Connected and Automated Vehicle Based Intersection Maneuver Assist Systems (CAVIMAS) - Reduced Eye-tracking Data + Survey Data

<p>Background:</p>

<p>Intersection crashes can be potentially mitigated by leveraging deployments of vehicle-to-infrastructure (V2I) and vehicle-to- vehicle (V2V) safety management solutions. However, it is equally critical that these deployments are undertaken in tandem with interventions based on human factors evidence relating to the content and presentation of such solutions. This driving simulator study designed and evaluated a conceptual system - Connected and Automated Vehicle based Intersection Maneuver Assist Systems (CAVIMAS) - aimed at assisting drivers with intersection maneuvers by leveraging connected infrastructure and providing real-time guidance and warnings and active vehicle controls.</p>

<p>Dataset:</p>

<p>A flatfile that contains deidentified data from human participants from the driving simulator study.  Data available for each participant and contains variables for system type, workload score, survey items, and eye movement coding of driver visual gaze at intersections. </p>

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