Browsing by Author "Blanco, Myra"

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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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    Automated Vehicle Crash Rate Comparison Using Naturalistic Data
    Blanco, Myra; Atwood, Jon; Russell, Sheldon M.; Trimble, Tammy E.; McClafferty, Julie A.; Perez, Miguel A. (Virginia Tech Transportation Institute, 2016-01-08)
    This study assessed driving risk for the United States nationally and for the Google Self-Driving Car project. Driving safety on public roads was examined in three ways. The total crash rates for the Self-Driving Car and the national population were compared to (1) rates reported to the police, (2) crash rates for different types of roadways, and (3) scenarios that give rise to unreported crashes. First, crash rates from the Google Self-Driving Car project per million miles driven, broken down by severity level were calculated. The Self-Driving Car rates were compared to rates developed using national databases which draw upon police-reported crashes and rates estimated from the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study (NDS). Second, SHRP 2 NDS data were used to calculate crash rates for three levels of crash severity on different types of roads, broken down by the speed limit and geographic classification (termed “locality” in the study; e.g., urban road, interstate). Third, SHRP 2 NDS data were again used to describe various scenarios related to crashes with no known police report. This analysis considered whether such factors as driver distraction or impairment were involved, or whether these crashes involved rear-end collisions or road departures. Crashes within the SHRP 2 NDS dataset were ranked according to severity for the referenced event/incident type(s) based on the magnitude of vehicle dynamics (e.g., high Delta-V or acceleration), the presumed amount of property damage (less than or greater than $1,500, airbag deployment), knowledge of human injuries (often unknown in this dataset), and the level of risk posed to the drivers and other road users (Antin, et al., 2015; Table 1). Google Self-Driving Car crashes were also analyzed using the methods developed for the SHRP 2 NDS in order to determine crash severity levels and fault (using these methods, none of the vehicles operating in autonomous mode were deemed at fault in crashes).
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    CMV Driver Health Outreach
    Trimble, Tammy E.; Morgan, Justin F.; Hanowski, Richard J.; Blanco, Myra (National Surface Transportation Safety Center for Excellence, 2013-10)
    Many commercial motor vehicle (CMV) drivers struggle to maintain a healthy lifestyle against the demands of their job. While some previous CMV health programs have been developed, these programs have either not been widely implemented or they fail to adequately address the needs of CMV drivers with programs adaptable to their unique lifestyle challenges. Additionally, reaching this highly fragmented and mobile population has proven difficult. This report describes the development of an integrated social networking-based health effort, called Driving Healthy. The main objective of Driving Healthy was to create a unique health and wellness resource for the CMV community that provides trusted information about a variety of health topics in an easy-to-access fashion, as well as timely updates via social networking platforms. Specific objectives included the development and enhancement of the Driving Healthy website and the social networking platforms that complement the website. In doing so, additional driver-focused health information was produced, along with new outreach tools and materials and expanded connectivity options for this outreach effort. This report documents two project phases. Phase I of the project spanned the period of January 1, 2010, through July 31, 2011, with the sites being launched in January 2011. Phase II covers August 1, 2011, through November 15, 2012, and included the development of additional outreach tools.
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    Commercial Motor Vehicle Driving Safety Website
    Tidwell, Scott; Trimble, Tammy E.; Blanco, Myra (National Surface Transportation Safety Center for Excellence, 2016-08-06)
    This report documents the CMV Driving Safety website (http://cmvdrivingsafety.org/), which was created by the National Surface Transportation Safety Center for Excellence (NSTSCE) as an outreach effort to assist commercial motor vehicle (CMV) fleets and drivers, driver trainers, CMV training schools, and insurance companies. The website contains 15 unique pages and provides six downloadable training modules on driver distraction, driver health, hours of service, driver drowsiness and fatigue, sharing the road, and safety systems. In addition to profiling the website, the report provides statistics on site visits and the number of times the training modules have been downloaded.
