Browsing by Author "Olson, Rebecca Lynn"

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    Assessment of a Drowsy Driver Warning System for Heavy Vehicle Drivers: Final Report
    Olson, Rebecca Lynn; Morgan, Justin F.; Hanowski, Richard J.; Daily, Brian; Zimmermann, Richard P.; Blanco, Myra; Bocanegra, Joseph L.; Fitch, Gregory M.; Flintsch, Alejandra Medina (United States. National Highway Traffic Safety Administration, 2008)
    Drowsiness has a globally negative impact on performance, slowing reaction time, decreasing situational awareness, and impairing judgment. A field operational test of an early prototype Drowsy Driver Warning System was conducted as a result of 12 years of field and laboratory studies by the National Highway Traffic Administration and the Federal Motor Carrier Safety Administration. This project included Control and Test groups. The final data set for the analysis consisted of 102 drivers from 3 for-hire trucking fleets using 46 instrumented trucks. Fifty-seven drivers were line-haul and 45 were long-haul operators. The data set contained nearly 12.4 terabytes of truck instrumentation data, kinematic data, and video recordings for 2.4 million miles of driving and 48,000 driving-data hours recorded, resulting in the largest data set ever collected by the U.S. Department of Transportation. In this study, 53 research questions were addressed related to safety benefits, acceptance, and deployment. Novel data reduction procedures and data analyses were used. Results showed that drivers in the Test Group were less drowsy. Drivers with favoring opinions of the system tended to have an increase in safety benefits. Results of the assessment revealed that the early prototype device had an overall positive impact on driver safety.
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    Assessment of Drowsy-Related Critical Incidents and the 2004 Revised Hours-of-Service Regulations
    Olson, Rebecca Lynn (Virginia Tech, 2006-12-08)
    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.
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    The Drowsy Driver Warning System Field Operational Test: Data Collection Methods: Final Report
    Hanowski, Richard J.; Blanco, Myra; Nakata, Akiko; Hickman, Jeffrey S.; Schaudt, William A.; Fumero, Maria C.; Olson, Rebecca Lynn; Jermeland, Julie; Greening, Michael; Holbrook, G. Thomas; Knipling, Ronald R.; Madison, Phillip (United States. National Highway Traffic Safety Administration, 2008-09)
    A Drowsy Driver Warning System (DDWS) detects physiological and/or performance indications of driver drowsiness and provides feedback to drivers regarding their state. The primary function of a DDWS is to provide information that will alert drivers to their drowsy state and motivate them to seek rest or take other corrective steps to increase alertness. The system tested in this study was the Driver Fatigue Monitor (DFM) developed by Attention Technologies, Inc., which estimates PERCLOS (percent eye closure). The primary goal of this field operational test (FOT) was to determine the safety benefits and operational capabilities, limitations, and characteristics of the DFM. The FOT was conducted in a naturalistic driving environment and data were collected from actual truck drivers driving commercial trucks. During the course of the study, 46 trucks were instrumented with a Data Acquisition System (DAS). Over 100 data variables such as the PERCLOS output from the DFM and driving performance data (e.g., lane position, speed, and longitudinal acceleration) were collected. Other collected measures included video, actigraphy, and questionnaires. The FOT had 103 drivers participate. Drivers were randomly assigned to either control (24 drivers) or experimental groups (79 drivers). The data collected include the following: approximately 46,000 driving-data hours; 397 load history files from 103 drivers; approximately 195,000 hours of activity/sleep data; questionnaires from all drivers; fleet management surveys from each company; and focus group results collected from 14 drivers during two post-study focus group sessions. The focus of this report is the description of the data collection procedures.
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    Fatigue analyses: from 16 months of naturalistic commercial motor vehicle driving data
    Wiegand, Douglas M.; Hanowski, Richard J.; Olson, Rebecca Lynn; Melvin, Whitney (National Surface Transportation Safety Center for Excellence, 2008-05-31)
    Under the sponsorship of the National Surface Transportation Safety Center for Excellence, an existing naturalistic data set from the Drowsy Driver Warning System Field Operational Test (DDWS FOT) was expanded and analyzed to gain a greater understanding of the conditions which are associated with fatigue in commercial motor vehicle (CMV) driving.
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    Field Evaluation of Alternative Automated Systems for Reducing Illegal Passing of School Buses, DTNH22-00-07007, Task Order 1
    Hanowski, Richard J.; Spaulding, Jeremy M.; Gaskins, Charla; Schaudt, William A.; Miller, Steven; Holbrook, G. Thomas; Olson, Rebecca Lynn; Dingus, Thomas A.; Hickman, Jeffrey S.; Huey, Richard; Llaneras, Eddy E. (Virginia Tech Transportation Institute, 2007-03-27)
    The overall objective of this research was to develop a prototype system that would automatically detect and record vehicles that illegally pass stopped school buses. There were four primary steps in meeting this objective: (1) determine the feasibility of developing and implementing a prototype system using advanced technology that would automatically document the identity of drivers and their vehicles that illegally pass stopped school buses; (2) if feasible, build a prototype unit; (3) design and conduct a proof-of-concept field test to determine system adequacy, including its accuracy and reliability; and (4) develop a set of recommendations for further development, research, and demonstration of the approach in an operational field setting. The objective of the second part of the research was to refine the initial system that had been developed in the first part.
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    The Impact of Driving, Non-driving Work, and Rest Breaks on Driving Performance in Commercial Vehicle Operations
    Blanco, Myra; Hanowski, Richard J.; Olson, Rebecca Lynn; Morgan, Justin F.; Soccolich, Susan A.; Wu, Shih-Ching (United States. Federal Motor Carrier Safety Administration, 2011-05)
    Current hours-of-service (HOS) regulations prescribe limits to commercial motor vehicle (CMV) drivers' operating hours. Besides assessing activities performed in the 14-hour workday, the relationship between safety-critical events (SCEs) and driving hours, work hours, and breaks was investigated. The data used in the analyses were collected in the Naturalistic Truck Driving Study and included 97 drivers and about 735,000 miles of continuous driving data. The assessment of the drivers' workday determined that, on average, drivers spent 66 percent of their shift driving, 23 percent in non-driving work, and 11 percent resting. Analyses on driving hours (i.e., driving only) and SCE risk found a time-on-task effect across hours. Analyses on work hours (i.e., driving in addition to non-driving work) found that risk of being involved in an SCE increased as work hours increased. This suggests that time-on-task effects may not be related to driving hours alone, but implies an interaction between driving hours and work hours: if a driver begins the day with several hours of non-driving work, followed by driving that goes deep into the 14- hour workday, SCE risk was found to increase. The finding from the workday characterization that drivers spent approximately 23 percent of their workday performing non-driving work provides a possible explanation for this time-on-task effect across work hours. Breaks from driving were found to be beneficial in reducing SCEs (during 1- hour window after a break) and were effective to counteract the negative effects of time-on-task.