An Intelligent Driving System for Automatically Anticipating and Negotiating Road Curves

Yijun Matthew Chan 1 David Partouche 1 Michel Pasquier 1
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes
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
Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robots and Systems, 2007, San Diego (CA), United States. 2007
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https://hal.inria.fr/inria-00182090
Contributeur : Christian Laugier <>
Soumis le : mercredi 24 octobre 2007 - 18:57:24
Dernière modification le : jeudi 11 janvier 2018 - 06:20:04

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  • HAL Id : inria-00182090, version 1

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Yijun Matthew Chan, David Partouche, Michel Pasquier. An Intelligent Driving System for Automatically Anticipating and Negotiating Road Curves. Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robots and Systems, 2007, San Diego (CA), United States. 2007. 〈inria-00182090〉

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