United States Department of Transportation
i
Traffic safety measures using multiple streams real time data : final report
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2017-01-04
[PDF-1.23 MB]
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Abstract:Traffic crashes and accidents result from many complex factors, but at a basic level, they are conflicts
among vehicles and/or other road users. Roadway conditions, traffic signals, weather, traffic flow,
drivers' behavior and health of vehicles on roadways are among significant factors that influence these
conflicts. With the enormous advances in connected vehicles technology, the Internet of Things (IOT)
and smart cars, the opportunities for more advanced safety techniques that are proactive and
customizable to individual drivers are becoming more realizable. The main objective of this project is
to build advanced analytics to estimate a composite traffic safety risk measure that change temporally
and spatially, and take into account driver behavior, roadway quality conditions and historical safety
characteristics of roadways. Our vision is that with smart cars and smart roadways, a travel plan for a
given driver will be associated with a safety risk profile composed of these risk estimates that are
sampled in time and change whenever one or more of the underlying data streams change. This project
will focus more on the development of such a methodology and less on how it should be implemented
and calibrated for different applications
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