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A literature review was conducted to identify and summarize findings relating to commercial truck and bus driver distrac- tion research conducted thus far. The literature reviewed in this task consisted of reports and analyses available from aca- demic, government, and industry sources. The review was conducted primarily through Internet searches of online data- bases, publications, and other industry resources. The reports identified have been summarized and are described in the following sections: â¢ The nature of distracted driving. â¢ Driver tasks unique to professional drivers. â¢ Countermeasure technologies and their effectiveness. â¢ Operational strategies and recommended practices. The primary focus of this review was to examine and fur- ther understand driver distraction and its impact on commer- cial vehicle safety. Because available truck and bus technology capabilities have been changing dramatically since the mid- 1990s, the literature cited herein was published since that time. LITERATURE REVIEW METHODOLOGY Literature searches were performed using websites, aca- demic databases, books, trade press publications, and arti- cles. The following databases were used to conduct the reviews: â¢ Transportation Research Information Database (TRID): The largest online bibliographic database of transporta- tion research, containing more than 900,000 records of published research. â¢ Business Source Premier: Features the full text for more than 2,200 journals. Full text is provided back to 1965, and searchable cited references back to 1998. â¢ LexisNexis: Provides access to many popular articles as well as some scholarly works. There is also access to congressional records, court decisions, and government statistical reports. These databases were searched using a variety of topic-related key words and phrases, often in combinations to improve focus. Key words included commercial motor vehicles, truck- ing, motor coaches, commercial drivers, safety, safety man- agement, risk management, operations management, driver 6 distraction, driver tasks, driver workload, distraction counter- measures, safety culture, safety climate, crash reduction, driver training, and driver supervision. NATURE OF DISTRACTED DRIVING A wide range of studies have addressed distracted driving and it continues to be a very active research topic. Studies of most relevance to this project are summarized here for the general driver population; the next section addresses commer- cial vehicle drivers specifically. The issues can be grouped into the following topics. Detailed Definition of Distracted Driving Pettitt et al. (2005) developed a comprehensive definition of distraction that accounts for all key components. In this def- inition, driver distraction occurs: â¢ When a driver is delayed in the recognition of informa- tion necessary to safely maintain the lateral and longitu- dinal control of the vehicle (the driving task) (Impact). â¢ Owing to some event, activity, object, or person, within or outside the vehicle (Agent). â¢ When a device that compels or tends to induce the driverâs shifting attention away from fundamental driving tasks (Mechanism). â¢ By compromising the driverâs auditory, biomechanical, cognitive, or visual faculties or combinations thereof (Type). Problem ExtentâHow Does Distracted Driving Relate to Crash Risk? McEvoy et al. (2005) examined crash data for cell phone use before a crash and found that crash likelihood was four times greater if drivers had used their phones in the minutes before a crash. Backer-GrÃ¸ndahl and Sagberg (2009) noted that, based on more recent crash data, driver distraction plays a role in between 8% and 25% of crashes. ZoomSafer (2011a) conducted a general survey of 500 business managers and noted that, although 32% of all companies surveyed have had instances of crashes linked to driver distraction, trucking had a higher occurrence (between 41% and 53% of companies) of distraction-related crashes. CHAPTER TWO LITERATURE REVIEW
7Traditional Distraction versus Electronic Devices Backer-GrÃ¸ndahl and Sagberg (2009) factored in exposure rates to determine the relative crash risk of various types of distraction. Looking at billboards, searching for addresses, and moving objects in automobiles were identified as having the highest relative risk. Molino et al. (2009) reviewed liter- ature addressing the effects of electronic billboards and found a 5 to 1 ratio of studies showing negative effects. Based on a driver survey, NHTSA (2010) identified the most common forms of distraction to be talking to passengers, radios/music, eating and drinking, and using a cell phone (in that order). Klauer et al. (2010) analyzed naturalistic driving data from the 100-car study to analyze the crash risk of simple, moderate, and complex secondary tasks. Although simple tasks had no effect, moderate tasks such as talking and listening on a hand- held device increased crash risk by a factor of 1.3. Complex tasks such as dialing a hand-held device increased risk by a fac- tor of 2.1. Another survey asked drivers to assess the degree to which distraction relates to crash involvement. The results were found to have some consistency with an analysis of the 100-car data: 30% of the time a situation outside the vehicle was responsible for the distraction, whereas objects inside the car were the cause 20% of the time. Among other factors, cell phone use was responsible for 2% of the distractions. Rakauskas and Ward (2005) examined the level of driver distraction associated with cell phone use, alcohol impair- ment, and in-vehicle tasks (such as pushing a button), and found that the particular in-vehicle tasks selected were more distracting than the cell phone conversations. Royal (2003) describes a NHTSA survey of distracting behaviors across 4,010 drivers. Looking for an object inside the car was the most common answer; only 2% of the responses dealt with technology, noted as being primarily radio. For participants involved during in a crash in the previous five years, only 0.6% attributed the cause to cell phone use. Cades et al. (2011) cites multiple sources to argue that eyes-on-road dis- tractions impair the driver, whether they relate to electronic devices or conversations with passengers. When Do Drivers Choose to Engage in Distracting Behaviors? Lerner et al. (2008) examined when drivers are willing to take a risk and engage in nondriving-related tasks. The study found their willingness to do this is related more to task issues and lifestyle than driving issues, and also noted that drivers were unlikely to plan ahead for either technology usage or delay usage until the driving demands were relatively low. How Does Distraction Relate to Driving Performance? Hancock et al. (2003) studied individuals driving on a test track who were presented with a dual task to create a distraction. The results showed that drivers braked later when engaged in a distraction task; however, they also braked harder, indicat- ing individuals in these conditions may stop sooner rather than later when a distraction is present. However, Morgan et al. (2011) reviewed driving performance parameters as they relate to distraction and found there were more lane devia- tions, less consistent and slower speeds, and poorer responses to emergencies. The study also noted that drivers allocate part of their cognitive resources to the secondary task, resulting in a form of âtunnel visionâ such that they do not scan the road scene as well. Rakauskas et al. (2004) employed a driving simulator to assess the relationship between distraction and three levels of conversation difficulty on a cell phone. Review- ing speed, lateral tracking, crash avoidance, and mental work- load it was found that speed was, on average, slower during conversation. No significant decline in safety measures was noted for any of the various levels of conversation difficulty; however, the researchers concluded that this relationship could be examined further. Smith et al. (2005) examined a variety of visual tasks to determine which types of visual stimuli present a threat. The study revealed that, as the visual task complexity increased, the inter-vehicle distance from the vehicle ahead increased; additionally, given similar eye glance patterns of two sec- ondary tasks, longer lasting secondary tasks present a greater crash risk. They concluded that, assuming similar eye glance patterns, as the time to complete a secondary task increases a safety threat becomes more imminent. Are Hands-Free Devices Safer Than Hand-Held Devices? The World Health Organization (WHO) (2011) examined a wide range of literature to conclude that, although using a mobile phone is detrimental to driving, it is not clear that hands-free phones are safer. Additionally, in a review of four experimental studies (Burns et al. 2002; Consiglio et al. 2003; Pattern et al. 2004; TÃ¶rnros and Bolling 2005, 2006) pertaining to cell phone conversations during driving-related activities, Ishigami and Klein (2009) generally found that both hands-free and hand-held phones, as compared with the experimental controls, impaired detection reaction times but not vehicle lane keeping tasks. This meta-analysis of cell phone research also found that, particularly with hands-free phones, drivers slow down when conversing on a cell phone (Ishigami and Klein 2009). Ishigami and Klein (2009) attrib- uted this slowing effect to a compensatory behavior for main- taining performance for keeping the vehicle in the lane. A more inclusive meta-review of 30 experimental and epi- demiological studies, including the 10 studies reviewed by Ishigami and Klein (2009), found similar trends (National Safety Council 2010). In the McEvoy et al. (2005) study, both hands-free and hand-held phones were determined to increase risk, with no difference found in risk depending on the type of phone. Conversely, an examination of naturalis- tic driving data of commercial vehicle drivers found that talk- ing or listening on a hands-free phone (i.e., driver talking
through a headset) provided a significant protective effect (odds ratio of 0.4), similar to the talking or listening to a cit- izenâs band (CB) radio (odds ratio of 0.6), therefore decreas- ing the risk of a safety-critical event (Olson et al. 2009). Olson et al. (2009) suggested that dialing a phone requires substantial visual attention, taking the driverâs eyes off the forward roadway, whereas listening or talking on the phone engages the driver and may provide an alerting mechanism (FMCSA 2009). The contrasting conclusions from these studies are the result at least in part from the different approaches used to obtain the results. The fundamental difference between Ishigami and Klein (2009) and Olson et al. (2009) is the level of experi- menter manipulation; where experimental studies are tightly controlled, naturalistic studies continuously capture data from drivers under normal driving texts without experimenter intervention. The McEvoy et al. (2005) study interviewed drivers who were hospitalized after a crash and researchers examined these driversâ cell phone records to determine if a cell phone had been used up to 10 min prior to the crash. By contrast, Olson et al. (2009), by examining naturalistic driving data, were able to examine the events that occurred seconds before the safety-critical event and distinguish the risk of the manual phone manipulation as compared with the driverâs phone conversation. As WHO (2011) recommends, there continues to be a need for more research to understand the degree to which cell phone subtasks (e.g., visual/manual demands and conversa- tion demands) contribute to driver impairment. How Risky Is Text Messaging While Driving? WHO (2011) concluded that text messaging is a considerable risk. Drews et al. (2009) used a driving simulator to show a greatly increased crash rate from text messaging. Section Summary Although a few topics are clear, there remain areas that require further research. The studies reviewed indicated a clear link to an increased risk of being involved in safety-critical events as a result of cell phone use while driving. Although the degree of risk is not clear, the risk from texting and dial- ing appears to be significantly greater. This result must be tempered with work showing the significant risk associated with nonphone distraction sources. Driving performance appar- ently does change when drivers are distracted; however, the consequences of this are not yet well understood given the contradictory results noted. Although some early research indicated that hands-free phones are no less risky than hand- held phones, more recent work examining naturalistic driving data shows a protective effect in using hands-free phones. 8 Citation Summaries Backer-GrÃ¸ndahl, A. and F. Sagberg, âRelative Crash Involve- ment Risk Associated with Different Sources of Driver Distraction,â presented at the First International Driver Dis- traction and Inattention Conference, Gothenburg, Sweden, Sep. 28â29, 2009. The authors introduce three types of research on driver distraction. First, there are experimental (e.g., simulator) or naturalistic studies that show the effects of distraction on driving behavior. Next, there are prevalence studies that use crash databases to show that driver distraction plays a role in between 8% to 25% of crashes. Finally, there are crash risk studies that improve on the former by factoring in exposure rates (i.e., how often the driver population engages in dis- tracting behaviors). This study took the latter approach by recruiting 4,307 crash-involved driver participants and determining relative crash risk through quasi-induced exposure. The most fre- quently occurring distractions were talking with passengers and attending to children in rear seats; however, the distrac- tions with the highest relative risk were looking at billboards outside, searching for addresses, and moving objects inside the car. Lower on the list were talking with passengers, attending to children in the rear seats, and adjusting a music device or radio tuner. Cades, D.M., S.R. Arndt, and A.M. Kwashniak, âDriver Distraction Is More Than Just Taking Eyes Off the Road,â ITE Journal, July 2011, pp. 26â33. The authors synthesize previous research to make the case that, although eyes-off-road distraction is clearly a safety haz- ard, distractions occurring with eyes-on-road also carry a sig- nificant potential for driver impairment. They cite research showing that eyes-on-road drivers when presented with dis- tractions do not necessarily perceive or encode objects they are looking at, are less likely to respond to traffic events, make riskier judgments regarding gaps in traffic, and are slower to respond to safety-critical events. Furthermore, the studies cited show that these drivers have smaller fields of view and thus do not scan as wide a range of the traffic scene. The types of distractions introduced in the studies included electronic devices as well as conversations with passengers. The authors assert that a high cognitive workload of the type associated with electronic in-vehicle devices may reduce the driverâs ability to process visual information available in the road- way environment. Drews, F.A., H. Yazdani, C.N. Godfrey, J.M. Cooper, and D.L. Strayer, âText Messaging During Simulated Driving,â Human Factors: The Journal of the Human Factors and Ergonomics Society, Vol. 51, 2009, pp. 762â770.
