Forecasting the burden of road traffic injuries: a scenario including fully-autonomous vehicles

dc.contributor.advisorMurray, Christopher
dc.contributor.authorReidy, Patrick Edward
dc.date.accessioned2017-10-26T20:45:09Z
dc.date.available2017-10-26T20:45:09Z
dc.date.issued2017-10-26
dc.date.submitted2017-08
dc.descriptionThesis (Master's)--University of Washington, 2017-08
dc.description.abstractRoad traffic injuries are one of the largest causes of death for teenagers and adults in the United States. Fully autonomous vehicles (FAV) have the potential to impact not only the transportation industry, but also the population health of the United States by decreasing road traffic fatalities. We forecasted a lower bound of the burden of road traffic fatalities by estimating the decrease in drunk driving fatalities. Comparing scenarios with FAV adoption and baseline scenarios of no FAV adoption, results show that modest adoption of FAVs could prevent around 6,000 drunk driving deaths per year by 2040. This work highlights the current burden of road traffic injuries and how new technology could partly alleviate that burden.
dc.embargo.termsOpen Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherReidy_washington_0250O_17797.pdf
dc.identifier.urihttp://hdl.handle.net/1773/40418
dc.language.isoen_US
dc.rightsnone
dc.subjectForecasting
dc.subjectFully Autonomous Vehicles
dc.subjectGlobal Burden of Disease
dc.subjectPublic health
dc.subject.otherGlobal Health
dc.titleForecasting the burden of road traffic injuries: a scenario including fully-autonomous vehicles
dc.typeThesis

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