Interaction research has been initially focusing on partially and conditionally automated vehicles. Augmented Reality (AR) may provide a promising way to enhance drivers' experience when using autonomous driving (AD) systems. This study sought to gain insights on drivers' subjective assessment of a simulated driving automation system with AR-based support. A driving simulator study was conducted and participants' rating of the AD system in terms of information imparting, nervousness and trust was collected. Cumulative Link Models (CLMs) were developed to investigate the impacts of AR cues, traffic density and intersection complexity on drivers' attitudes towards the presented AD system. Random effects were incorporated in the CLMs to account for the heterogeneity among participants. Results indicated that AR graphic cues could significantly improve drivers' experience by providing advice for their decision-making and mitigating their anxiety and stress. However, the magnitude of AR's effect was impacted by traffic conditions (i.e. diminished at more complex intersections). The study also revealed a strong correlation between self-rated trust and takeover frequency, suggesting takeover and other driving behavior need to be further examined in future studies.


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    Title :

    Drivers' Attitudes and Perceptions towards A Driving Automation System with Augmented Reality Human-Machine Interfaces


    Contributors:


    Publication date :

    2020-10-19


    Size :

    847399 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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