9The authors used a laboratory study involving a driving simulator to evaluate the driving performance of 40 partici- pants engaged in a single task (i.e., driving) versus a dual task (i.e., driving and text messaging). Participants in the dual task experimental group took their eyes off the road an aver- age of 5 s to engage in texting activities and were involved in six times as many accidents as their control group counter- parts. The texting drivers also took significantly longer to respond to brake lights ahead and demonstrated poor forward and lateral control of the simulator vehicle. Although these results were in line with findings from nat- uralistic studies, the severity of distraction effects may differ because simulator participants are aware they are being stud- ied in a laboratory environment, and college student partici- pants may differ in meaningful ways from professional truck drivers. FMCSA, Driver Distraction in Commercial Vehicle Opera- tions, Tech Brief, Publication No. FMCSA-RRR-09-045, FMCSA, Washington, D.C., 2009. This tech brief provides a summary of the Olson et al. (2009) study. Hancock, P.A., M. Lesch, and L. Simmons, âThe Distrac- tion Effects of Phone Use During a Crucial Driving Maneu- ver,â Accident Analysis and Prevention, Vol. 35, 2003, pp. 501â514. In this study, dual tasks were examined where individuals were required to respond to an in-vehicle telephone and make stopping decisions. A total of 42 participants were included in the study that resulted in a final sample of 36. Participants com- pleted the driving tasks on a one-fifth-mile loop-shaped track. A combination of distraction and stopping conditions were presented in addition to a controlled environment as follows: â¢ ControlâDriving only, â¢ Distracter only, â¢ Stopping only, and â¢ Distracter and stopping. Younger participants tended to approach the intersection faster than their older peers, but there were no gender differ- ences. In terms of brake response time, participants braked significantly slower when a distraction task was presented. Older drivers drove much more slowly than their younger counterparts during a distraction. The study concluded that the older groups as well as females tended to be more affected by distractions than the other groups (younger and male). Results also indicated that participants would brake harder in the presence of a distraction, which in turn stopped the vehi- cle sooner. Therefore, the research suggests that individuals may indeed stop sooner rather than later when a distraction is present. Ishigami, Y. and R. Klein, âIs a Hands-free Phone Safer Than a Handheld Phone?â Journal of Safety Research, Vol. 40, No. 2, 2009. The authors conducted a review of experimental, observa- tional, and epidemiological studies pertaining to the use of cell phones and driving-related activities. In most instances, hands-free communication was found to be as hazardous (or no less hazardous) to driving skills as using hand-held phones. This was true in nondriving studies, simulated driving studies, field driving studies, and epidemiological studies. In some cases, the authors concluded that hands-free devices were more dangerous than hand-held phones because the driver underestimates the threat and does not attempt to counteract potential negative effects (e.g., reaction time). Klauer, S.G., F. Guo, J. Sudweeks, and T.A. Dingus, An Analysis of Driver Inattention, Using a Case-crossover Approach on 100-car Data: Final Report, Report No. DTNH22-00-C-07007, National Highway Traffic Safety Administration, Washington, D.C., 2010. The authors analyzed the 100-Car Study database using logistic regression to identify behaviors that increased crash risk. They focused on three types of secondary tasks: com- plex, moderate, and simple. Examples of simple secondary tasks included adjusting a radio or other vehicle manufactured devices, talking to a passenger(s) in an adjacent seat, talking or singing with no passenger present, drinking, smoking, and thinking. As a group, these simple secondary behaviors were found not to increase crash risk. Next, the authors looked at moderate secondary behaviors, including talking and listening or other hand-held device activities, inserting or retrieving a compact disc, reaching for objects, grooming and other hygiene activities, eating, and looking at something outside of the vehicle. As a group, mod- erate secondary behaviors increased the crash risk 1.3 times, compared with no secondary behaviors. Finally, complex secondary behaviors included dialing a hand-held device; locating, reaching, and answering a hand- held device; reading; live animals or insects in the vehicle; reaching for a moving object; and applying makeup. As a group, drivers engaged in complex secondary tasks were 2.1 times more likely to be involved in a crash than drivers who did not perform these tasks. Lerner, N., J. Singer, and R. Huey, Driver Strategies for Engaging in Distracting Tasks Using In-vehicle Technolo- gies, Report No. HS DOT 810919, National Highway Traffic Safety Administration, Washington, D.C., 2008. Rather than conduct another study demonstrating the link between driver distraction and safety-critical events, the authors investigated when drivers are willing to take a risk
and engage in nondriving-related tasks. A focus group was used to become familiarized with the types of in-vehicle technologies commonly used, followed by an on-road study in which drivers kept a log of how willing they would be to engage in certain behaviors at specified points along pre- determined routes. Findings showed that driver willingness was associated more with task-related motivations and life- styles than with driving-related issues such as roadway or traffic characteristics. Drivers were also not very likely to plan ahead for their technology use or delay use until road conditions and driving demands were low. McEvoy, S.P., M.R. Stevenson, A.T. McCartt, M. Wood- ward, C. Haworth, P. Palamara, and R. Cercarelli, âRole of Mobile Phones in Motor Vehicle Crashes Resulting in Hos- pital Attendance: A Case-crossover Study,â BMJ, Vol. 331, 2005, pp. 1â5. Cell phone activity was examined for defined intervals before and after a crash. The sample consisted of 456 partic- ipants. Researchers concluded that crash likelihood was four times higher for participants that had used their phone within 10 min before the crash. There were no differences of crash likelihood between gender, age, or cell phone type. Both hands- free and hand-held cell phone use resulted in an elevated crash risk. Although this study found an increased crash risk associ- ated with cell phone use, it was suggested that enforcing laws that limit use may be difficult. Bluetooth technology has become increasingly prevalent in newer vehicles to promote hands-free cell phone use. However, the research in this study did not find a difference of crash likelihood between hands-free or hand-held devices. The presence of Bluetooth technology may encourage more people to use cell phones while driving thus contributing to an increase of crashes. Molino, J.A., J. Wachtel, J.E. Farbry, M.B. Hermosillo, and T. M. Granda, The Effects of Commercial Electronic Variable Message Signs (CEVMS) on Driver Attention and Distraction: An Update, Report No. FHWA-HRT-09-018, Federal Highway Administration, Washington, D.C., 2009. The authors reviewed literature addressing whether com- mercial electronic variable message sign displays (e.g., elec- tronic billboards and digital billboards) act to distract drivers and reduce driving safety. That is, as the outdoor advertising industry is moving in the direction of making billboards more attention-grabbing, is this causing drivers to substantively shift their attention away from the road? Empirical studies were reviewed and, although results were somewhat mixed, there was a 5 to 1 ratio of studies finding some negative driver safety effects as opposed to no effects of billboards. From a mental workload perspective, it can be concluded that drivers have a finite amount of capacity to focus on driving plus some spare capacity (i.e., a buffer that allows drivers 10 to focus some attention on nondriving tasks). The surplus capacity is reduced or eliminated as the driver takes on addi- tional demands (e.g., fixed hazards such as dangerous road layouts or transient hazards such as bad weather) and so it makes sense to prohibit billboards or other distracters from locations that already have known fixed hazards (e.g., sharp turns or difficult intersections). Further research must be con- ducted to review the effect of sign idiosyncrasies (e.g., infor- mation density, font size, message content, and dynamic messages) that could play a role in the severity of distraction. The authors present a list of independent and dependent vari- ables that could be studied, as well as the research strategies that might be employed. Table 3 in the studyâs appendix out- lines the associated advantages and disadvantages of the various field and lab approaches. Morgan, J.F., T.E. Trimble, D.S. Bowman, S. Baker, R. Pickett, D. Murray, and G. Bergoffen, Synthesis of Literature Relating to Cellular Telephone/Personal Digital Assistant Use in Commercial Truck and Bus Operations, Report No. FMCSA-RRR-11-015, Federal Motor Carrier Safety Admin- istration, Washington, D.C., 2011. This article reviewed four aspects of driving performance that have empirically been shown to be harmed by driver distraction. First, lateral control of a vehicle is impaired by distraction, with distracted drivers experiencing more un- intentional lane departures; greater variability in the vehicleâs position inside the lane; and sharper, more frequent steering wheel inputs and corrections, compared with undistracted drivers. Second, distraction has been shown to be detrimen- tal to longitudinal (i.e., speed) control of the vehicle, with distracted drivers typically struggling to maintain a constant speed; this greater variability in speed is accompanied by a lower average speed than undistracted drivers. Third, dis- tracted drivers have slower reaction times to unanticipated safety-critical events and are less likely to identify these events compared with undistracted drivers. Finally, the arti- cle describes how workload is also negatively affected by distraction, because distracted drivers must divide their cog- nitive resources between required driving and extraneous demands; as a result, distracted drivers attempt to compen- sate by focusing almost entirely on the central visual field ahead, as opposed to performing normal visual scanning of the entire roadway, again increasing the odds that they will fail to identify safety-critical events. National Safety Council, Understanding the Distracted BrainâWhy Driving While Using Hands-free Cell Phones Is Risky Behavior, White Paper, 2010 [Online]. Available: distracteddriving.nsc.org. As cell phone usage has increased over the past 15 years, the National Safety Council estimates that 25% of vehicle crashes can now be attributed to cell phone use, which amounts to 1.6 million crashes and 645,000 injuries. More than 80% of drivers admit to talking on their cell phones
