NDLI: An Adaptive Longitudinal Driving Assistance System Based on Driver Characteristics

Content Provider	IEEE Xplore Digital Library
Author	Jianqiang Wang Lei Zhang Dezhao Zhang Keqiang Li
Copyright Year	2000
Abstract	A prototype of a longitudinal driving-assistance system, which is adaptive to driver behavior, is developed. Its functions include adaptive cruise control and forward collision warning/avoidance. The research data came from driver car-following tests in real traffic environments. Based on the data analysis, a driver model imitating the driver's operation is established to generate the desired throttle depression and braking pressure. Algorithms for collision warning and automatic braking activation are designed based on the driver's pedal deflection timing during approach (gap closing). A self-learning algorithm for driver characteristics is proposed based on the recursive least-square method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data in the manual operation phase, and the identification result is applied during the automatic control phase in real time. A test bed with an electronic throttle and an electrohydraulic brake actuator is developed for system validation. The experimental results show that the self-learning algorithm is effective and that the system can, to some extent, adapt to individual characteristics.
Sponsorship	IEEE Intelligent Transportation Systems Society
Starting Page	1
Ending Page	12
Page Count	12
File Size	1372717
File Format	PDF
ISSN	15249050
Volume Number	14
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Adaptation models Algorithm design and analysis Analytical models Data models Vehicle dynamics Adaptive systems self-learning algorithm Car following driver characteristics driving-assistance systems
Content Type	Text
Resource Type	Article
Subject	Automotive Engineering Mechanical Engineering Computer Science Applications

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