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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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    Effects of a Driver Monitoring System on Driver Trust, Satisfaction, and Performance with an Automated Driving System
    Vasquez, Holland Marie (Virginia Tech, 2016-01-27)
    This study was performed with the goal of delineating how drivers' interactions with an Automated Driving System were affected by a Driver Monitoring System (DMS), which provided alerts to the driver when he or she became inattentive to the driving environment. There were two specific research questions. The first was centered on addressing how drivers' trust and satisfaction with an Automated Driving System was affected by a DMS. The second was centered on addressing how drivers' abilities to detect changes in the driving environment that required intervention were affected by the presence of a DMS. Data were collected from fifty-six drivers during a test-track experiment with an Automated Driving System prototype that was equipped with a DMS. DMS attention prompt conditions were treated as the independent variable and trust, satisfaction, and driver performance during the experimenter triggered lane drifts were treated as dependent variables. The findings of this investigation suggested that drivers who receive attention prompts from a DMS have lower levels of trust and satisfaction with the Automated Driving System compared to drivers who do not receive attention prompts from a DMS. While the DMS may result in lower levels of trust and satisfaction, the DMS may help drivers detect changes in the driving environment that require attention. Specifically, drivers who received attention prompts after 7 consecutive seconds of inattention were 5 times more likely to react to a lane drift with no alert compared to drivers who did not receive attention prompts at all.
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    Effects of In-Vehicle Information Systems (IVIS) Tasks on the Information Processing Demands of a Commercial Vehicle Operations (CVO) Driver
    Blanco, Myra (Virginia Tech, 1999-12-10)
    This study was performed with two main goals in mind. The first goal was to understand and predict "red-lines" and "yellow-lines" in terms of what the CVO driver can process without hindering the primary task of driving. The second goal was to collect conventional secondary task data for CVO driving performance. An on-the-road experiment was performed with the help of 12 truck drivers. Type of task, presentation format, information density, and age were the independent variables used in the experiment. The 22 dependent measures collected were grouped into the following categories: eye glance measures, longitudinal driving performance, lateral driving performance, secondary task performance, and subjective assessment. The findings of this study strongly suggest that paragraphs should not be used under any circumstance to present information to the driver while the vehicle is in motion. On the other hand, the Graphics with Icons represent the most appropriate format in which driving instructions and information should be presented for IVIS/CVO tasks. In order to avoid a high visual attention demand to the driver due to a secondary task, only simple search tasks with the most important information shall be presented. Although the suggested format, type of task, and information density represent a higher visual attention demand than a conventional secondary task, these characteristics seem to bind a task with a moderate attentional demand. Other combinations of format, type of task, and information density will cause an increase in the driver's attentional demand that will consequently deteriorate their driving performance causing unsafe driving situations.
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    Enhanced Camera/Video Imaging Systems (E-C/VISs) for Heavy Vehicles
    Wierwille, Walter W.; Bowman, Darrell Scott; Alden, Andrew S.; Gibbons, Ronald B.; Hanowski, Richard J.; Blanco, Myra; Leeson, B.; Hickman, Jeffrey S. (United States. National Highway Traffic Safety Administration, 2011-06)
    Tests were performed to determine the feasibility of developing an Enhanced Camera/Video Imaging System (Enhanced C/VIS or E-C/VIS) to provide heavy-vehicle drivers with better situation awareness to the sides and rear of their vehicles. It is well known that large blind spots currently exist in these areas and that sideswipe crashes can occur as a result. An additional goal was to extend the operating envelope of conventional video to nighttime and to inclement weather. A three-channel system was envisioned in which there would be a camera at each (front) fender of the tractor looking backward along the sides of the rig. The third channel would be aimed rearward from the back of the trailer. The current document describes the project results. Indoor tests involved selection of components having the best capabilities, while early outdoor tests used the selected components in a single-channel side mounted system. Subjects evaluated rain and dark conditions. Results were satisfactory. Once developed, the three-channel system was tested and found to work well in the nighttime and inclement weather environments. Street lighting was also included in the testing.
