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Intersection Decision Support: Evaluation of a Violation Warning System to Mitigate Straight Crossing Path Collisions
Neale, Vicki L.
Perez, Miguel A.
Doerzaph, Zachary R.
Lee, Suzanne E.
Dingus, Thomas A.
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This project entailed the design, development, testing, and evaluation of intersection decision support (IDS) systems to address straight crossing path (SCP) intersection crashes. This type of intersection crash is responsible for more than 100,000 crashes and thousands of fatalities each year. In developing these IDS systems for both signalized and stop-controlled intersections, a top-down systems approach was used that determined the necessary system functions and evaluated the capability of different technologies to perform those functions. Human factors tests were also conducted that evaluated the effectiveness of warning algorithms and infrastructure-based driver-infrastructure interfaces in eliciting a stopping response from drivers about to be involved in an SCP intersection crash. Results indicated that further technological development is needed for the sensing and intersection state IDS functions. Furthermore, infrastructure-based warning interfaces tested were greatly outperformed by previously-tested in-vehicle warnings. Thus, future research on IDS systems should focus on their infrastructure-cooperative configuration, where the system supports an in-vehicle warning.