Car-following is the most general behavior in highway driving. It is crucial to recognize the cut-in intention of vehicles from an adjacent lane for safe and cooperative driving. In this paper, a method of behavior estimation is proposed to recognize and predict the lane change intentions based on the contextual traffic information. A model predictive controller is designed to optimize the acceleration sequences by incorporating the lane-change intentions of other vehicles. The public data set of next generation simulation is labeled and then published as a benchmarking platform for the research community. Experimental results demonstrate that the proposed method can accurately estimate vehicle behavior and therefore outperform the traditional car-following control.


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    Title :

    Lane-Change Intention Estimation for Car-Following Control in Autonomous Driving


    Contributors:
    Zhang, Yihuan (author) / Lin, Qin (author) / Wang, Jun (author) / Verwer, Sicco (author) / Dolan, John M. (author)

    Published in:

    Publication date :

    2018-09-01


    Size :

    2045726 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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