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    Enhanced Night Visibility Series, Volume I: Executive Summary
    Hankey, Jonathan M.; Blanco, Myra; Gibbons, Ronald B.; McLaughlin, Shane B.; Dingus, Thomas A. (United States. Federal Highway Administration, 2005-12)
    This volume, an executive summary of the Enhanced Night Visibility project, is the first of 18 volumes that report on the project's evaluation of the merit of implementing supplemental ultraviolet headlamps, supplemental infrared systems, and other vision enhancement systems (VESs) to enhance drivers' nighttime roadway safety. The entire project evaluated 18 VESs in terms of their ability to provide object detection and recognition. Objects included scenarios with pedestrians standing or walking in different locations on the roadway. Pedestrians were dressed in black, white, or blue clothing to produce varying levels of contrast with their surroundings. Detection and recognition testing took place in clear weather, rain, snow, and fog conditions. Project research also evaluated a subset of the VESs for their effect on drivers' disability and discomfort glare. The VESs were also tested for their value in facilitating drivers' detection of pavement markings and other traffic control devices. The results indicated that supplemental ultraviolet headlamps do not provide sufficient benefit to justify further testing; however, supplemental infrared vision enhancement systems do offer an improvement over headlamps alone for detection of pedestrians. Near infrared systems have the potential to provide an added benefit in detecting pedestrians in inclement weather, but the implementation of NIR technology is the key to achieving this benefit.
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    Enhanced Night Visibility Series, Volume II: Overview of Phase I and Development of Phase II Experimental Plan
    Dingus, Thomas A.; Allen, Gary R.; Brich, Stephen C.; Neale, Vicki L.; Schroeder, Aaron D.; Blanco, Myra; Schnell, Thomas; Gillespie, James S.; Schroeder, Tracey T.; Simmons, Carole J.; Hankey, Jonathan M. (United States. Federal Highway Administration, 2005-12)
    The focus of the Phase I effort was on the establishment of performance and design objectives to facilitate the deployment of ultraviolet A (UV-A) headlamps. This report describes the plan to develop UV-A headlamp specifications, evaluate fluorescent infrastructure materials, quantify glare and photobiological risks, expand the cost/benefit analysis, and demonstrate and implement the UV-A technology. It also includes a literature review that was conducted before the Phase II studies. As is often the case in large projects, some of the planned work eventually changed or was replaced to address more pressing issues. The later volumes of this report series detail what research occurred and why.
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    Enhanced Night Visibility Series, Volume III: Phase II - Study 1: Visual Performance During Nighttime Driving in Clear Weather
    Blanco, Myra; Hankey, Jonathan M.; Dingus, Thomas A. (United States. Federal Highway Administration, 2005-12)
    Phase II-- Study 1 was performed as a stepping stone to expand the knowledge of how different vision enhancement systems can affect detection and recognition of different types of objects. The empirical testing for this study was performed on the Smart Road testing facility during clear weather conditions. A total of 30 participants were involved in the study. A 12 by 9 by 3 mixed-factorial design was used to investigate the effects of different types of vision enhancement systems, types of objects on the roadway, and driver's age on detection and recognition distances; subjective evaluations were obtained for the different systems as well. The results of the empirical testing suggest that no vision enhancement system consistently performs best in clear weather conditions. However, the halogen headlamp tested (low-beam configuration) consistently provided one of the longest detection and recognition distances, and even when other systems provided farther detection distances, these distances were generally not significantly different from halogen low beam. The only exception was the infrared thermal imaging system tested, which resulted in significantly farther detection distances for pedestrians and cyclists wearing dark-colored (low-contrast) clothing.
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    Enhanced Night Visibility Series, Volume IV: Phase II - Study 2: Visual Performance During Nighttime Driving in Rain
    Blanco, Myra; Hankey, Jonathan M.; Dingus, Thomas A. (United States. Federal Highway Administration, 2005-12)
    Phase II, Study 2 (rainy weather) was performed following the same procedures used for Study 1 (clear weather). Study 2 helped expand the knowledge of how current vision enhancement systems can affect detection and recognition of different types of objects while driving during adverse weather, specifically during rain conditions. The empirical testing for this study was performed on the Virginia Smart Road; the rain was controlled by weather making equipment. Thirty participants were involved in the study. A 12 by 7 by 3 mixed factorial design was used to investigate the effects of different types of vision enhancement systems, different types of objects on the roadway, and driver's age on detection and recognition distances; subjective evaluations also were obtained for the different vision enhancement systems. The results of the empirical testing suggest that vision enhancement systems that include halogen headlamps as their main component (i.e., halogen alone or halogen with ultraviolet A) consistently allow drivers the best detections during rain conditions. In fact, the halogen headlamp (low-beam configuration) provides the longest detection and recognition distances overall; in the few trials where other systems allow farther detection distances, these differences did not represent meaningful improvements. Even drivers using the infrared thermal imaging system, which resulted in farther detection distances for pedestrians and cyclists under clear conditions, perform no differently in the rain than when only the low beams of the vehicle were used.
