Rapid parking trajectory planning is very import for intelligent cyber-physical transportation systems. A three-stage Gaussian pseudo-spectrum data-driven fuzzy logic parallel parking trajectory planning algorithm is proposed in this work. First, a three-stage parking trajectory planning dynamic optimization problem (DOP) is established based on the three stages parking division and vehicle kinematics model. Subsequently, an improved three-stage Gaussian pseudo-spectrum method (T-GPM) is proposed to solve the typical DOPs so as to construct the database. With analyzing the database, fuzzy rules are designed to achieve fuzzy logic-based data-driven parking trajectory planning, which would extremely decrease the planning time of parking trajectory. To verify the performance of the proposed method, numerical simulation tests are conducted and results show that with using the data-driven fuzzy logic strategy, the proposed planning method can quickly and effectively generate parking trajectories online with small deviation, and the calculation time is reduced by over 99% compared to T-GPM. Furthermore, the CarSim co-simulation tests and real car parking tests are conducted with different scenarios. Experiments demonstrate that feasible parking trajectories can be generated by the proposed method and the trajectories are tracked with no collision, revealing the effectiveness of the improvement.


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    Titel :

    Gaussian Pseudo-spectrum Optimization-Based Fuzzy Logic Parallel Parking Trajectory Planning


    Untertitel :

    Gaussian Pseudo-Spectrum Optimization-Based Fuzzy Logic… W. He et al.


    Weitere Titelangaben:

    Int.J Automot. Technol.


    Beteiligte:
    He, Wen (Autor:in) / Chen, Yong (Autor:in) / Liu, Tao (Autor:in) / Ren, Fan (Autor:in) / Wan, Kailin (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.02.2025


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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