Abstract The task of driving is very complex and highly demanding for the individual. The optimal driver assistance strongly depends on the situation and the driver’s needs. In particular, this applies to driving manoeuvres as lane changes. Consequently, future advanced driver assistance systems will have to detect and assess driving situations as well as the driver’s intentions automatically before a driving manoeuvre is initiated. The method proposed predicts situations of upcoming lane changes based on assessments of the environmental situation and the driver’s behaviour. For this purpose, information gained from a 360° sensory perception of the vehicle surroundings and from the analysis of the driver’s gaze behaviour is fused by means of a Bayesian network. The implemented algorithms work in real-time and provide a probabilistic estimation of the intention of the driver to perform a specific manoeuvre. The application of prediction was integrated into a test vehicle and evaluated by using real traffic data and driving studies.


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    Titel :

    Fusion of Driver Behaviour Analysis and Situation Assessment for Probabilistic Driving Manoeuvre Prediction


    Beteiligte:


    Erscheinungsdatum :

    23.06.2017


    Format / Umfang :

    22 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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