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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 - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, 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.
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Submitted on : Wednesday, October 24, 2007 - 6:57:24 PM
Last modification on : Wednesday, February 2, 2022 - 3:58:16 PM


  • HAL Id : inria-00182090, version 1



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. ⟨inria-00182090⟩



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