Intelligent vehicles should be capable to understand the intention of other traffic participants when driving on urban roads. Yet, current approaches mostly emphasize the importance of the crossing/not-crossing (C/NC) problem and neglect the intention estimation task. To this end, we propose a pedestrian intention estimation method based on the extended theory of planned behavior (TPB). In contrast to previous qualitative modeling based on surveys and questionnaires, neural networks and hand-crafted rules are designed to quantitatively model the components of the extended TPB in the proposed architecture. Besides, the interaction between the components is simulated by a mixed classification strategy. Our pedestrian intention estimation model achieves 82% accuracy and outperforms the baseline method by 3% on the pedestrian intention estimation (PIE) dataset.


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    Titel :

    Applying the Extended Theory of Planned Behavior to Pedestrian Intention Estimation


    Beteiligte:
    Wu, Haoran (Autor:in) / Zheng, Sifa (Autor:in) / Xu, Qing (Autor:in) / Wang, Jianqiang (Autor:in)


    Erscheinungsdatum :

    11.07.2021


    Format / Umfang :

    538217 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch