{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1827"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1827","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Vehicular accident occurrence analysis and prediction","abstract":"Vehicular 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.","abstract_html":"Vehicular 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.","abstract_has_math":false,"creators":["Way, Pete"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Sartipi, Mina","Kandah, Farah; Ward, Michael","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:46:59Z","subjects":["Engineering mathematics","Traffic accidents","Traffic accident investigation"],"languages":["English","eng"],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/659","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sartipi, Mina","Kandah, Farah; Ward, Michael","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Way, Pete"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:coverage","label":"Dc Coverage","values":["Hamilton County (Tenn.)"]},{"key":"dc:date","label":"Dc Date","values":["2020-05-01T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering mathematics","Traffic accidents","Traffic accident investigation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/659"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computer Science and Engineering","M. 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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."]},{"key":"dc:title","label":"Title","values":["Vehicular accident occurrence analysis and prediction"]}]}],"canonical_facts":{"dc:contributor":["Sartipi, Mina","Kandah, Farah; Ward, Michael","College of Engineering and Computer Science"],"dc:coverage":["Hamilton County (Tenn.)"],"dc:creator":["Way, Pete"],"dc:date":["2020-05-01T07:00:00Z"],"dc:description":["Dept. of Computer Science and Engineering","M. 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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."],"dc:identifier":["https://scholar.utc.edu/theses/659"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Engineering mathematics","Traffic accidents","Traffic accident investigation"],"dc:title":["Vehicular accident occurrence analysis and prediction"],"dc:type":["Masters theses","Text"]},"updated_at":"2026-07-24T05:46:59Z"}