Driving scene understanding is to obtain compre-hensive scene information through the sensor data and provide a basis for downstream tasks, which is indispensable for the safety of self-driving vehicles. Specific perception tasks, such as object detection and scene graph generation, are commonly used. However, the results of these tasks are only equivalent to the characterization of sampling from high-dimensional scene features, which are not sufficient to represent the scenario. In addition, the goal of perception tasks is inconsistent with human driving that just focuses on what may affect the ego-trajectory. Therefore, we propose an end-to-end Interpretable Implicit Driving Scene Understanding (II-DSU) model to extract implicit high-dimensional scene features as scene understanding results guided by a planning module and to validate the plausibility of scene understanding using auxiliary perception tasks for visualization. Experimental results on CARLA benchmarks show that our approach achieves the new state-of-the-art and is able to obtain scene features that embody richer scene information relevant to driving, enabling superior performance of the downstream planning.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Interpretable End-to-End Driving Model for Implicit Scene Understanding


    Beteiligte:
    Sun, Yiyang (Autor:in) / Wang, Xiaonian (Autor:in) / Zhang, Yangyang (Autor:in) / Tang, Jiagui (Autor:in) / Tang, Xiaqiang (Autor:in) / Yao, Jing (Autor:in)


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    588034 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    DRIVING SCENE UNDERSTANDING

    DING SHUGUANG / JIN YUEXIANG / FAN MINGYU et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Auditory Scene Understanding for Autonomous Driving

    Furletov, Yury / Willert, Volker / Adamy, Jurgen | IEEE | 2021


    Online Resident Space-Object Shape Modeling through Implicit Scene Understanding

    Heintz, Aneesh / Peck, Mason A. / Sun, Fangchen et al. | AIAA | 2021


    ONLINE RESIDENT SPACE-OBJECT SHAPE MODELING THROUGH IMPLICIT SCENE UNDERSTANDING

    Heintz, Aneesh / Peck, Mason A. / Sun, Fangchen et al. | TIBKAT | 2021


    Online Shape Modeling of Resident Space Objects Through Implicit Scene Understanding

    Heintz, Aneesh M. / Peck, Mason / Sun, Fangchen et al. | AIAA | 2021