3 research outputs found

    Evaluation of Drivers’ Affectability and Satisfaction with Black Spots Warning Application

    Get PDF
    Since a significant percentage of crashes occur at black spots, different methods have been proposed to prioritize the modification of these spots and prevent crashes. One of these prevention methods in transportation is the hazard warning systems. The purpose of this study is to evaluate the satisfaction of drivers and their affectability from a map-based warning application is evaluated. To this end, black spots were identified on one of the two-way two-lane highways in the North-West of Iran and 32 male drivers were tested in the intervention group (warning state) and the control group (non-warning state). The evaluation of the warning application was done in two steps. In the first stage, drivers’ affectability between the two groups was compared, where average speed and number of speed limit violations were studied in warning and non-warning states. In the second stage, drivers' satisfaction with application features was examined using questionnaires. The findings showed that the difference in mean speeds at black spots between warning and non-warning states was significant with 95% confidence level and the use of warning application was effective in reducing the number of drivers with speed limit violations at black spots. Most drivers were highly content with the warning from car speakers, advisory warnings and warning distance from black spot, and did not have enough satisfaction with visual warnings, the application installation procedure, and warnings from smartphone speakers. Additionally, the results of the questionnaire revealed that not only warnings did not cause distraction for the drivers, they were effective in increasing their caution. These findings can be used to eliminate the shortcomings of the hazard warning application

    Improving Usefulness of Automated Driving by Lowering Primary Task Interference through HMI Design

    Get PDF

    Specificity and timing of advisory warnings based on cooperative perception

    No full text
    corecore