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    Enhanced Night Visibility Series, Volume XII: Overview of Phase II and Development of Phase III Experimental Plan
    Hankey, Jonathan M.; Blanco, Myra; Neurauter, Michael L.; Gibbons, Ronald B.; Porter, Richard J.; Dingus, Thomas A. (United States. Federal Highway Administration, 2005-12)
    This volume provides an overview of the six studies that compose Phase II of the Enhanced Night Visibility project and the experimental plan for its third and final portion, Phase III. The Phase II studies evaluated up to 12 vision enhancement systems in terms of drivers' ability to detect and recognize objects, visibility of pavement markings, and discomfort caused by glare from oncoming headlamps. Drivers' ability to detect and recognize objects was assessed in clear, rain, fog, and snow conditions. The results indicated that supplemental ultraviolet headlamps do not provide sufficient benefit to justify further testing. The performance of supplemental infrared (IR) vision enhancement systems, on the other hand, was robust enough to suggest further investigation. As a result, additional IR testing, disability glare testing, and off-axis object detection on the Virginia Smart Road were proposed as a replacement for public road Phase III testing with UV-A. The details of the experimental plan for each of these testing areas are provided in the Phase III portion of this report.
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    Evaluating the Sleeper Berth Provision: Investigating Usage Characteristics and Safety-Critical Event Involvement
    Soccolich, Susan A.; Blanco, Myra; Hanowski, Richard J. (National Surface Transportation Safety Center for Excellence, 2015-07-20)
    Hours-of-service (HOS) regulations control the maximum daily drive time, workday hours, and work week (period) hours for commercial motor vehicle (CMV) drivers. The regulations also include periods of off-duty time that drivers must take before beginning a work shift, referred to as shift-restart methods in this study. In the 2005 regulations, the shift-restart methods included taking at least 10 consecutive hours off duty or in the sleeper berth (10+ hour restart), taking at least 34 consecutive hours off duty or in the sleeper berth (34+ hour restart), and a sleeper berth provision (SBP). The SBP requires one period of at least 8 (but less than 10) consecutive hours spent in the sleeper berth plus a period of at least 2 (but less than 10) consecutive hours spent in the sleeper berth, off duty but not in the sleeper berth, or a combination of off-duty time spent in and out of the sleeper berth. The purpose of this project was to examine the usage of shift-restart methods and the relationship between shift-restart methods and driver safety performance in a naturalistically collected driving data set. The data used for this study were collected by the Virginia Tech Transportation Institute (VTTI) in the Naturalistic Truck Driving Study (NTDS) and developed into a hybrid data set of naturalistically collected video data and activity register data that accurately detail the participating CMV drivers’ driving and non-driving activities.(7) With the activity register data, researchers determined which restart method drivers used before beginning a new work shift: 10+ hour restart, 34+ hour restart, or the SBP. The proportion of shifts preceded by SBP breaks was significantly higher for drivers who reported taking medications regularly versus those who did not and also for drivers with longer average delivery distances. The number of years of CMV driving experience had a significant inverse relationship with the proportion of total shifts with SBP breaks. A mixed-effect negative binomial model with a logarithmic link function was used to model safety-critical event (SCE) rate at the shift level, controlling for the driver. The SCE rates in shifts following an SBP break were found not to be statistically different from those in shifts following 10+ hour or 34+ hour restart breaks. Odds ratios were also used to assess the risks associated with each of the three shift-restart methods. The 10+ hour restart and 34+ hour restart methods were found not to be significantly different. However, both the 10+ hour restart and 34+ hour restart methods were associated with significantly higher risk than the SBP. This project serves to enhance the understanding of the current HOS regulations and the impact that these regulations have on drivers, a topic of significant concern in the CMV community. Drivers have different preferred break usage patterns. The use of the SBP in the current study does not appear to be associated with a decrement in safety performance. Future efforts should look into how the usage of shift-restart methods has changed under the new regulations, which went into effect on July 1, 2013, and modified the driving limits, on-duty time limits, and rest break requirements.
