This paper proposes a method for using a forward-looking monocular camera along with previewed road geometry from a high-fidelity, low-dimensional map to estimate lateral planar vehicle states by measuring the vehicle's temporally anticipated reference trajectory. Theoretical estimator performance from a steady-state Kalman Filter implementation of the estimation framework is calculated for various look-ahead distances and vehicle speeds. Application of this filter structure to real driving data is also briefly discussed. The use of temporally previewed measurements of a vehicle's reference path is shown to greatly improve the accuracy of vehicle planar state estimates, and shows promise for use in closed-loop lane keeping and driver assist applications.


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    Title :

    Global and local frameworks for vehicle state estimation using temporally previewed mapped lane features


    Contributors:


    Publication date :

    2013-06-01


    Size :

    1222590 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    GLOBAL AND LOCAL FRAMEWORKS FOR VEHICLE STATE ESTIMATION USING TEMPORALLY PREVIEWED MAPPED LANE FEATURES

    Brown, A. / Brennan, S. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2013




    SASMEX previewed

    Online Contents | 1994