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Using Safety Performance Models, Autonomous Vehicle Data, And Machine Learning To Develop Contextual Complexity Criteria To Establish A Standardized Process For On-Road Evaluation Of Medically At-Risk Drivers Considering Static And Dynamic Factors Of The Roadway Environment, Vijay Bendigeri

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The field of transportation engineering has an opportunity to positively impact the medical community, specifically the clinicians who evaluate, train, and rehabilitate at-risk drivers. Driving Rehabilitation Specialists (DRSs) have an essential role in making roads safer for medically-at-risk drivers, their passengers, and other road users. DRSs conduct on-road driving evaluations, which are considered the gold standard to make fitness-to-drive decisions due to their high face validity. Most DRSs use a fixed route, meaning the exact same route is used to evaluate each client. When a DRS develops a fixed route, that clinician identifies characteristics of the roadway they think are …