11 while operating a vehicle, whereas 18% admit to texting while driving. To counteract this trend, more than 200 state bills were introduced in 2009, along with an Executive Order signed by President Obama. The National Security Council suggests that the reason cell phones present such a distraction is because drivers do not realize that talking on the phone takes cognitive resources away from the road. In addition to this cognitive explanation, cell phones can be incrementally distracting when they cause a driver to take his or her eyes off the road and/or hands off the wheel. Using a hands-free device is seen as a solution by the general public (as well as current state laws and company policies); however, the report noted that research has accu- mulated to demonstrate that these devices are no better (and potentially worse) than talking on hand-held phones. The human brain processes information sequentially and does not multitaskâas a result, drivers encounter inattention blind- ness (âlookingâ but not âseeingâ) when talking on the phone. Because they are not aware of this deficit, research has found that hands-free drivers are less likely to see high and low rel- evant objects; visual cues; exits, red lights, and stop signs; navigational signage; and the content of objects. These find- ings are unique to hands-free talking compared with talking with in-vehicle passengers. Adult passengers in the front seat can actually have a protective effect on crash risk, because they share awareness of the driving situation. As a result, the authors report that cell phone users (hand- held or hands-free) are four times more likely than nonusers to be involved in an accident. The report suggests that wide- spread education efforts are necessary, as well as comprehen- sive company policies and state laws banning all cell phone use. In addition, policies and laws will require strong enforcement by companies and the law, respectively. Finally, new technologies capable of blocking cell phone capabilities are another avenue worth exploring. NHTSA, Countermeasures That Work: A Highway Safety Countermeasure Guide for State Highway Safety Offices, 6th ed., National Highway Traffic Safety Administration, Washington, D.C., 2011. This guide was created as a reference to help State High- way Safety Offices select empirically proven counter- measures when addressing major highway safety problem areas, including distracted and fatigued driving. The authors begin by discussing the nature of distracted and fatigued driving, pointing out the relative difficulty of effectively countering these problem areas, because they are in large part societal issues dependent on lifestyle patterns and choices. To date, most research has centered on cell phones, despite the prevalence and severity of other distracters. Cell phones are likely singled out because they require the atten- tion of multiple senses (i.e., vision: locating the phone; touch: holding or dialing the phone; sound: listening to the party at the other end of the phone; and speech: talking to the other party), not to mention the cognitive capacity needed to understand and communicate. In 2002, NHTSA surveyed 4,010 drivers to identify the most common forms of distraction, which included (from most common to least common) talking to passengers, chang- ing radio stations or looking for music, eating or drinking, using a cell phone, dealing with children in the back seat, and reading a map or directions. In addition, NHTSA surveyed drivers to assess the degree to which distracted driving contributed to crash involvement, as seen from the survey participantâs perspective. It is noted that survey findings were likely underreported owing to response bias and, indeed, a follow-up study (the 100-car nat- uralistic driving study), found that nearly 80% of the 82 recorded crashes and 65% of the 761 near crashes involved drivers who took their eyes off the road just prior to the inci- dent. Still, there was a degree of consistency between the nat- uralistic study findings and NHTSAâs survey concerning which distractions most frequently lead to safety incidents. In both studies, roughly 30% of the time something outside the car was responsible for the distraction, whereas objects inside the car were responsible closer to 20% of the time. The latter included other passengers (19% in this survey; 11% in the naturalistic driving study) and cell phone use (2% of the time in both studies). Olson, R.L., R.J. Hanowski, J.S. Hickman, and J. Bocanegra, Driver Distraction in Commercial Vehicle Operations, Report No. FMCSA-RRR-09-042, Federal Motor Carrier Safety Administration, Washington, D.C., 2009. This study examined data from two previous naturalistic driving studies to calculate the odds ratios and population- attributable risk estimates for distracting tasks present in com- mercial vehicle operations. When combined, these datasets included 203 commercial drivers, 7 trucking fleets, and 16 fleet locations. These data represented approximately 3 million miles of continuously collected vehicle kinematic and video data. From these data, there were 4,452 safety-critical events (i.e., crashes, near-crashes, crash-relevant conflicts, and un- intentional lane deviations) that were examined. Key findings included: â¢ Of these safety-critical events, 81.5% had some type of driver distraction listed as a potential contributing factor. â¢ Drivers were engaged in nondriving related tasks in 71% of crashes, 46% of near crashes, and 60% of all safety-critical events. â¢ The task âtalking or listening on a hands-free phoneâ (i.e., driver talking through a headset) provided a signif- icant protective effect (odds ratio of 0.4), therefore decreasing the risk of a safety-critical event. â¢ Tasks associated with increased risk (high odds ratios) were associated with long eyes-off-forward-roadway times.
More detail on this study is provided in the next section. Pettitt, M., G. Burnett, and A. Stevens, âDefining Driver Dis- traction,â presented at the 12th World Congress on Intelligent Transport Systems, San Francisco, Calif., Nov. 6â10, 2005. The authors developed a comprehensive definition of dis- traction that accounts for all key components. In this defini- tion, driver distraction occurs: â¢ When a driver is delayed in the recognition of informa- tion necessary to safely maintain the lateral and longitu- dinal control of the vehicle (the driving task) (Impact). â¢ As the result of some event, activity, object, or person, within or outside the vehicle (Agent). â¢ When something that compels or tends to induce the driverâs shifting attention away from fundamental driv- ing tasks (Mechanism). â¢ By compromising the driverâs auditory, biomechanical, cognitive, or visual faculties, or combinations thereof (Type). Rakauskas, M.E., L.J. Gugerty, and N.J. Ward, âEffects of Naturalistic Cell Phone Conversations on Driving Performance,â Journal of Safety Research, Vol. 35, 2004, pp. 453â464. A simulator was used to assess the relationship between cell phone distraction and three levels of conversation diffi- culty (none, easy, and difficult). Safety measures used in the study consisted of: â¢ Speed maintenance, â¢ Lane positioning maintenance, â¢ Crash avoidance, and â¢ Mental workload. When participants held conversations while driving, results indicated more variation in acceleration and speed. Also, the average speed traveled was slower than non- conversation trials. However, the difficulty of cell phone dialogue did not result in any significant decreases in safety performance measures. It is important to note that no sig- nificant reaction time differences were found between con- versation groups when a hazardous event was presented (e.g., vehicle pulling out). Researchers concluded that: (1) the complexity of cell phone conversations while driving could be examined further, (2) technology manufacturers are becoming more active in reducing distractions, and (3) policymakers could decide to focus on one driving objec- tive (safety or convenience). Rakauskas, M. and N. Ward, Behavioral Effects of Driver Distraction and Alcohol Impairment, 49th Annual Human Factors and Ergonomics Society Meeting, Orlando, Fla. Sep. 26â30, 2005. 12 Cell phone conversations, alcohol impairment, and com- mon in-vehicle tasks were analyzed to determine the level of distraction associated with each. Conversations consisted of repeating a sentence, solving a verbal puzzle, or responding to a specific topic. In-vehicle tasks included pushing a button, adjusting airflow, changing temperatures, and pushing CD track buttons. Participants were assigned to either the control (received cranberry juice) or experimental (received alcohol and cranberry mixture) group. Blood alcohol content was maintained at 0.08 to represent the legal limit. Results indicated that participants engaged in cell phone conversations or in-vehicle tasks performed worse than those without a secondary task. The control group (no alcohol) per- formed worse while completing the in-vehicle tasks than the intoxicated participants without any secondary tasks. It is important to note that participants were more distracted by engaging in the in-vehicle tasks than conversing on the cell phone, meaning that cell phones caused less distraction than pushing buttons in the vehicle, adjusting airflow, changing temperatures, or pushing CD track buttons. Researchers suggested that banning hand-held cell phones may be a first step to limiting crashes, but additional studies needed to examine the specific issues associated with cell phone use while driving (e.g., in-vehicle tasks and text mes- saging). Also, educating the public on the risks associated with the various cell phone uses may provide a safer environ- ment while driving. Royal, D., National Survey of Distracted and Drowsy Driving, National Highway Traffic Safety Administration, Washington, D.C., 2003. The NHTSA studied the frequency of 12 distracting behaviors that people engage in while driving. The sample consisted of 4,010 U.S. drivers, and responses received were self-reported. Each driver was asked to estimate the number of trips taken each week and the frequency of distracting activities while driving. Participants were asked if they have had any crashes within the last five years and whether any distractions were involved. Of the participants who did have a crash result- ing in damage to a vehicle, only 0.6% of crashes were attributed to cell phone use. Table 1 includes the percent- age of crashes resulting from various distractions. The study found that males were more likely to use their phone while driving than females and older participants were less likely to use technologies (make or receive calls, change the radio, use a navigation system, etc.) than younger counter- parts. Of the drivers that did use cell phones while driving, the average duration of each call was approximately 4.5 min. Generally, most of the participants supported five pro- posed measures to reduce the use of cell phones while driving.
