Predicting turn and stop maneuvers of potentially errant drivers is a basic requirement for advanced driver assistance systems for urban intersections. Previous work has shown that an early estimate of the driver's intent can be inferred by evaluating the vehicle's speed during the intersection approach. In the presence of a preceding vehicle, however, the velocity profile might be dictated by car-following behaviour rather than by the need to slow down before doing a left or right turn. To infer the driver's intent under such circumstances, a simple, real-time capable approach using an explicit model to represent both car-following and turning behaviour is proposed. Models for typical turning behavior are extracted from real world data. Preliminary results based on a Bayes net classification are presented.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Driver intent inference at urban intersections using the intelligent driver model


    Contributors:


    Publication date :

    2012-06-01


    Size :

    1492524 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Driver Intent Inference at Urban Intersections Using the Intelligent Driver Model

    Liebner, M. / Baumann, M. / Klanner, F. et al. | British Library Conference Proceedings | 2012


    Driver Intent Inference and Risk Assessment

    Liebner, Martin / Klanner, Felix | Springer Verlag | 2015


    Context-based estimation of driver intent at road intersections

    Lefevre, S. / Ibanez-Guzman, J. / Laugier, C. | IEEE | 2011


    Generic driver intent inference based on parametric models

    Liebner, Martin / Ruhhammer, Christian / Klanner, Felix et al. | IEEE | 2013