The goal of this study is to provide a framework, using hidden semi-Markov models, for modeling a driver’s response time after an alert is provided in manual driving. Given the plethora of alerts and warning within a vehicle, there is a need to understand when a driver will respond after an alert is provided. Data from a previous driving simulator study, where drivers were interacting with an in-vehicle information system (IVIS) were used for model training. The final data set included 16 participants, with 288 task initiations. The proposed model could predict a driver’s response time accurately using only a small portion of the available data, and had a mean absolute error of 0.51 seconds with 84% of predictions within an absolute error of 1 second. This framework has applicability in mitigating the risk of transitions in driver distraction. This includes transitions from the road to the secondary task and back to the road.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Predicting Driver’s Transition Time to a Secondary Task Given an in-Vehicle Alert


    Contributors:


    Publication date :

    2022-05-01


    Size :

    1580903 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    METHOD OF VEHICLE DRIVER'S ALERT AND VEHICLE

    GROH ALEXANDER / NORTON ALAN / FELDMAN CASEY BRYAN et al. | European Patent Office | 2019

    Free access

    Forward-looking radar signals alert via driver's phone

    HALEY JEFFREY T | European Patent Office | 2019

    Free access

    Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

    Tilbury, Dawn / Robert, Lionel / Petersen, Luke et al. | SAE Technical Papers | 2019


    The tracter driver's steering control task

    Bottoms, D.J. | Tema Archive | 1982


    Vehicle driver's seat structure

    JEONG SEUNG MIN / NOH SEUNG HO | European Patent Office | 2024

    Free access