Frontal Pre-Collision Systems (PCS) and Lane Departure Warning (LDW) systems are two of the first active safety systems to penetrate the passenger vehicle market. PCS can warn the driver, amplify the driver's braking effort, and autonomously brake even if there is no driver input. LDW systems deliver a warning to the driver when the vehicle is drifting out of its lane. The potential effectiveness of these two systems in the field not only depends on the crash scenarios they are likely to activate in but also on driver behavior. This study utilized the National Motor Vehicle Crash Causation Survey (NMVCCS), which unlike traditional databases focuses on behavioral aspects that lead to a collision. The target populations for PCS and LDW were found by aggregating crashes that had a) crash scenarios and b) critical reasons attributed to the collisions that were most likely mitigated by the systems. The warning component of PCS was found to be potentially effective in 45% of applicable crash scenarios. The brake assist and autonomous braking components were potentially effective in 71% and 74% of collisions, respectively. LDW was potentially effective in 18% of road departure collisions. These target populations are not estimates of actual system effectiveness but are quantification of the specific crash and driver scenarios most likely to be mitigated by LDW and PCS.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Identification of target populations for current active safety systems using driver behavior


    Beteiligte:


    Erscheinungsdatum :

    2012-06-01


    Format / Umfang :

    253451 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Identification of Target Populations for Current Active Safety Systems Using Driver Behavior

    Kusano, K. / Gabler, H.C. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2012


    Driver behavior modeling using hybrid dynamic systems for driver-aware active vehicle safety

    Boyraz,P. / Sathyanarayana,A. / Hansen,J.H. et al. | Kraftfahrwesen | 2009


    Driver Identification Using Driving Behavior, Habits and Driver Characteristics

    Bani Milhim, Alaeddin / CHIM, Huong / Jalaliyazdi, Milad et al. | SAE Technical Papers | 2021


    Driver Identification Using Driving Behavior, Habits and Driver Characteristics

    Jalaliyazdi, Milad / Sheikh, Tooba / Bani Milhim, Alaeddin et al. | British Library Conference Proceedings | 2021


    Current trends in vehicle active safety and driver assistance development

    Giebel,T. / Meinecke,M.M. / Gonter,M. et al. | Kraftfahrwesen | 2008