13 Public awareness had the highest support at 88%, followed by only allowing hands-free or voice-activated phones (71%), insurance penalties for crashes that involve cell phone use (67%), doubled or tripled fines for traffic violations involving cell phone use, and a ban on cell phone use while driving (57%). Smith, D.L., J. Chang, D. Cohen, J. Foley, and P. Glassco, A Simulation Approach for Evaluating the Relative Safety Impact of Driver Distraction During Secondary Tasks, World Congress on Intelligent Transportation Systems, 2005. This study examined driver distraction and several sec- ondary tasks that included: â¢ Visual tasks of less than 30 s (adjusting radio, dialing a cell phone); â¢ Complex visual tasks equivalent to one minute (map reading); â¢ Auditoryâverbal tasks that were 1â2 min (listening to a book on tape); and â¢ Driving for 2 min without additional tasks. A series of different visual tasks were measured in the study by using varying visual stimuli to determine in which cases visual stimuli present a threat. Results demonstrated that, as the visual task difficulty increased, the drivers tended to increase the amount of distance between their car and the vehicle directly in front, âfalling back.â An additional finding was that, given similar eye glance patterns of two secondary tasks, longer lasting secondary tasks present a greater crash risk. This was because the lead vehicle was traveling at variable speeds (decelerating unexpect- edly, etc.) and the distracted driver was less able to monitor following distance during longer secondary tasks. Therefore, assuming similar eye glance patterns, as the time to com- plete a secondary task increases a safety threat becomes more imminent. World Health Organization, Mobile Phone Use: A Growing Problem of Driver Distraction, 2011 [Online]. Available: www.who.int/violence_injury_prevention/publications/road_ traffic/en/index.html. Reviewing worldwide road fatalities and injuries, the report noted the risk posed by distracted driving as an increasing concern to policymakers even while the extent of the problem is not well known. Intended to raise aware- ness about distracted driving, the report summarizes exist- ing research. It focused primarily on mobile phone use, but also on other types of distractions. The report concluded that using a mobile phone while driving has a detrimental effect on driving behavior, and noted the lack of conclusive evidence that hands-free phones are safer than hand-held units. It further noted that text messaging while driving results in considerable physical and cognitive distraction, reducing driving performance. The authors concluded that more research is needed to understand the degree to which particular aspects of mobile phone use (dialing, talking, etc.) contribute to driver impairment. ZoomSafer, Inc., Measuring Corporate Attitudes About Employee Distracted Driving, 2011 [Online]. Available: http:// ZoomSafer.com/assets/Whitepapers/Survey-Results-White- Paper.pdf. ZoomSafer, an organization that makes software to prevent distracted driving, surveyed 500 North American business managers to identify corporate attitudes and best practices related to mobile phone use among drivers. From the overall sample, which included long-haul and short-haul trucking companies; construction companies; utility com- panies; taxi, limo, and bus companies; sales and service companies; home and business services and government, they found that 32% of all companies have knowledge or evidence of their employees getting into vehicle crashes as a result of cell phone distractions. When focusing solely on trucking (long-haul and local/short-haul), findings showed higher rates of cell phone-related crashes (53% and 41%, respectively), but also higher levels of policy implementation (71% and 83%, respectively) and enforcement (71% and 59%, respectively). DRIVER TASKS UNIQUE TO PROFESSIONAL DRIVERS The number of studies addressing distracted driving for pro- fessional drivers is much less than that for drivers in general. Studies of most relevance to this project are summarized here. The issues can be grouped into the following topics. Problem ExtentâHow Does Distracted Driving Relate to Crash Risk for Commercial Drivers? Knipling et al. (2003) examined safety problem areas and found the top three to be at-risk driving behaviors, high-risk Distraction Percentage Look for something outside the car 23 Dealing with children or other passengers 19 Looking for something inside the car 14 Another driver 11 Personal thoughts/thinking 5 Looking at an animal outside of the car 3 Dealing with technology (primarily radio) 2 Other distractions 23 TABLE 1 PERCENT OF CRASHES ATTRIBUTED TO DISTRACTION TYPES
drivers, and driver health and wellness. NHTSA (2010) showed a smaller proportion of large truck drivers and bus drivers who were distracted during a crash (8% and 6%, respec- tively) than is the case with passenger car drivers (11%); this has been a consistent finding over multiple years. The Large Truck Crash Causation Study (LTCCS; FMCSA 2005) found that driver inattention was the cause in 9% of fatal crashes, whereas 8% were the result of an external distraction and 2% an internal distraction; these distraction factors made it 5.1 and 5.8 times more likely for the truck driver to be at fault in a crash. Llaneras et al. (2005) con- ducted interviews with truck drivers and safety regulators regarding aftermarket technology for trucks. Nearly one- half of drivers admitted to âclose callsâ resulting from distraction. Traditional Distraction Sources versus Electronic Devices Hickman et al. (2010) examined 12 months of naturalistic truck and bus driver data based on the DriveCam video mon- itoring tool. Nondriving-related tasks requiring more visual attention were found to have had the strongest association to safety-critical events. Therefore, cell phone tasks such as dialing sharply increased the odds ratio. At the same time, talking or listening on a cell phone posed no increased risk and actually had a protective effect. The researchers cau- tion that although these effects can be associated, cause and effect cannot be determined because of the naturalistic nature of the study. Olson et al. (2009) combined data from two naturalistic studies, resulting in three million miles of kinematic and video data. This team found tertiary tasks (i.e., tasks unnecessary to the role of driving) present in 46% to 77% of safety-critical events, noting that these are differ- ent conclusions from the LTCCS. Notably, cell phone con- versations plus CB radio use was found to be protective. As with Hickman et al. (2010), it was concluded that the mean duration of eyes-off-road were associated with the severity of a safety-critical event. SmartDrive (2010) examined the most prevalent types of distractions during risky driving maneuvers, finding that having an object in hand rates high- est (44%), with cell phone-talking in second place (13%). Llaneras et al. (2005) assessed specific devices, finding that multifunctional devices were viewed favorably by respon- dents. These can be locked out while the vehicle is in motion if the fleet chooses; however, there is wide vari- ability as to the use of this feature. Although interactive tech- nologies alert drivers of developing situations and can be potentially distracting to drivers, three FMCSA-sponsored studies (Murray et al. 2009a,b,c) found significant net safety benefits for active safety systems [forward collision warning (FCW), lane departure warning (LDW), roll stability control (RSC)]. This finding is bolstered by the American Trans- portation Research Institute (ATRI) (2003) in which carriers surveyed noted safety as the prime motivation for deploying such systems. 14 How Risky Is Text Messaging While Driving? The Olson et al. (2009) study noted earlier found that risk was 23 times higher when texting compared with driving normally. This was far above the next most risky behaviors such as looking for objects or interacting with the dispatch- ing device. How Do Driver Practices Relate to Distraction-Related Risk? SmartDrive (2010) conducted a study observing 14 million video events from more than 34,000 drivers and found that a small number of drivers represented the majority of the driver distraction safety problem. Although 10% of safety-critical events involved distraction, this figure was 67% for the top 5% of drivers with the highest number of distraction events. Drivers with the most recorded distractions were 7.4 times more likely to be in a crash or near a crash than drivers with the fewest recorded distractions. Section Summary A brief summary is provided here to encapsulate the preceding discussion. Generally speaking, commercial drivers are less prone to be in a distraction-related crash as compared with the general public. The correlation of âbad appleâ commercial drivers with distraction-related safety-critical events is signifi- cant enough to enable fleet managers to adjust hiring practices and training. Nevertheless, distraction appears to be a cause for concern for all commercial drivers. As to the source of distrac- tion, researchers have found eyes-off-road to be a more com- pelling measure than the nature of the distraction. Relating this to cell phones, the manual tasks are noted as risky. With respect to hands-free phones, research findings are inconclusive. Notably, texting is especially risky. Regarding job-related elec- tronics, lock-out features are increasingly available to fleets. Citation Summary American Transportation Research Institute (ATRI) and Gartner G2, Inc., Trucking Technology Survey Results Sum- mary, ATRI, Arlington, Va., 2003. Onboard technology offers motor carriers insight into in- cab activities and driver (and vehicle) performance. According to a survey of 150 motor carriers, improved safety is the num- ber one reason carriers choose to deploy such technologies. And, although a very small proportion of carriers reported installing onboard safety systems in that survey, adoption of in-vehicle technologies has certainly grown as the novelty has worn off and the benefits have been demonstrated. FMCSA, The Large Truck Crash Causation Study Summary Report, Federal Motor Carrier Safety Administration, Wash- ington, D.C., 2005.
15 The FMCSA and NHTSA conducted the LTCCS by inves- tigating a nationally representative sample of 963 large truck crashes that occurred between April 2001 and December 2003. The investigations determined that truck driver inatten- tion was a causal factor (as opposed to an associated factor) in just 9% of fatal truck crashes; however, inattention made it 17.1 times more likely that a crash would be attributed to the truck (as opposed to a passenger vehicle or other factor). Meanwhile, 8% of crashes were attributed to truck driver external distraction (outside the cab) and 2% were attributed to truck driver internal distraction (inside the cab); respec- tively, these distraction factors made it 5.1 and 5.8 times more likely for the truck to be at fault in a crash. Hickman, J., R. Hanowski, and J. Bocanegra, Distraction in Commercial Trucks and Buses: Assessing Prevalence and Risk in Conjunction with Crashes and Near-crashes, Report No. FMCSA-RRR-10-049, Federal Motor Carrier Safety Administration, Washington, D.C., 2010. This study analyzed 12 months of naturalistic truck and bus driver data provided by DriveCam, whose onboard safety monitoring systems record videos of drivers and data from kinematic sensors on safety-related events. One data set included data wherein kinematic sensors were activated by nonsafety-triggered events (e.g., driving over train tracks) to serve as a baseline in calculating odds ratios. This data set included safety-triggered events and baseline events from 183 truck and bus fleets with 13,306 trucks and buses. Con- cerning safety events, there were 1,085 crashes, 8,375 near crashes, and 30,661 crash-relevant conflicts in the data set, compared with 211,171 baseline (nonsafety) events. Tertiary tasks (i.e., tasks unnecessary to the role of driving) were found to have the strongest association to safety-critical events when they demanded more visual attention. Therefore, concerning cell phones, while talking or listening on a hands- free cell phone posed no increased risk (and actually had a protective effect), reaching for a phone (or headset or earpiece) or dialing, texting, e-mailing, or using the Internet sharply increased the odds of a safety-critical event. A strength of naturalistic studies is the high ecological validity, which cannot be easily replicated through simulator studies. A weakness, however, is that, because no variables are being manipulated, cause-and-effect inferences cannot be made. That is, observation only revealed an increased asso- ciation between tertiary tasks with visual components and safety-critical event occurrence. Pertaining more specifically to this study, another caveat is that the base rates of unwanted tertiary behaviors were likely much lower than would be found in the general population, because drivers knew their behaviors were being monitored and were working for carri- ers who were safety conscious enough to install the onboard safety monitoring devices. Knipling, R., J. Hickman, and G. Bergoffen, CTBSSP Syn- thesis 1: Effective Commercial Truck and Bus Safety Man- agement Techniques, Transportation Research Board of the National Academies, Washington, D.C., 2003. This synthesis report provides a summary of safety man- agement techniques in commercial truck and bus transporta- tion. Twenty safety problem areas and 28 safety management techniques were identified through a literature review, discus- sions and interviews with industry experts, and suggestions from the TRB synthesis panel. Problem areas included both driver and vehicle issues, and safety management techniques ranged from driver recruiting and selection to advanced safety technologies. A questionnaire was distributed to fleet safety managers and other industry safety experts through several trade asso- ciations and industry-related professional organizations to assess their relative importance. The top three problem areas for safety manager respondents were found to be at-risk driving behaviors (e.g., speeding and tailgating), high-risk drivers (all causes combined), and driver health and wellness. The three most common management techniques practiced by safety managers were continuous tracking of driversâ crashes, inci- dents, and violations; regularly scheduled vehicle inspec- tions and maintenance; and hiring based on criteria related to driver crash, violation, or incident history. Each of these tech- niques was practiced by 90% or more of the safety manager respondents. Based on the survey results and reviewed literature, four âsafety opportunity areasâ were selected for further research and discussion: driver health, wellness, and lifestyle; high risk drivers; behavioral safety management; and safety man- agement professionalism. Several opportunities to improve safety were identified for each area: â¢ Driver health, wellness, and lifestyle â Motor carrier wellness programs. â¢ High risk drivers â Predicting crash rate based on past behaviors, and â Intervention programs. â¢ Behavioral safety management â Self-management programs, â Driver incentive programs, â Safety placards, and â On-board recording. â¢ Safety management professionalism â Certification of fleet safety practices, and â Certification of safety managers. Llaneras, R.E., J.P. Singer, and R. Bowers-Carnahan, Assess- ment of Truck Driver Distraction Problem and Research Needs, Report No. DOT HS 809883, National Highway Traf- fic Safety Administration, Washington, D.C., 2005.
