An Intelligent Driving System for Automatically Anticipating and Negotiating Road Curves

Abstract : 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 (C2i), NTU, aims at using fuzzy neural architectures such as GenSoFNN-Yager to realize intelligent driving i.e., 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.
Type de document :
Communication dans un congrès
International Conference on Intelligent Robots and Systems, Oct 2007, San Diego, United States
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https://hal.inria.fr/inria-00171498
Contributeur : David Partouche <>
Soumis le : mercredi 12 septembre 2007 - 15:09:39
Dernière modification le : jeudi 11 janvier 2018 - 06:21:05

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  • HAL Id : inria-00171498, version 1

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David Partouche, Michel Pasquier, Matthew Chan. An Intelligent Driving System for Automatically Anticipating and Negotiating Road Curves. International Conference on Intelligent Robots and Systems, Oct 2007, San Diego, United States. 〈inria-00171498〉

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