driving. In this chapter, we will discuss various monitoring methods for driver and driving behavior as well as for predicting unsafe driving behaviors. In respect to measurement methods of driver drowsiness, we discussed visual and non-visual features of driver behavior, as well as driving performance behaviors related to vehicle-based features. Eye related measurements such as PERCLOS, yawning detection and some limitations in measuring visual features are discussed in detail. As for non-visual features, we explore various physiological signals and possible drowsiness detection methods that use these signals. As for vehicle-based features, we describe steering wheel movement and the standard deviation of lateral position. To detect driver distraction, we describe head pose and gaze direction methods. To predict unsafe driving behavior, we explain predicting methods based on facial expressions and car dynamics. Finally, we discuss several issues to be tackled for active driver safety systems. They are (1) hybrid measures for drowsiness detection, (2) driving context awareness for safe driving, (3) the necessity for public data sets of simulated and real driving conditions.

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Metadata
Title
Monitoring Driver’s State and Predicting Unsafe Driving Behavior
Author
Hang-Bong Kang
Copyright Year
2014
Publisher
Springer Netherlands
Book
Algorithm & SoC Design for Automotive Vision Systems

Print ISBN: 978-94-017-9074-1

Electronic ISBN: 978-94-017-9075-8

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-94-017-9075-8_6