Honors College Theses

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Browsing Honors College Theses by Author "Ali, Arsha"

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    Evaluation of Common Secondary Tasks in Highly Automated Vehicles
    Ali, Arsha; Rawashdeh, Osamah
    In highly automated vehicles, a driver is required to takeover control from the automated system and manually drive in the event of a situation automation cannot handle. Until autonomy is perfected, a driver’s input is mission critical. However, it is possible the driver became occupied with an alternate, non-driving related task and no longer has the proper situational awareness to safely takeover driving before automation is disengaged. The purpose of this study is to understand how common non-driving related tasks affect a driver’s takeover performance. The results of a questionnaire are being used to determine prevalent non-driving related tasks that are common among drivers today and projected to be engaged in as vehicle automation progresses. Although previous studies have incorporated non-driving related tasks, there is a paucity in comparative studies that have investigated more than one task under the same conditions. Most recent autonomous vehicle takeover research has concentrated primarily on the takeover response time for single tasks, or focused on takeover modality (e.g., visual, auditory, haptic). In this project, the comparison of non-driving related tasks by response time and performance are being evaluated. The time that participants take to takeover vehicle control after a takeover request is initiated is being analyzed under a non-scheduled system initiated handover with a fixed time-to-collision of 6 seconds. For this experiment, a customized driving simulator was constructed and a simulated driving scenario was meticulously designed. This study is based on the premise that longer takeover response times are indicative of low situational awareness. The pilot study results show that a fast takeover time does not mean safer driving behavior. Identifying how users respond to takeover requests when previously engaged in different non-driving related tasks will assist designers in constructing vehicle takeovers that are likely to be successful.