The researchers interviewed truck drivers and safety regula- tors to learn more about available original equipment manufac- turers (OEM) and aftermarket technology options for trucks. Most research on driver distraction focuses on light vehicles, yet trucks are often the quickest to adopt new technologies. Additionally, findings from driver distraction research con- cerning passenger vehicles may not be fully applicable to the trucking industry, owing to myriad differences in the types of in-vehicle devices, device placement and design, or other factors associated with the nature of being a professional driver (e.g., skill, experience, and judgment). Interviewed drivers and safety personnel were optimistic that profes- sional truck drivers make smart decisions regarding when and when not to use in-cab technology, although this was highly subjective and nearly half of the drivers still admitted to experiencing a âclose callâ resulting from distraction. The authors also used task analysis to critically examine a variety of available in-truck devices and gauge the quality of their human factors design as it pertains to minimizing driver distraction. Devices included telematic systems, safety and warning devices, and navigation and fleet management sys- tems, such as the following: â¢ AutoVue Lane Departure Warning System â¢ Bendix X-Vision (night vision system) â¢ Delphi Truck Productivity Computer (multifunctional device, similar to the AutoPC) â¢ Eaton Vorad and Smart Cruise (Adaptive Cruise Control) â¢ Freightliner Driver Message Center â¢ Freightliner Rollover Stability Advisor â¢ Global T-Fleet communications and tracking system â¢ Mack VIP display (multifunctional message center) â¢ MobileMax communications system (text messaging) â¢ Mobiuss TTS Onboard Computer â¢ PACCAR Driver Message Center â¢ People Net Wireless Fleet Solutions â¢ Qualcomm Fleet Advisor and MvPC (text-messaging) â¢ VDO FM System â¢ Volvo Driver Information Display and Volvo Link (text messaging). Multifunctional devices appeared to be particularly com- mon in the industry, and having systems that offered both text messaging and driver communication functions topped the list, both for OEM and aftermarket products. As proactive steps toward limiting distraction, many systems are customiz- able so that fleet safety managers can decide if they want to (completely or partially) lock out certain functions or, in the case of messaging systems, send messages with differ- ent levels of urgency and only allow the driver to read emer- gency messages while the vehicle is in motion. Despite these options, it varies widely between and even within fleets whether these lock-out capabilities are utilized. Finally, inter- views revealed that banning technology is viewed as impracti- cal and unwarranted, whereas the effectiveness of policies prohibiting the use of in-vehicle devices while driving is also questionable. Interviewees argued that effectiveness of these 16 policies was contingent on enforcement and consistently applied rules (with penalties for noncompliance), whereas the key to limiting distraction from in-vehicle devices rested on enhanced designs and interfaces and reasonably applied restrictions and lock outs. Murray, D., S. Shackelford, and A. Houser, Analysis of Ben- efits and Costs of Forward Collision Warning Systems for the Trucking Industry, Publication FMCSA-RRT-09-021, FMCSA, U.S.DOT, Washington, D.C., 2009a. Murray, D., S. Shackelford, and A. Houser, Analysis of Benefits and Costs of Lane Departure Warning Systems for the Trucking Industry, Publication FMCSA-RRT-09-022, FMCSA, U.S.DOT, Washington, D.C., 2009b. Murray, D., S. Shackelford, and A. Houser, Analysis of Benefits and Costs of Roll Stability Control Systems for the Trucking Industry, Publication FMCSA-RRT-09-020, FMCSA, U.S.DOT, Washington, D.C., 2009c. Although interactive technologies alert drivers of devel- oping situations and can be potentially distracting to drivers [e.g., forward collision warning system (FCWS) and lane departure warning system (LDWS)], it is likely that their net effect is to increase safety. These three studies spon- sored by FMCSA discovered significant benefits as a result of deploying safety systems. In one study, it was determined that FCWS, if used nationally on all fleets, would prevent between 8,597 and 18,013 rear-end crashes, reducing annual injuries by 6,303 and fatalities by 103. LDWS was found to offer similar benefits, with the potential to prevent thou- sands of sideswipes, rollovers, and head-on collisions, with an annual reduction of 1,973 injuries and 100 fatali- ties. Finally, RSC systems were found capable of prevent- ing between 1,422 and 2,037 rollovers each year, reducing the number of injuries by 1,322 and deaths by 73. For each $1 spent on deploying FCWS, LDWS, and RSCs, a return- on-investment of $1.93, $1.98, and $2.33 could be expected, respectively, with initial investments recouped within 6 to 37 months. Olson, R.L., R.J. Hanowski, J.S. Hickman, and J. Bocanegra, Driver Distraction in Commercial Vehicle Operations, Report No. FMCSA-RRR-09-042, Federal Motor Carrier Safety Administration, Washington, D.C., 2009. The researchers combined data from two naturalistic stud- ies to identify 4,452 safety-critical events and 19,888 base- line events among 203 commercial motor vehicle (CMV) drivers from 55 trucks belonging to 7 different fleets. In total there were 3 million miles of continuously collected kine- matic and video data. Tertiary tasks were determined to be present in 46.2% to 77.5% of the safety-critical events, lead- ing to notably different conclusions from the LTCCS. Risk was especially elevated when drivers performed highly com- plex tertiary tasks, such as text messaging or taking their eyes off the road to rummage through a grocery bag (see Table 2).
17 Talk/sing/dance with no indication of passenger 1.05 0.90 1.22 Smoking-related behaviorâcigarette in hand or mouth 0.97 0.82 1.14 Drink from a container 0.97 0.72 1.30 Interact with or look at other occupant(s) 0.35* 0.22 0.55 Talk or listen to hands-free phone 0.44* 0.35 0.55 Bite nails/cuticles 0.45* 0.28 0.73 Look at outside vehicle, animal, person, object, or undetermined 0.54* 0.50 0.60 Talk or listen to CB radio 0.55* 0.41 0.75 Smoking-related behaviorâreaching, lighting, extinguishing 0.60* 0.40 0.89 Other personal hygiene 0.67* 0.59 0.75 Asterisk indicates a significant odds ratio. Task Odds Ratio LCL UCL Text message on cell phone 23.24* 9.69 55.73 OtherâComplex Tertiary Task (e.g., cleaning side mirror, rummaging through a grocery bag) 10.07* 3.10 32.71 Interact with/look at dispatching device 9.93* 7.49 13.16 Write on pad, notebook, etc. 8.98* 4.73 17.08 Use calculator 8.21* 3.03 22.21 Look at map 7.02* 4.62 10.69 Use/reach for other electronic device (e.g., video camera, 2-way radio) 6.72* 2.74 16.44 Dial cell phone 5.93* 4.57 7.69 OtherâModerate Tertiary Task (e.g., opening a pill bottle to take medicine, exercising in the cab) 5.86* 2.84 12.07 Personal grooming 4.48* 2.01 9.97 Read book, newspaper, paperwork, etc. 3.97* 3.02 5.22 Put on/remove/adjust sunglasses or reading glasses 3.63* 2.37 5.58 Reach for object in vehicle 3.09* 2.75 3.48 Look back in sleeper berth 2.30* 1.30 4.07 Adjust instrument panel 1.25* 1.06 1.47 Talk or listen to hand-held phone 1.04 0.89 1.22 Eat 1.01 0.83 1.21 Remove/adjust jewelry 1.68 0.44 6.32 OtherâSimple Tertiary Task (e.g., opening and closing driverâs door) 2.23 0.41 12.20 Put on/remove/adjust hat 1.31 0.69 2.49 Use chewing tobacco 1.02 0.51 2.02 Put on/remove/adjust seat belt 1.26 0.60 2.64 TABLE 2 ODDS RATIOS AND 95% CONFIDENCE INTERVALS TO ASSESS LIKELIHOOD OF A SAFETY-CRITICAL EVENT WHILE ENGAGING IN TERTIARY TASKS
Significant predictors of safety-critical events have asterisks placed next to their odds ratios, which inform the reader how much each behavior elevates the risk of being involved in an event. For instance, the statistically significant odds ratio estimate of 23.24 for text messaging means that drivers who engage in text messaging behind the wheel are more than 23 times more likely to be involved in a safety-critical event than drivers who do not text message behind the wheel, hold- ing all other behaviors constant. In addition to the best esti- mate for the odds ratio value, the table also presents 95% confidence intervals, which indicate a range of possible odds ratio values, with 95% certainty that the true odds ratio falls between the lower confidence level and upper confidence level. Therefore, although the odds ratio estimate is 23.24 for text messaging, it may actually fall between 9.69 and 55.73, owing to statistical uncertainty. In any case, the behavior increases risk because it is always over the value of 1.00. A protective effect (odds ratio below 1.00) was observed for several tasks, including talking and listening by means of a hands-free phone and use of the CB radio. Olson and colleagues expanded on these findings to demonstrate that the mean duration of eye glances away from the road were associated with the severity of the safety- critical event. Odds ratios suggested that long glances of more than 2 s greatly increased the risk of a safety-critical event; not surprisingly, behaviors with the highest odds ratios in Table 2 were most often also behaviors associated with taking oneâs eyes off the road. NHTSA, Traffic Safety Facts: Distracted Driving 2009, Wash- ington, D.C., 2010 [Online]. Available: http://www.distraction. gov/research/PDF-Files/Distracted-Driving-2009.pdf. Using the Fatality Accident Reporting System, NHTSAâs National Center for Statistics and Analysis showed that a smaller proportion of large truck drivers and bus drivers who were distracted during a crash (8% and 6%, respectively) than is the case with passenger car drivers (11%). This is a consistent finding over multiple years. SmartDrive, Commercial Fleet Distracted Driving Research 2010, 2010 [Online]. Available: http://www.smartdrive.net/ documents/smartdrive-distracted-driving-report_2010.pdf. SmartDrive Systems, a fleet safety and efficiency solutions company, has engaged tens of thousands of truck drivers in a study, known as the SmartDrive Safety program, to provide fleets a glimpse into the causes and rates of commercial driver distraction. During 2010, SmartDrive observed nearly 14 mil- lion video events from 34,466 commercial drivers who were observed through in-cab video, allowing SmartDrive to cre- ate the SmartDrive Distracted Driving Index (SDDI) as a baseline for future comparisons. The SDDI has revealed, among other things, that a small minority of drivers represent the vast majority of distracted driving problems. That is, although the study found that 18 roughly 10% of all safety-triggered events (e.g., sudden stops, swerves, and collisions) involved a driver engaged in distracted driving activities, this figure jumped to 67% for the top 5% of drivers with the highest number of distraction events. Compar- ing drivers with the most recorded distractions to drivers with the fewest recorded distractions revealed that the former group is 7.4 times more likely to be involved in a crash or near crash. The nine most prevalent distractions discovered during risky driving maneuvers were: â¢ Object in hand (e.g., MP3 players, personal digital assis- tants, and paperwork); 44.5% â¢ Talking on a hand-held mobile phone; 13.4% â¢ Beverage; 12.7% â¢ Food; 10.1% â¢ Smoking; 9.9% â¢ Operating a hand-held device (e.g., texting); 9.1% â¢ Talking and listening on mobile phone (hands-free); 5.2% â¢ Using a map or navigation device; 1.0% â¢ Grooming and personal hygiene; 0.6%. COUNTERMEASURE TECHNOLOGIES FOR DISTRACTION AND THEIR EFFECTIVENESS Numerous research studies have investigated counter- measure technologies for distracted driving, and the con- sumer electronics industry is active as well. Publications of most relevance to this project are summarized here. The issues can be grouped into the following topics. Combining Driver Monitoring with Driver Assistance Lerner et al. (2008) developed a matrix that mapped 36 find- ings to possible countermeasures for each respective finding. Countermeasure options included public education and safety campaigns, driver training, user interface design, functional lock-out technology of electronic devices, and interactive control technology, such as driver assistance systems. (Driver assistance systems include functions such as LDW and FCW that serve to make the driver aware of safety-critical situations and therefore have the potential to compensate for driver attention lapses.) Llaneras et al. (2000) reported on the results of a NHTSA-sponsored online forum, which concluded that driver assistance systems are useful to provide additional âeyes and ears.â Several studies have addressed driver monitoring to detect distracted driving, with sensor-based collision warning sys- tems playing a role to mitigate the momentary effects of the distraction event. The authors clearly recognize that there exists the possibility of a driver âgamingâ the system and engaging in more secondary tasks knowing that there are sup- port systems such as crash warning. For instance, in the final report for the Intelligent Vehicle Initiative FCW field operational test, Battelle (2007) reported
