Designing autonomous vehicles for urban environments remains an unresolved problem. One major dilemma faced by autonomous cars is understanding the intention of other road users and communicating with them. To investigate one aspect of this, specifically pedestrian crossing behavior, we have collected a large dataset of pedestrian samples at crosswalks under various conditions (e.g., weather) and in different types of roads. Using the data, we analyzed pedestrian behavior from two different perspectives: the way they communicate with drivers prior to crossing and the factors that influence their behavior. Our study shows that changes in head orientation in the form of looking or glancing at the traffic is a strong indicator of crossing intention. We also found that context in the form of the properties of a crosswalk (e.g., its width), traffic dynamics (e.g., speed of the vehicles) as well as pedestrian demographics can alter pedestrian behavior after the initial intention of crossing has been displayed. Our findings suggest that the contextual elements can be interrelated, meaning that the presence of one factor may increase/decrease the influence of other factors. Overall, our work formulates the problem of pedestrian-driver interaction and sheds light on its complexity in typical traffic scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Understanding Pedestrian Behavior in Complex Traffic Scenes


    Beteiligte:
    Rasouli, Amir (Autor:in) / Kotseruba, Iuliia (Autor:in) / Tsotsos, John K. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.03.2018


    Format / Umfang :

    1013398 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Pedestrian detection in traffic scenes using multi-attitude classifiers

    Brehar, Raluca / Nedevschi, Sergiu | IEEE | 2013


    Multi-Relational Pedestrian Trajectory Prediction in Complex Scenes

    Peng, Wenshuo / Cui, Zhoujuan / Duan, Yiping et al. | IEEE | 2022


    Understanding object relations in traffic scenes

    Hensel, Irina / Bachmann, Alexander / Hummel, Britta et al. | Tema Archiv | 2010