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    Fact Sheets
    Tidwell, Scott; Fitchett, Vikki L.; Blanco, Myra (National Surface Transportation Safety Center for Excellence, 2017-12-06)
    To extend its public outreach, the National Surface Transportation Safety Center for Excellence has created concise fact sheets describing research findings important to surface transportation safety. To date, fact sheets have been completed for nine projects. They are readily accessible through the NSTSCE page of the Virginia Tech Transportation Institute’s website (https://www.vtti.vt.edu/national/nstsce/index.html) and the Commercial Motor Vehicle Driving Safety website (http://cmvdrivingsafety.org).
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    Human Factors Evaluation of Level 2 and Level 3 Automated Driving Concepts: Concepts of Operation
    Marinik, Andrew; Bishop, Richard; Fitchett, Vikki L.; Morgan, Justin F.; Trimble, Tammy E.; Blanco, Myra (United States. National Highway Traffic Safety Administration, 2014-07)
    The Concepts of Operation document evaluates the functional framework of operations for Level 2 and Level 3 automated vehicle systems. This is done by defining the varying levels of automation, the operator vehicle interactions, and system components; and further, by assessing the automation relevant parameters from a scenario-based analysis stand-point. Specific to the “Human Factors Evaluation of Level 2 and Level 3 Automated Driving Concepts" research effort, scenarios and literature are used to identify the range of near- to mid-term production-intent systems such that follow-on research topics with highest impact potential can be identified through commonalities in operational concepts.
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    Human Factors Evaluation of Level 2 and Level 3 Automated Driving Concepts: Past Research, State of Automation Technology, and Emerging System Concepts
    Trimble, Tammy E.; Bishop, Richard; Morgan, Justin F.; Blanco, Myra (United States. National Highway Traffic Safety Administration, 2014-07)
    Within the context of automation Levels 2 and 3, this report documents the proceedings from a literature review of key human factors studies that was performed related to automated vehicle operations. This document expands and updates the results from a prior literature review that was performed for the US DOT. Content within this document reflects the latest research and OEM activity as of June 2013. Studies both directly addressing automated driving, and those relevant to automated driving concepts have been included. Additionally, documents beyond the academic literature, such as articles, summaries, and presentations from original equipment manufacturers and suppliers, have been researched. Information from both United States and international projects and researchers is included. This document also identifies automated-driving relevant databases in support of future research efforts.
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    Human Performance Evaluation of Light Vehicle Brake Assist Systems
    Fitch, Gregory M.; Blanco, Myra; Morgan, Justin F.; Rice, Jeanne C.; Wharton, Amy E.; Wierwille, Walter W.; Hanowski, Richard J. (United States. National Highway Traffic Safety Administration, 2010-04)
    The Brake Assist System (BAS) is a safety feature that supplements drivers' inadequate braking force during panic braking maneuvers upon the detection of a rapid brake pedal application. This report presents an evaluation of drivers' panic braking performance using BAS. Two vehicles with electronic BASs were selected: a 2006 Mercedes-Benz R350 and a 2007 Volvo S80. Sixty-four participants, balanced for age and gender, drove one of the instrumented vehicles at 45 mph and stopped at an unexpected barricade. Following debriefing, drivers performed another braking maneuver at the barricade, were shown how to perform a hard stop, and performed hard-braking maneuvers in which BAS was either enabled or disabled. Twenty-eight percent of drivers activated BAS subsequent to the demonstration. In the most conservative analysis, where the effect of BAS activation was isolated from driver panic-braking variability, it was found that BAS-active stopping distances were on average 1.43 ft (s.e. = 1.19 ft) shorter than BAS-disabled stopping distances. Yet, two drivers, who differed in age, sex, and vehicle driven, exhibited reductions in stopping distance exceeding 10 ft. Overall, the as-tested BAS has potential safety benefit that could be accrued from reduced stopping distance, but were not realized in this evaluation. Moreover, BAS implementations that do not completely rely on the driver may offer greater safety benefits.
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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.