19 that driver assistance systems helped drivers keep a safe following distance, improve reaction time, and increase awareness when distracted. Blaschke et al. (2009) evaluated options for managing distracted driving: block incoming calls when aware of a complex driving situation, warn driver of distracted conditions, or minimize negative outcomes of distraction with support systems such as LDWS. Kircher and AhlstrÃ¶m (2009) examined the relationship between driver assistance systems such as FCW and LDW and driver distrac- tion countermeasures. They noted that such systems could warn drivers earlier, particularly when combined with eye tracking systems that would detect eyes-off-road conditions. Lee et al. (2000) examined the potential of FCW to mitigate driver distraction in driving simulator experiments. The study found that cognitive demands (speaking) pose a risk equal to visual distractions and that the effects could be mitigated with FCW. The authors suggest integrating detection of distraction events with FCW to issue earlier warnings, as long as this does not encourage the driver to increasingly engage in distracting activities. Donmez et al. (2008) built on earlier work to demon- strate that presenting real-time feedback to drivers on lane position resulted in fewer distracting activities. The team rec- ommended both retrospective and real-time feedback. As to the technological approach to detecting driver distrac- tion, Blaschke et al. (2009) advocates eye- or head-tracking systems. By contrast, Zhang et al. (2008) describes work in the SAVE-IT program to identify decrements in driving per- formance as a result of visual distraction. The authors here concluded that while eye-based tracking is more accurate, head-based systems are more practical, and therefore recom- mended moving forward with head movement sensors. WHO (2011) notes the potential value of technological interventions such as workload managers and LDWs; how- ever, these technologies are seen as having a limited impact on a global basis owing to their low market penetration. Insurance-Links Measures to Monitor Cell Phone Use ZoomSafer (2011b) describes both an active and passive approach to cell phone use within a vehicle, in the context of usage-based insurance (UBI) techniques. The active approach connects a smartphone with a UBI device in the vehicle, such that the smartphone is automatically deactivated when the vehicle is in motion. The passive approach consists of integrat- ing UBI data (including events during driving) with billing records from the telecommunications carrier for the cell phone, so that events can be correlated with cell phone use. Although the active approach requires a smartphone, the pas- sive approach works with any phone. The Importance of Good Design in HumanâMachine Interfaces NHTSA (1997) took an early look at the safety implications of cell phones, noting the cognizant risks but also highlighting the core issue of inattentiveness. The authors contend that banning devices is not the correct approach and good design is key. Volpe (2008) offers a primer on technology for traffic safety, noting that it is important to consider the humanâmachine inter- face (HMI) when developing new safety systems, to strike the right balance between driver assistance and distraction. Burns (2007) presented a Transport Canada analysis of in-vehicle devices to argue that the impetus for distraction counter- measures lies with the designers of these devices. Llaneras et al. (2000) reported on the results of a NHTSA-sponsored online forum, which concluded that clearer graphics and ergonomics are needed in vehicle cabs. The Research and Innovate Tech- nology Administration (RITA) (2011) describes a panel con- sisting of consumer electronics industry members held as part of a symposium on occupationally related distracted driving. It asserted that electronic devices can distract or assist the driver, and lock-outs and similar features exist for professional drivers. They noted that technology is moving in the direction of faster touch, less touch, or no touch (speech command and control). Vollrath and Totzke (2000) conducted driving simulator exper- iments to determine that driving performance is at its worst with manual tasks, followed by visual tasks, and most effective during with auditory tasks, concluding that auditory interfaces should be emphasized in design and, if visual/manual tasks are needed, augment the driver with driver assistance systems. Lee et al. (2007) described the SAVE-IT project to imple- ment adaptive interface technology as a countermeasure to driver distraction. The team developed models that accurately detected cognitive distraction 75% to 95% of the time. Find- ings suggested that listening to information is less demanding than responding to questions, cognitive and visual demands are additive, and cognitive distraction is multifaceted. To the latter point, the researchers noted that cognitive distraction is composed of distinct types with different impacts on driving performance. As to specific design measures, Lee and Hoffman (2004) examined optimum methods to warn a distracted driver. They found that graded warnings (i.e., warnings that progress from less urgent to more urgent if the driver does not respond) were better received than single-state warnings; also that haptic messages were more acceptable to drivers than auditory mes- sages. Fuller and Tsimhoni (2009) examined issues relating to screen placement using driving simulator studies. They noted that all screens can create distraction and showed that far- away screens created more significant distraction issues than screens close to the driver. Llaneras et al. (2005) conducted interviews with commercial fleet safety managers that indi- cated that, although lock-out functions are available for in-cab devices, the utilization of these functions varies widely. Section Summary Although the combination of driver monitoring and driver assistance systems has been shown to be effective in miti- gating the effects of distraction, there exists the possibly of a driver âgamingâ the system and engaging in more sec- ondary tasks owing to the presence of a support system,
creating an opposite effect. As to the human interface, the vehicle industry can potentially benefit from advances in HMI from the consumer electronics industry. Research studies have increased the knowledge base as to the inter- action between drivers and support systems, which will be important to the good design of these systems. Citation Summary Battelle, Final Report Evaluation of the Volvo Intelligent Vehicle Initiative Field Operational Test Version 1.3, National Highway Traffic Safety Administration, Washington, D.C., 2007. In 1999, the U.S.DOT partnered with Volvo Trucks North America and US Xpress to test collision warning system (CWS), adaptive cruise control (ACC), and advanced elec- tronic braking (AdvBS) systems in a Field Operational Test of intelligent vehicle safety systems (IVSS) designed for CMVs. Concerning usability of the safety systems, most drivers agreed that CWS visual and audible signals were always easy to see and hear; different IVSS warnings (for- ward, side, visual, auditory) were easy to distinguish from one another (although at times difficult owing to mental or physical fatigue) and from non-IVSS systems in the truck. Finally, although drivers found AdvBS useful in all con- ditions and ACC useful aside from climbing hills or sitting in heavy traffic, the perceived usefulness of CWS varied more. Specifically, CWS was found to be most useful when visibil- ity was low (e.g., during night time, foggy conditions, heavy rain, or snow), but much more distracting in heavy traffic. Furthermore, nearly half of all CWS warnings were deter- mined by drivers to be false positives, which they found annoying. Still, most drivers reported that neither the visual nor auditory warnings caused them to be distracted from their driving tasks, and that they did not need to look away from the road to identify what a CWS alert meant. On the contrary, it was reported that CWS and ACC helped them keep at a safe following distance, improve reaction time, and increase awareness when distracted. Blaschke, C., B. FÃ¤rber, R. Limbacher, B. Trefflich, F. Breyer, and S. Mayer, âOnline Estimation of the Driverâs State Enhancement of Lane-keeping Assistance,â First Inter- national Conference on Driver Distraction and Inattention, Gothenburg, Sweden, Sep. 28â29, 2009. This study evaluated three available options for managing driver distraction, including prevention, mitigation, and mini- mizing negative outcomes. Preventing distraction involves the utilization of driving data (e.g., road conditions, traffic, and weather) to determine a driverâs capacity to handle addi- tional information. If demand on the driver is already high, then incoming calls to the driver will be postponed or in-vehicle information systems will be locked, so as to not overload the driver. 20 Mitigating distraction, on the other hand, involves distrac- tion warning systems, which issue warnings to the driver when the system detects he or she is being distracted, with the goal of bringing the driverâs attention back to focusing on the road. Finally, to minimize negative outcomes of driver distrac- tion, the approach advocated in this paper involves using driver assistance systems that provide a safety net in instances of driver distraction (e.g., LDWS). These warning systems typically generate acoustic or haptic warnings to the driver and some advanced systems will guide the vehicle back to the middle of the lane. However, a problem with traditional in-vehicle systems is their hypersensitive false alarms (e.g., inconsequential minor deviations from the middle of the lane or unsignaled lane changes). This paper demonstrates that in-vehicle systems can be improved by using eye- and head- tracking devices to recognize when the driver is visually dis- tracted and most likely to actually need the safety system to activate, which acts to suppress unnecessary warnings. Burns, P.C., âDriver Distraction Countermeasures,â In Distracted Driving, I.J. Faulks, M. Regan, M. Stevenson, J. Brown, A. Porter, and J.D. Irwin, Eds., Australasian College of Road Safety, Sydney, NSW, Australia, 2007. Transport Canada investigated potential countermeasures that could reduce the amount of unnecessary distraction drivers face from in-vehicle telematic devices. The authors concluded that the impetus rests with product designers, who must do more to consider the distraction potential of their products and increase human factors research during product design, devel- opment, and testing phases. Essentially, designers should give first considerations to safety and usability factors, followed by device features, rather than the other way around. Donmez, B., L.N. Boyle, and J.D. Lee, âMitigating Driver Distraction with Retrospective and Concurrent Feedback,â Accident Analysis and Prevention, Vol. 40, 2008, pp. 776â786. This was a follow-up study to previous work by the authors where it was demonstrated (using a driving simulator) that drivers engaged in fewer distracting activities (i.e., looking at in-vehicle information systems instead of the road) when given real-time feedback on their driving performance (e.g., lane position). A caveat, however, is that receiving real-time feed- back may act as an additional distraction and interfere with task performance. To expand on those findings, this simulator experiment compared three feedback delivery conditions: retrospective (i.e., end of trip) feedback, combined retrospective and con- current (i.e., real-time) feedback, and no feedback. Accel- erator release times were measured following unexpected braking events by lead vehicles, and drivers in both feedback groups (retrospective and combined feedback) outperformed drivers receiving no feedback, as measured by significantly
