{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/47599"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/47599","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Crash Risk and Mobile Device Use Based on Fatigue and Drowsiness Factors in Truck Drivers","abstract":"Driver distraction has become a major concern for the U.S. Department of Transportation (US DOT). Performance decrements are typically the result of driver distraction because attentional resources are limited, which are limited; fatigue and drowsiness limit attentional resources further. The purpose of the current research is to gain an understanding of the relationship between mobile device use (MDU), fatigue, through driving time and time on duty, and drowsiness, through time of day and amount of sleep, for commercial motor vehicle drivers. A re-analysis of naturalistic driving data was used to obtain information about the factors, MDU, safety-critical events (SCE), and normal driving epochs. Odds ratios were used to calculate SCE risk for 6 mobile device use subtasks and each of the factors, which were divided into smaller bins of hours for more specific information. A generalized linear mixed model and chi-square test were used to assess MDU for each factor and the associated bins. Results indicated visually demanding subtasks were associated with an increase in SCE risk, but conversation on a hands-free cell phone decreased SCE risk. There was an increase in SCE risk for visual manual subtasks for all bins in which analyses were possible. Drivers had a higher proportion of MDU in the early morning (circadian low period) than all other times of day that were analyzed. These results will be used to create recommended training and evaluate policy and technology and will help explain the relationship between MDU, fatigue, and drowsiness.","abstract_html":"Driver distraction has become a major concern for the U.S. Department of Transportation (US DOT). Performance decrements are typically the result of driver distraction because attentional resources are limited, which are limited; fatigue and drowsiness limit attentional resources further. The purpose of the current research is to gain an understanding of the relationship between mobile device use (MDU), fatigue, through driving time and time on duty, and drowsiness, through time of day and amount of sleep, for commercial motor vehicle drivers. A re-analysis of naturalistic driving data was used to obtain information about the factors, MDU, safety-critical events (SCE), and normal driving epochs. Odds ratios were used to calculate SCE risk for 6 mobile device use subtasks and each of the factors, which were divided into smaller bins of hours for more specific information. A generalized linear mixed model and chi-square test were used to assess MDU for each factor and the associated bins. Results indicated visually demanding subtasks were associated with an increase in SCE risk, but conversation on a hands-free cell phone decreased SCE risk. There was an increase in SCE risk for visual manual subtasks for all bins in which analyses were possible. Drivers had a higher proportion of MDU in the early morning (circadian low period) than all other times of day that were analyzed. These results will be used to create recommended training and evaluate policy and technology and will help explain the relationship between MDU, fatigue, and drowsiness.","abstract_has_math":false,"creators":["Toole, Laura"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Industrial and Systems Engineering","degree_department":"Industrial and Systems Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Smith-Jackson, Tonya L.","Hanowski, Richard J."],"committee_members":["Winchester, Woodrow W."],"year":2013,"date_issued":"2013-01-07","date_published":"2013-01-07","updated_at":"2026-07-22T22:20:05Z","subjects":["Commercial motor vehicles","Fatigue","drowsiness","distraction","Naturalistic Truck Driving Study"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:56"],"render_values":[{"text":"vt_gsexam:56","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/47599","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Smith-Jackson, Tonya L.","Hanowski, Richard J."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Winchester, Woodrow W."]},{"key":"dc:contributor.department","label":"Department","values":["Industrial and Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Toole, Laura"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-04-23T21:57:47Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-04-23T21:57:47Z"]},{"key":"dc:date.issued","label":"Date","values":["2013-01-07"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial and Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Commercial motor vehicles","Fatigue","drowsiness","distraction","Naturalistic Truck Driving Study"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:56"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/47599"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Driver distraction has become a major concern for the U.S. Department of Transportation (US DOT). Performance decrements are typically the result of driver distraction because attentional resources are limited, which are limited; fatigue and drowsiness limit attentional resources further. The purpose of the current research is to gain an understanding of the relationship between mobile device use (MDU), fatigue, through driving time and time on duty, and drowsiness, through time of day and amount of sleep, for commercial motor vehicle drivers. A re-analysis of naturalistic driving data was used to obtain information about the factors, MDU, safety-critical events (SCE), and normal driving epochs. Odds ratios were used to calculate SCE risk for 6 mobile device use subtasks and each of the factors, which were divided into smaller bins of hours for more specific information. A generalized linear mixed model and chi-square test were used to assess MDU for each factor and the associated bins. Results indicated visually demanding subtasks were associated with an increase in SCE risk, but conversation on a hands-free cell phone decreased SCE risk. There was an increase in SCE risk for visual manual subtasks for all bins in which analyses were possible. Drivers had a higher proportion of MDU in the early morning (circadian low period) than all other times of day that were analyzed. These results will be used to create recommended training and evaluate policy and technology and will help explain the relationship between MDU, fatigue, and drowsiness."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Crash Risk and Mobile Device Use Based on Fatigue and Drowsiness Factors in Truck Drivers"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Smith-Jackson, Tonya L.","Hanowski, Richard J."],"dc:contributor.committeemember":["Winchester, Woodrow W."],"dc:contributor.department":["Industrial and Systems Engineering"],"dc:creator":["Toole, Laura"],"dc:date.accessioned":["2014-04-23T21:57:47Z"],"dc:date.available":["2014-04-23T21:57:47Z"],"dc:date.issued":["2013-01-07"],"dc:description.abstract":["Driver distraction has become a major concern for the U.S. Department of Transportation (US DOT). Performance decrements are typically the result of driver distraction because attentional resources are limited, which are limited; fatigue and drowsiness limit attentional resources further. The purpose of the current research is to gain an understanding of the relationship between mobile device use (MDU), fatigue, through driving time and time on duty, and drowsiness, through time of day and amount of sleep, for commercial motor vehicle drivers. A re-analysis of naturalistic driving data was used to obtain information about the factors, MDU, safety-critical events (SCE), and normal driving epochs. Odds ratios were used to calculate SCE risk for 6 mobile device use subtasks and each of the factors, which were divided into smaller bins of hours for more specific information. A generalized linear mixed model and chi-square test were used to assess MDU for each factor and the associated bins. Results indicated visually demanding subtasks were associated with an increase in SCE risk, but conversation on a hands-free cell phone decreased SCE risk. There was an increase in SCE risk for visual manual subtasks for all bins in which analyses were possible. Drivers had a higher proportion of MDU in the early morning (circadian low period) than all other times of day that were analyzed. 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