The riskiness of the roadway environment needs to be known in advance to improve driving safety. Such knowledge brings strong benefit to drivers and could be used to reduce the risk of collision. For example, vehicles can support a driver with guidance before arriving at the risky zones. In this paper, we focus on this use case. We propose risk avoidance by Vehicular Knowledge Networking (VKN). The proposed method mines the maneuver conflicts to determine risky zones. According to identified zones, guidance (e.g., speed and lane change suggestions) is shared with vehicles to help drivers pass these risky regions smoothly. Extensive simulations in different settings have shown that risk avoidance by VKN could decrease the collision risk by approximately 50%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Risk Avoidance by Vehicular Knowledge Networking


    Contributors:


    Publication date :

    2022-06-01


    Size :

    372745 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    VEHICULAR KNOWLEDGE NETWORKING ASSISTED ADAS CONFIGURATION

    UCAR SYEHAN / HIGUCHI TAKAMASA / ALTINTAS ONUR et al. | European Patent Office | 2023

    Free access

    VEHICULAR KNOWLEDGE NETWORKING ASSISTED ADAS CONFIGURATION

    UCAR SEYHAN / HIGUCHI TAKAMASA / ALTINTAS ONUR et al. | European Patent Office | 2024

    Free access

    VEHICULAR KNOWLEDGE NETWORKING ASSISTED ADAS CONFIGURATION

    UCAR SEYHAN / HIGUCHI TAKAMASA / ALTINTAS ONUR et al. | European Patent Office | 2023

    Free access

    Vehicular networking

    Sommer, Christoph / Dressler, Falko | TIBKAT | 2015


    Vehicular networking

    Sommer, Christoph / Dressler, Falko | SLUB | 2014