21 shorter accelerator release times. Additionally, the combined feedback group also displayed significantly longer, more sus- tained glances to the road, leading the authors to conclude that providing drivers with both real-time and retrospective feedback on distraction state is an effective strategy for mit- igating the negative effects of distraction. Although real-time feedback is immediately helpful, an advantage of retrospec- tive feedback is that it is less transitory and can therefore be processed more fully by the driver, making it more likely to actually change long-term behavior. Fuller, H. and O. Tsimhoni, Glance Strategies for Using an In-vehicle Touch-screen Monitor, Report No. UMTRI-2009-5, Transportation Research Institute, University of Michigan, Ann Arbor, 2009. The authors consider the effects of positioning in-vehicle devices in different vehicle locations, because nonideal loca- tions may add to driver distraction. Both visual and motor demands of nonessential tertiary tasks were considered simul- taneously by means of using a touch-screen monitor to per- form the tertiary task and varying the location of the monitor. Driving simulator participants were instructed to focus their efforts primarily on following a lead vehicle that was sporad- ically speeding up and slowing down; additionally, they were instructed to perform the tertiary task on the touch-screen monitor. Performance on the primary task (following the lead vehi- cle) was worse for all participants who performed the sec- ondary task compared with those who did not, regardless of touch-screen position. Performance on the secondary task, however, predictably varied depending on the position of the touch-screen. More difficult positions (where participants had to reach farther and look farther to the side of their normal line of sight) resulted in longer times to completion for the sec- ondary task and more frequent glances to the monitor than when the monitor was in an ideally located position. It is therefore concluded that in-vehicle devices that require driver interactions should be placed closer to the driver, because placing them farther away takes more attention off the road. Kircher, K. and C. AhlstrÃ¶m, âIssues Related to the Driver Distraction Detection Algorithm AttenD,â First Inter- national Conference on Driver Distraction and Inattention, Gothenburg, Sweden, Sep. 28â29, 2009. Most applications of driver support systems attempt to help the driver when a critical safety event is unavoidable. Improve- ments to FCWS, LDWS, and others could be found by pro- viding earlier warnings, although this would further increase the number of false alarms. On the other hand, the systems could be improved by taking driver state into account and acting only when an increased risk presents itself. Options for this latter approach could include pressure-sensitive steering wheel sensors, breath analyzers, live video feeds, or automatic eye tracking. Because eye tracking can now be done unobtrusively, the authors chose this approach and described AttenD, an algo- rithm for detecting visual distraction in real time based on sustained single or repetitive glances away from the road. Essentially, AttenD uses a 2-s time buffer that depletes as drivers look away from the road and replenishes when eyes come back to the road. When the buffer is empty, the driver is classified as distracted. The buffer takes into account necessary acts of driving, such as checking mirrors or the speedometer, which do not count against the buffer until after a 1-s grace period. Logical applications of AttenD involve issuing warnings to drivers determined to be in a distracted state. One possibil- ity is to warn drivers every time they use up their 2-s buffer, so as to train the driver not to look away from the road so often. Otherwise, the distraction information could be fused with other in-vehicle systems such as FCWS and LDWS to more accurately identify when safety-critical events are probable. In contrast to the former option, using AttenD to minimize false warnings of other safety systems will not train the driver to focus his or her attention on the road and may actually have the opposite effect, teaching the driver to trust other systems to activate warning messages when dire situations arise. Lee, J.D. and J.D. Hoffman, âCollision Warning Design to Mitigate Driver Distraction,â SIGCHI Conference on Human Factors in Computing Systems, Vienna, Austria, Apr. 24â29, 2004. The authors evaluated what type of warning delivery sys- tem is the most effective and accepted in warning distracted drivers. Experiments were conducted requiring participants to interact with an in-vehicle e-mail system while a FCWS alerted drivers to a braking lead vehicle. Concerning alert strategy, graded warnings (where warn- ing intensity is proportional to threat severity) were better received than single-stage warnings (where warnings were issued in an identical fashion when a predetermined severity threshold was crossed). Concerning alert modality, haptic messages (e.g., vibrating seats) were more accepted by drivers than auditory messages. Lee, J., M. Reyes, Y. Liang, and Y.C. Lee, SAfety VEhicles Using Adaptive Interface Technology: Algorithms to Assess Cognitive Distraction, Volpe National Transportation Systems Center, Cambridge, Mass., 2007. To proactively address the issue of driver distraction, a program known as SAfety VEhicle(s) using adaptive Inter- face Technology (SAVE-IT) was created to identify effec- tive countermeasures to distraction and improve on existing safety warning systems. This paper describes Task 5 of the SAVE-IT program, which attempted to develop an algorithm capable of identifying declines in driving performance as a result of cognitive distraction.
The researchers developed models that accurately detected cognitive distraction 75% to 95% of the time. Findings sug- gested, among other things, that listening to IVIS information is less demanding than responding to questions about it; cog- nitive and visual demands are additive; and cognitive distrac- tion is multifaceted (i.e., distinct types of cognitive distraction have different impacts on driving performance). Lee, J.D., M.L. Ries, D.V. McGehee, and T.L. Brown, âCan Collision Warning Systems Mitigate Distraction Due to In-vehicle Devices?â NHTSA Driver Distraction Internet Forum, July 5âAug. 11, 2000. Because driver inattention/distraction is a contributing factor in more than 60% of all vehicle rear-end collisions, this study looked at the effectiveness of a rear-end collision avoidance system, better known today as a FCWS. A driving simulator was used to determine how well drivers, distracted or otherwise, could avoid an impending collision with FCWS assistance, utilizing either early or late warnings. The experiment found that the cognitive demands (e.g., speaking into a phone or two-way radio) that do not take a driverâs hands off the wheel or eyes off the road still pose a serious risk nearly equal to that from visual distractions. How- ever, both of these risks can be effectively mitigated with early warnings from an FCWS. The authors suggest that in-vehicle devices that distract attention away from the road be integrated or coordinated with warning systems that will detect distrac- tion and signal imminent danger (e.g., issue earlier warnings if the driver is on the phone). An obvious caveat, however, is that drivers could become passive and overreliant on warning systems to detect critical safety events, increasing a willing- ness to engage in distracting activities and lowering vigilance. Lerner, N., J. Singer, and R. Huey, Driver Strategies for Engaging in Distracting Tasks Using In-vehicle Technolo- gies, Report No. HS DOT 810919, National Highway Traf- fic Safety Administration, Washington, D.C., 2008. The purpose and findings of this study were cited earlier. Based on the studyâs findings, the authors developed a matrix that mapped 36 findings to possible countermeasures for each respective finding. Countermeasure options included ideas related to public education and safety campaigns, driver training, user interface design, functional lock-out technology, and interactive control (i.e., Driver Assist) technology. Llaneras, R.E., NHTSA Driver Distraction Internet Forum: Summary and Proceedings, National Highway Traffic Safety Administration, Washington, D.C., 2000. A virtual online conference was held to assess the dangers associated with the massive growth in the availability of in-car devices (e.g., cell phones, navigation systems, wireless Inter- net, information systems, entertainment systems, and night 22 vision systems). Benefits and safety risks are evaluated, along- side ways to measure distraction and implement user-friendly design features or solutions. Participants took issue with systems using poorly labeled and difficult to reach multi- functional controls. From a structural standpoint, suggestions for improvement included the use of standardized steering wheel-mounted controls, graphic icons, integrated designs, and easy-to-reach, easy-to-distinguish buttons. Concerning usability, participants discussed hands-free options, lock-out functions, and speech- based or voice recognition technologies, although this was a topic of debate, because cognitive demands present similar (although somewhat lower) levels of distraction as visual or motor demands. Although the complete automation of vehicles would gen- erate an obvious solution to the driver distraction problem, the foreseeable future will only allow a partial realization of driverless automation technology. Two recognizable options for the present include vehicle systems that provide âaddi- tional eyes and earsâ to the driver (e.g., collision warning sys- tems) and driver assistance systems that assume some limited driving tasks (e.g., adaptive cruise control). Llaneras, R.E., J.P. Singer, and R. Bowers-Carnahan, Assess- ment of Truck Driver Distraction Problem and Research Needs, Report No. DOT HS 809883, National Highway Traf- fic Safety Administration, Washington, D.C., 2005 As mentioned, multifunctional devices appear to be par- ticularly common in the industry, and having systems that offer both text messaging and driver communication func- tions top the list, both for OEM and aftermarket products. As proactive steps toward limiting distraction, many systems are customizable so that fleet safety managers can decide if they want to (completely or partially) lock out certain functions or, in the case of messaging systems, send messages with dif- ferent levels of urgency and only allow the driver to read emergency messages while the vehicle is in motion. Despite these options, it varies widely between and even within fleets whether these lock-out capabilities are used. Finally, inter- views revealed that banning technology is viewed as imprac- tical and unwarranted, whereas the effectiveness of policies prohibiting the use of in-vehicle devices while driving is also questionable. Interviewees argued that the effectiveness of these policies was contingent on enforcement and consistently applied rules (with penalties for noncompliance), whereas the key to limiting distraction from in-vehicle devices rested on enhanced designs and interfaces and reasonably applied restrictions and lock outs. NHTSA, An Investigation of the Safety Implications of Wire- less Communication in Vehicles, National Highway Traffic Safety Administration, Washington, D.C., 1997. The authors of this study recognized that the use of a cell phone while driving may contribute to collisions. However,
