{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/36393"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/36393","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Assessment of Drowsy-Related Critical Incidents and the 2004 Revised Hours-of-Service Regulations","abstract":"In 2004, 5,190 people were killed due to a traffic accident involving a commercial motor vehicle (CMV), up from 4,793 people killed in 2001 (Traffic Safety Facts, 2004; Traffic Safety Facts, 2001). Driver drowsiness is an important issue to consider when discussing CMVs. According to the FMCSA, over 750 people are killed and 20,000 people are injured each year due to drowsy CMV drivers (as cited in Advocates for Highway and Auto Safety, 2001). Driver drowsiness is an important issue for CMV drivers for several reasons, including long work shifts, irregular schedules and driving long hours on interstates and highways with no scenic interruptions to help keep the driver alert. Because of these and other factors, including the high mileage exposure that CMV drivers face, drowsiness is an important issue in a CMV driver's occupation. There were two main goals to this research: 1) gain a better understanding of the time-related occurrences of drowsy-related critical incidents (i.e., crashes, near-crashes and crash-relevant conflicts), and 2) obtain drivers' opinions of the 2004 Revised Hours-of-Service regulations. To do this, recent data were used from a Field Operational Test conducted by the Virginia Tech Transportation Institute in which 103 participants drove in an instrumented heavy vehicle for up to 16 weeks; video data, and sensor data were collected from each participant. In addition, actigraph data was collected from 96 of the 103 participants. Each vehicle was instrumented with four video cameras to capture images of the drivers face, the forward roadway, and the adjacent lanes on each side of the truck. In addition, multiple sensors were installed in the vehicle in order to collect data such as the driver's speed, braking patterns and steering wheel movement. These data were combined to provide a complete picture of each driver's environment and behavior while they drove their normal routes. Data analysts reviewed the data for critical incidents (crashes, near-crashes, and crash-relevant conflicts) and determined a drowsiness level for each incident; these downiness levels were compared to drowsiness levels of baseline incidents (i.e., normal driving periods). The results show that drivers were more likely to have a drowsy-related critical incident between 2:00 pm and 2:59 pm. In addition to the video and sensor data, each driver was asked to fill out a subjective questionnaire regarding the revised HOS regulations. Drivers preferred the revised HOS regulations over the old HOS regulations and the number one item that was preferred in the revised HOS regulations is the 34-hour restart which allows drivers to restart their work week by taking off 34 consecutive hours.","abstract_html":"In 2004, 5,190 people were killed due to a traffic accident involving a commercial motor vehicle (CMV), up from 4,793 people killed in 2001 (Traffic Safety Facts, 2004; Traffic Safety Facts, 2001). Driver drowsiness is an important issue to consider when discussing CMVs. According to the FMCSA, over 750 people are killed and 20,000 people are injured each year due to drowsy CMV drivers (as cited in Advocates for Highway and Auto Safety, 2001). Driver drowsiness is an important issue for CMV drivers for several reasons, including long work shifts, irregular schedules and driving long hours on interstates and highways with no scenic interruptions to help keep the driver alert. Because of these and other factors, including the high mileage exposure that CMV drivers face, drowsiness is an important issue in a CMV driver's occupation. There were two main goals to this research: 1) gain a better understanding of the time-related occurrences of drowsy-related critical incidents (i.e., crashes, near-crashes and crash-relevant conflicts), and 2) obtain drivers' opinions of the 2004 Revised Hours-of-Service regulations. To do this, recent data were used from a Field Operational Test conducted by the Virginia Tech Transportation Institute in which 103 participants drove in an instrumented heavy vehicle for up to 16 weeks; video data, and sensor data were collected from each participant. In addition, actigraph data was collected from 96 of the 103 participants. Each vehicle was instrumented with four video cameras to capture images of the drivers face, the forward roadway, and the adjacent lanes on each side of the truck. In addition, multiple sensors were installed in the vehicle in order to collect data such as the driver's speed, braking patterns and steering wheel movement. These data were combined to provide a complete picture of each driver's environment and behavior while they drove their normal routes. Data analysts reviewed the data for critical incidents (crashes, near-crashes, and crash-relevant conflicts) and determined a drowsiness level for each incident; these downiness levels were compared to drowsiness levels of baseline incidents (i.e., normal driving periods). The results show that drivers were more likely to have a drowsy-related critical incident between 2:00 pm and 2:59 pm. In addition to the video and sensor data, each driver was asked to fill out a subjective questionnaire regarding the revised HOS regulations. Drivers preferred the revised HOS regulations over the old HOS regulations and the number one item that was preferred in the revised HOS regulations is the 34-hour restart which allows drivers to restart their work week by taking off 34 consecutive hours.","abstract_has_math":false,"creators":["Olson, Rebecca Lynn"],"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":["Kleiner, Brian M."],"year":2006,"date_issued":"2006-12-08","date_published":"2006-12-08","updated_at":"2026-07-22T22:19:15Z","subjects":["critical incidents","hours of service","crashes","drowsiness","Fatigue","commercial motor vehicles"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-12222006-123604"],"render_values":[{"text":"etd-12222006-123604","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/36393","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":["Kleiner, Brian M."]