NDLI: Modeling of drivers collision avoidance behavior based on hybrid system model: an approach with data clustering

Content Provider	IEEE Xplore Digital Library
Author	Suzuki, T. Yamada, S. Hayakawa, S. Tsuchida, N. Tsuda, T. Fujinami, H.
Copyright Year	2005
Description	Author affiliation: Dept. of Mech. Sci. & Eng., Nagoya Univ., Japan (Suzuki, T.; Yamada, S.)
Abstract	This paper presents a development of the modeling of the human driving behavior based on the expression as hybrid dynamical system (HDS) focusing on the driver's collision avoidance behavior. The driving data are collected by using the three-dimensional driving simulator based on CAVE, which provides stereoscopic immersive vision. In our modeling, the relationship between the measured information such as the sensory information of range between cars, range rate and lateral displacement between cars and the output of driver of the steering amount are expressed by the piecewise linear (PWL) model, which is a class of HDS. Then, we solve the identification problem for the PWL model by using the combination of data clustering and support vector machine. By introducing the PWL model, it becomes possible to find not only coefficients in each submodel but also parameters in the logical (switching) conditions from the measured driving data. From the obtained results, it is found that the driver appropriately switches the 'control law' according to the sensory information. This enables us to capture not only the physical meaning of the driving skill, but also the decision-making aspect (switching conditions) in the driver's collision avoidance behavior.
Starting Page	3817
Ending Page	3822
File Size	4903611
Page Count	6
File Format	PDF
ISBN	0780392981
DOI	10.1109/ICSMC.2005.1571741
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Collision avoidance Humans Decision making Displacement measurement Piecewise linear techniques Support vector machines Switches Three dimensional displays Neural networks Fuzzy systems
Content Type	Text
Resource Type	Article

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