University of Tennessee at Chattanooga
Vehicular accident occurrence analysis and prediction
Abstract
dc:description.abstractVehicular accidents within Tennessee increased by 25% within 2009-2019 according to Tennessee’s Integrated Traffic Analysis Network. Accidents rank in the top three causes of accidental death across all ages in the U.S, and in 2017 accounted for 11.9% of all deaths by injury, the National Vital Statistics Report and Center for Health Statistics report. Accidents represent a massive cost in economics with 12.5 million in damages within 2018 from statistics from National Safety Council. These statistics indicate need for thorough investigation into reduction of accidents in our society. This thesis focuses on that need, with introduction of a novel predictive model based on historical accident occurrence in Hamilton County, Tennessee. The use of weather forecasts, roadway geometrics, and aggregated variables aids in creation of predictions for future accident occurrence. Additionally, an application is presented for use by local law enforcement and emergency services to assist resource deployment based upon predictions.
Degree
thesis:*- Grantor dc:publisher
- University of Tennessee at Chattanooga
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Way, Pete
- Contributors dc:contributor
-
- Sartipi, Mina
- Kandah, Farah; Ward, Michael
- College of Engineering and Computer Science
Subjects
dc:subject × 3Rights
dc:rights- Language dc:language
- English, eng
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholar.utc.edu/theses/659
- OAI identifier oai:identifier
- oai:scholar.utc.edu:theses-1827