Aiming at shortcomings of the traditional decision-making models for lane changing, such as only considering the nearest time gaps, and using static gap models, overlook the dynamic characteristic of vehicles’ gap. A new lane-changing decision-making model is put forward based on dynamic gap. By adopting an approach of depth-first search and the designed satisfactory function, the gap that meets the most satisfaction is selected for lanes changing. The second model uses the constraint optimization model on the basis of the gap obtained by the previous model. It then uses the primal dual interior point method based on the second order cone programming (SOCP) to obtain the optimal trajectory, after considering the comfort and traffic flow. Finally, the correctness, robustness, and linkage of the two models are verified through the design of typical lane changing scenarios and simulation experiments.


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    Titel :

    A Lane-Changing Trajectory Planning and Assistant Decision-Making Method for Autonomous Vehicle


    Beteiligte:
    Cui, Zheyu (Autor:in) / Hu, Jianming (Autor:in) / Guan, Hongfei (Autor:in)

    Kongress:

    18th COTA International Conference of Transportation Professionals ; 2018 ; Beijing, China


    Erschienen in:

    CICTP 2018 ; 87-101


    Erscheinungsdatum :

    02.07.2018




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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