This study aims to improve the accuracy of trajectory prediction in lane-changing scenarios compared to the state-of-the-art. Lane-changing trajectory prediction is critical for autonomous vehicle driving safety in the complex traffic environment. This paper proposed a novel vehicle lane-changing prediction method by combining kinematics and data-driven-based methods in an interactive framework. Firstly, a kinematics-based prediction method, Constant Angle Rate and Velocity Model (CTRV), and a data-driven prediction method, Long Short-Term Memory Network (LSTM) are systematically compared. It is demonstrated that CTRV is difficult to capture long-horizon lane-changing dynamics, and generates the results in low accuracy. On the contrary, LSTM performs better in lane-changing long-horizon scenarios, but worse in short-horizon scenarios, due to the difficulty of precise fitting in data-driven architecture. In this case, we construct a novel interactive multi-model (IMM) trajectory prediction method that combines the above two prediction models. This method successfully captures the short-horizon and long-horizon vehicle lane-changing dynamics and improves the prediction accuracy greatly. Public dataset NGSIM I-80 is adopted for simulation and validation. Results show that the IMM-based approach reduced the lane-changing trajectory prediction error by 3% at least compared to LSTM methods.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vehicle Lane-changing Trajectory Prediction Based on Interactive Multiple Model


    Beteiligte:
    Zhang, Hui (Autor:in)

    Kongress:

    ICETIS 2022 - 7th International Conference on Electronic Technology and Information Science ; 2022 ; Harbin, China


    Erschienen in:

    Erscheinungsdatum :

    01.01.2022


    Format / Umfang :

    7 pages



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Lane changing trajectory planning method for autonomous vehicle

    WANG JIAN / HAN HAIYANG / PEI ZHONGHUI | Europäisches Patentamt | 2023

    Freier Zugriff

    Intelligent vehicle autonomous lane changing trajectory planning method

    CHEN LINFENG / WAN YIDONG / WANG RONGJUN et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Intelligent vehicle lane changing trajectory planning method based on model predictive control

    QIN JIALE / ZHANG ZHAOJUN / LUO HONGJIE et al. | Europäisches Patentamt | 2025

    Freier Zugriff


    Vehicle interactive lane changing method considering multi-vehicle game

    MA YANLI / LYU ZHILIANG / XU XIAOPENG et al. | Europäisches Patentamt | 2022

    Freier Zugriff