This paper focuses on driver's lane change intention on motorway. The first part of the paper presents the different types of intention and which intention is interesting to consider for a driver assistance system. Several methods are usable in order to solve our problem: method such as Hidden Markov Models (HMM), rule-based system, pattern matching. All these methods have already shown their accuracy to detect few driver manoeuvres. The drawbacks and assets of these methods are presented leading to the choice of a method based on pattern matching that will be discussed. This method will be illustrated by some applications. The second part of the paper will explain the set-up of an experimentation which was carried out with the full scale dynamic simulator SHERPA (University of Valenciennes). The experimentation was set-up in order to suggest the driver to overtake in several different situations which are similar to those in real driving condition. The run was designed on a motorway and contains interaction with other vehicles and the environment. The data collected during the experiment will next be used to build the intentions driver model. Three types of data will be analysed: electrophysiological data such as ECG (electrocardiogram), driving task performance such as steering wheel angle and indicators vehicle-environment interactions such as the position in the lane. The aim of this paper is to describe an experiment performed in order to predict the actions of a driver in a nearby future when he overtakes on motorway. The method used to propose a model of driver intention is based on pattern matching techniques.


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    Titel :

    Identification of driver's lane change intention on motorway by pattern matching method


    Weitere Titelangaben:

    Erkennung der Spurwechselabsicht auf einer Straße mit Hilfe der Spurverfolgungsmethode


    Beteiligte:
    Younsi, Karine (Autor:in) / Rajaonah, Bako (Autor:in) / Floris, Jerome (Autor:in) / Simon, Philippe (Autor:in) / Popieul, Christophe (Autor:in)


    Erscheinungsdatum :

    2007


    Format / Umfang :

    6 Seiten, 1 Bild, 10 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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