Current and future in-vehicle personal assistant systems stand to benefit from knowledge of the level of familiarity that the driver has with different parts of the current route. Such systems could use this information to adapt driving directions to be more succinct, understandable and personalized. However accumulating evidence of familiarity by direct experience alone could take many months and still be incomplete. Instead, we propose building predictive models of driver familiarity with road networks by generalizing intelligently from a small sample of data. Inspired by psychology studies that suggest a variety of cognitive models of route familiarity in humans, we present an ensemble of familiarity models using different machine learning methods on GPS time series data collected during normal driving by a volunteer pool of 22 drivers from San Francisco Bay area. We validate the models' predictions through an extensive questionnaire administered to the subjects about route familiarity and need for directions along select routes. Our results indicate that a significant component of driver familiarity can be predicted from unobtrusively collected driving data. We conclude with a proposed approach for integrating such models with a generator of driving directions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Driver familiarity modeling for generating navigation directions


    Contributors:


    Publication date :

    2013-10-01


    Size :

    903557 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Generating Real-Time Driver Familiarity Index for Fine-Grained Dynamic Road Scenes

    PILLAI PREETI J / YALLA VEERAGANESH / PARUNDEKAR RAHUL RAVI et al. | European Patent Office | 2017

    Free access

    Generating real-time driver familiarity index for fine-grained dynamic road scenes

    PILLAI PREETI J / YALLA VEERAGANESH / PARUNDEKAR RAHUL RAVI et al. | European Patent Office | 2017

    Free access

    Driver familiarity adapted explanations for proactive automated vehicle operations

    PARUNDEKAR RAHUL / AGOSTA JOHN MARK | European Patent Office | 2016

    Free access

    A study of driver experience and vehicle familiarity in accidents

    Fell, James C. / Mudrowsky, Edward F. / Tharp, Kenneth J. | Elsevier | 1972


    Technology for generating alternate navigation directions for vehicles

    CHAN AARON SCOTT / SANCHEZ KENNETH J | European Patent Office | 2019

    Free access