An intelligent driving system for automatically anticipating and negotiating road curves

Human error is the main cause of the many road traffic accidents which every year take the lives of millions of people and injure many more. Driving safety is thus a major concern leading to research in autonomous driving systems. One project at the centre for computational intelligence (C 2 i), NTU...

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Bibliographic Details
Published in2007 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 117 - 122
Main Authors Chan, M., Partouche, D., Pasquier, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2007
Subjects
Automated highways
Automatic control
Competitive intelligence
Computational intelligence
Fuzzy neural networks
Fuzzy systems
Humans
Intelligent robots
Intelligent systems
Road accidents
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ISBN9781424409112
142440911X
ISSN2153-0858
DOI10.1109/IROS.2007.4399350

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Summary:Human error is the main cause of the many road traffic accidents which every year take the lives of millions of people and injure many more. Driving safety is thus a major concern leading to research in autonomous driving systems. One project at the centre for computational intelligence (C 2 i), NTU, aims at using fuzzy neural architectures such as GenSoFNN-Yager to realize intelligent driving Le., to learn to autonomously park, make U-turns, drive, and even decide when to change lane, overtake, etc. This paper presents recent work on intelligent speed adaptation and steering control (ISASC), a novel feature of which is the ability to anticipate the road profile and negotiate curves safely. The proposed system was developed and tested on a driving simulator. Experimental results show the robustness of the system in learning from example the desired human driving expertise and applying this knowledge to negotiate new unseen roads.
ISBN:9781424409112
142440911X
ISSN:2153-0858
DOI:10.1109/IROS.2007.4399350