},{"key":"dc:contributor.department","label":"Department","values":["Industrial and Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Olson, Rebecca Lynn"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T20:50:38Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T20:50:38Z","2007-01-15"]},{"key":"dc:date.issued","label":"Date","values":["2006-12-08"]},{"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":["critical incidents","hours of service","crashes","drowsiness","Fatigue","commercial motor vehicles"]}]},{"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":["etd-12222006-123604"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/36393"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In 2004, 5,190 people were killed due to a traffic accident involving a commercial motor vehicle (CMV), up from 4,793 people killed in 2001 (Traffic Safety Facts, 2004; Traffic Safety Facts, 2001). Driver drowsiness is an important issue to consider when discussing CMVs. According to the FMCSA, over 750 people are killed and 20,000 people are injured each year due to drowsy CMV drivers (as cited in Advocates for Highway and Auto Safety, 2001). Driver drowsiness is an important issue for CMV drivers for several reasons, including long work shifts, irregular schedules and driving long hours on interstates and highways with no scenic interruptions to help keep the driver alert. Because of these and other factors, including the high mileage exposure that CMV drivers face, drowsiness is an important issue in a CMV driver's occupation. There were two main goals to this research: 1) gain a better understanding of the time-related occurrences of drowsy-related critical incidents (i.e., crashes, near-crashes and crash-relevant conflicts), and 2) obtain drivers' opinions of the 2004 Revised Hours-of-Service regulations. To do this, recent data were used from a Field Operational Test conducted by the Virginia Tech Transportation Institute in which 103 participants drove in an instrumented heavy vehicle for up to 16 weeks; video data, and sensor data were collected from each participant. In addition, actigraph data was collected from 96 of the 103 participants. Each vehicle was instrumented with four video cameras to capture images of the drivers face, the forward roadway, and the adjacent lanes on each side of the truck. In addition, multiple sensors were installed in the vehicle in order to collect data such as the driver's speed, braking patterns and steering wheel movement. These data were combined to provide a complete picture of each driver's environment and behavior while they drove their normal routes. Data analysts reviewed the data for critical incidents (crashes, near-crashes, and crash-relevant conflicts) and determined a drowsiness level for each incident; these downiness levels were compared to drowsiness levels of baseline incidents (i.e., normal driving periods). The results show that drivers were more likely to have a drowsy-related critical incident between 2:00 pm and 2:59 pm. In addition to the video and sensor data, each driver was asked to fill out a subjective questionnaire regarding the revised HOS regulations. Drivers preferred the revised HOS regulations over the old HOS regulations and the number one item that was preferred in the revised HOS regulations is the 34-hour restart which allows drivers to restart their work week by taking off 34 consecutive hours."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Assessment of Drowsy-Related Critical Incidents and the 2004 Revised Hours-of-Service Regulations"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Smith-Jackson, Tonya L.","Hanowski, Richard J."],"dc:contributor.committeemember":["Kleiner, Brian M."],"dc:contributor.department":["Industrial and Systems Engineering"],"dc:creator":["Olson, Rebecca Lynn"],"dc:date.accessioned":["2014-03-14T20:50:38Z"],"dc:date.available":["2014-03-14T20:50:38Z","2007-01-15"],"dc:date.issued":["2006-12-08"],"dc:description.abstract":["In 2004, 5,190 people were killed due to a traffic accident involving a commercial motor vehicle (CMV), up from 4,793 people killed in 2001 (Traffic Safety Facts, 2004; Traffic Safety Facts, 2001). Driver drowsiness is an important issue to consider when discussing CMVs. According to the FMCSA, over 750 people are killed and 20,000 people are injured each year due to drowsy CMV drivers (as cited in Advocates for Highway and Auto Safety, 2001). Driver drowsiness is an important issue for CMV drivers for several reasons, including long work shifts, irregular schedules and driving long hours on interstates and highways with no scenic interruptions to help keep the driver alert. Because of these and other factors, including the high mileage exposure that CMV drivers face, drowsiness is an important issue in a CMV driver's occupation. There were two main goals to this research: 1) gain a better understanding of the time-related occurrences of drowsy-related critical incidents (i.e., crashes, near-crashes and crash-relevant conflicts), and 2) obtain drivers' opinions of the 2004 Revised Hours-of-Service regulations. To do this, recent data were used from a Field Operational Test conducted by the Virginia Tech Transportation Institute in which 103 participants drove in an instrumented heavy vehicle for up to 16 weeks; video data, and sensor data were collected from each participant. In addition, actigraph data was collected from 96 of the 103 participants. Each vehicle was instrumented with four video cameras to capture images of the drivers face, the forward roadway, and the adjacent lanes on each side of the truck. In addition, multiple sensors were installed in the vehicle in order to collect data such as the driver's speed, braking patterns and steering wheel movement. These data were combined to provide a complete picture of each driver's environment and behavior while they drove their normal routes. Data analysts reviewed the data for critical incidents (crashes, near-crashes, and crash-relevant conflicts) and determined a drowsiness level for each incident; these downiness levels were compared to drowsiness levels of baseline incidents (i.e., normal driving periods). The results show that drivers were more likely to have a drowsy-related critical incident between 2:00 pm and 2:59 pm. In addition to the video and sensor data, each driver was asked to fill out a subjective questionnaire regarding the revised HOS regulations. Drivers preferred the revised HOS regulations over the old HOS regulations and the number one item that was preferred in the revised HOS regulations is the 34-hour restart which allows drivers to restart their work week by taking off 34 consecutive hours."],"dc:description.degree":["Master of Science"],"dc:identifier.other":["etd-12222006-123604"],"dc:identifier.uri":["http://hdl.handle.net/10919/36393"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["critical incidents","hours of service","crashes","drowsiness","Fatigue","commercial motor vehicles"],"dc:title":["Assessment of Drowsy-Related Critical Incidents and the 2004 Revised Hours-of-Service Regulations"],"dc:type":["Thesis"],"thesis:degree_discipline":["Industrial and Systems Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:15Z"}