Computer-based guidance of passenger vehicles is a common reality today, but cost, computation, and robustness challenges remain to obtain accurate vehicle state estimates. This study builds on previous work by the authors towards the development of a vehicle state estimation framework that uses optimal preview control theory to fuse map, GPS, inertial, and forward-looking camera information in a linear filter that offers a-priori predictions of state estimate accuracy. By designing an optimal preview controller around a preview filter designed to make full use of a test vehicle's low-cost sensors, on-board map, and available visibility, a matched perception and control system is obtained. The resulting preview-based guidance system has a structure similar to LQG algorithms, and is tested both in simulation and on a real vehicle. The closed loop system provides lane-level tracking performance with low cost sensors.


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    Title :

    Temporal preview estimation for design of a low cost lane-following system using a forward-facing monocular camera


    Contributors:


    Publication date :

    2014-06-01


    Size :

    1795823 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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