23 it was stated that it is both the physical movement associated with dialing and holding a phone as well as the cognitive processes that coincide with the phone conversation. It was also proposed that hands-free devices may assist drivers, but may lead to longer conversations and the increased likeli- hood of a crash. Also, the key factor is not just using a cell phone, but driver inattentiveness while driving. This study makes several key suggestions to improving the safety of drivers who use cell phones. The authors make it clear that cell phone-related accidents cannot decrease by simply banning the devices. Instead, in-vehicle communica- tion systems could be developed that allow the user to wire- lessly communicate with fewer distractions. In addition, some of the other recommendations included: â¢ Enforcing inattentive behavior issues, â¢ Improving the range of cell phone-related research to more specifically define the problem, â¢ Broadening consumer education about using a cell phone while driving, and â¢ Developing the most ideal in-vehicle communication systems using the National Advanced Driver Simulator. Research and Innovative Technology Administration (RITA), âIn-vehicle Technology to Address Distracted Driving,â Sym- posium on Prevention of Occupationally-Related Distracted Driving, Johns Hopkins Education and Research Center for Occupational Safety and Health, Laurel, Md., Apr. 18, 2011. Panelists from the consumer electronics industry described how, while technology can distract drivers (e.g., cell phones, entertainment systems, and navigation and information sys- tems), it can also be used to help mitigate distraction. Tech- nology of the latter classification includes lock outs (e.g., not allowing incoming calls, texts, or e-mails while the vehicle is in motion), warning notifications (i.e., when a high level of risk is detected), and other advances that reduce the amount of necessary interaction (whether visual, manual, or cognitive) drivers must engage in with on-board systems or devices. A critical attribute of new, seemingly useful technologies is how much driver workload they require. Human factors specialists need to keep best practices in mind when design- ing new technologies so that they do not overload the driver and increase the possibility of distraction. Certain types of distraction (e.g., searching for street signs) can be circumvented with hardware (GPS unit) and software (text to speech). Similarly, hands-free devices are intended to prevent distractions that would take a driverâs hands off the wheel; this technology can incorporate ear buds, Blue- tooth, steering wheel controls, and/or voice recognition soft- ware. Essentially, technology is moving in the direction of faster touch (e.g., predictive text, next word prediction, logic and algorithms), less touch (hybrid text and speech entry), or no touch (speech command and control). Vollrath, M. and I. Totzke, In-vehicle Communication and Driving: An Attempt to Overcome Their Interference, Cen- ter for Traffic Sciences, University of Wuerzburg, Germany, 2000. Multiple Resources Theory dictates that in-vehicle com- munications using different channels (i.e., manual operations, visual or auditory information processing) will differentially impact driving performance. The authors performed a mixed betweenâwithin subject driving simulator experiment to demonstrate that all three of these tertiary communication tasks cause decrements in driving performance. However, performance is at its worst with the manual operation task, followed by the visual information processing task and the auditory information processing task. Based on these findings, the authors suggested that infor- mation should be presented to drivers acoustically whenever possible. Visual output should be avoided or else be accom- panied by a driver assistance system that ensures that the vehicle maintains its lane position (e.g., LDWS). Finally, unnecessary manual operations are by far the least desir- able component in terms of distraction and risk, most likely because this category typically contains some extent of visual information processing. If motor actions are required, they should be accompanied by a driver assistance system that maintains both lane position and following distance (e.g., LDWS and FCWS). Volpe National Transportation Systems Center and Research and Innovative Technology Administration, Technology Applications for Traffic Safety Programs: A Primer, Report No. DOT HS 811 040, National Highway Traffic Safety Administration, Cambridge, Mass., 2008. The authors reviewed emerging digital and communica- tion technology that is either currently or soon to be available to improve highway safety. Highlighted traffic safety tech- nologies include those that provide information and services to drivers, traffic operations agencies, emergency services per- sonnel, and law enforcement professionals. Specifically, vehi- cle to driver, vehicle to vehicle, vehicle to and from roadside, and vehicle to and from traffic and emergency call centers are all discussed. The report emphasizes the importance of considering the HMI when developing new safety technologies, so that the right balance is struck between delivering desired infor- mation and minimizing driver distraction. For instance, care- ful consideration must be given to the placement of safety devices and the manner of information delivery. World Health Organization, Mobile Phone Use: A Growing Problem of Driver Distraction 2011 [Online]. Available: www. who.int/violence_injury_prevention/publications/road_traffic/ en/index.html.
In this report, the challenges of assessing the extent of the distracted driving problem are noted, given the differences in police reporting and crash data coding related to distracted driving. As to countermeasures, the need for extended public awareness campaigns are seen as important to increase pub- lic understanding of the risks of driving while distracted. The potential value of technological interventions, such as work- load managers and LDW, is noted but viewed as having a limited impact at this time. The report concludes by issuing a call to governments to be proactive in setting policy, using the current state of knowledge, as failure to act now could make it more difficult to address the issues at a later point. Zhang, H., M. Smith, and R. Dufour, A Final Report of SAfety VEhicles Using Adaptive Interface Technology: Visual Distraction, Volpe National Transportation Systems Center, Cambridge, Mass., 2008. This paper describes Task 7 of the SAVE-IT program, which focused on methods for identifying decrements in driving performance owing to visual distraction. Although eye-based measures are slightly more accurate in identify- ing distraction than head-based measures, the latter option is more practical; that is, the necessary sensors for detecting eye gaze movement are more expensive and suffer from cer- tain limitations (e.g., interference from eyewear), whereas head-movement sensors are cheaper and easier to implement. Because most severe visual distractions are likely to be cap- tured by head movement sensors (i.e., sustained eye gazes that are farther off to the side), the researchers suggested moving forward with this type of technology. ZoomSafer Inc., Beyond Telematics: Extending UBI Data to Include Mobile Phone Use While Driving, 2011b [Online]. Available: http://zoomsafer.com/resources/#1. ZoomSafer describes both an active and passive approach to cell phone use within a vehicle, in the context of UBI tech- niques. The active approach consists of UBI software resident on a smartphone (an âappâ), which connects with a UBI device in the insuredâs vehicle. The smartphone is automatically deactivated when the vehicle is in motion, and incoming texts and messages are automatically responded to by the applica- tion to indicate the user is driving. The passive approach con- sists of integrating UBI data (including events during driving) with billing records from the telecommunications carrier for the cell phone, so that events can be correlated with cell phone use. Although the active approach requires a smartphone, the passive approach works with any phone. OPERATIONAL STRATEGIES AND RECOMMENDED PRACTICES A wide range of operational practices have been studied and put into place to address distracted driving and some recom- mended practices have emerged. Studies of most relevance to 24 this project are summarized here. The issues can be grouped into the following topics. Examination of Company Safety Practices Hickman et al. (2007) examined behavior-based safety pro- grams common in some industries, but which have not seen wide use within the trucking industry. Surveys of motor carrier safety managers indicated that driver observation and feedback programs, plus ride-alongs, are most important. Short et al. (2007) examined the means of mitigating dis- tracted driving through an organizationâs safety culture. For instance, a strong safety culture may have internal definitions and messages related to distracted driving, which may be part of training and employee communications. The authorâs key point for this concept was that focus on the safety message must exist from top to bottom within the organization. Simi- larly, Network of Employers for Traffic Safety (NETS) (2011) describes a panel discussion of model distracted driving pro- grams, which involved representatives from major private fleets. Panel members also discussed the importance of top management buy-in plus clearly communicating policies, including consequences for disobeying. They also reported on safety videos and post-incident coaching tools and met- rics as being useful. Lueck and Murray (2011) interviewed safety executives from major carriers and identified the fol- lowing common attributes of effective safety management: well-defined policies and strategies, engaged safety direc- tors, a willingness to test new methods and systems (such as active safety), training (and remedial training for problem drivers), and direct involvement in developing company safety strategy. Employees: Hiring, Training, and Well-Being ATAF (1999) examined the safety practices of award-winning carriers and noted the following key factors: having satisfied employees, hiring the right people, training and monitoring these individuals, and using quality control measures. Mejza et al. (2003) identified 148 high-performing carriers with respect to safety and surveyed them as to their safety manage- ment programs and practices. Regardless of fleet size, they pointed to extensive hiring and training practices, multiple methods for evaluating those practices, and driver rewards for positive safety records. Knipling et al. (2003) examined 28 safety management techniques, the most common of which were tracking of driverâs incidents, violations, and crashes; regular vehicle inspection and maintenance; and hiring based on safety criteria. They also identified four safety opportunity areas: motor carrier wellness programs, predicting crash rates based on past behaviors, behavioral safety management, and safety management professionalism. In a TRB synthe- sis report, Staplin et al. (2005) examined driver training pro- grams that have the greatest potential for improving safety. Several recommended practices were noted, including mini- mum industry requirements for entry-level drivers, the use of
25 driving simulators and skid pads in training, and multimedia and video techniques. Cell Phone Prohibition Policies In a highway safety guide prepared for states, NHTSA (2011) gave cell phone bans a low effectiveness rating based on studies showing that cell phone use rates revert to the base- line after a year unless there is sustained enforcement of these laws. However, the Governors Highway Safety Asso- ciation (GHSA) (2011) noted that cell phone bans, while their effectiveness is not entirely clear, do have some long- term effect. They called on states to enforce cell phone laws once passed and to establish assistance programs to help employers implement effective policies. ZoomSafer (2011a) conducted a general survey of 500 busi- ness managers and noted that, although 32% of the companies have had instances of crashes linked to driver distraction, only 62% have cell policies, with 53% actually enforcing it. For trucking, depending on operational focus, the occur- rence of distraction-related crashes was 41% to 53%, with 71% to 83% having policies on cell phone use, and 59% to 71% actively enforcing the policy. Hickman et al. (2010) examined truck and bus driver data from a DriveCam and found that truck and bus drivers operating with a company prohibition on cell phone use were 0.83 times less likely to use the device, whereas driving in a state that prohibited cell phone use while driving had no effect. Section Summary At the company level, clarity within the organization as to safety culture and clear messages are important. At the employee level, careful hiring, thorough training, attending to wellness, driver rewards, and remedial practices when inci- dents occur are all important parts of the puzzle. And, while the value of laws prohibiting cell phone use is not clear, at least one study has demonstrated that company prohibitions on cell phone use do inhibit a driverâs use of the devices. Citation Summary ATAF, Safe Returns: A Compendium of Injury Reduction and Safety Management Practices of Award-winning Carriers, American Trucking Associations Foundations, Alexandria, Va., 1999. This study analyzed interview and survey responses of safety managers in outstanding TL, LTL, private, and special- ized fleets to identify various management âtools for success.â Because safe operations feed into financial stability, produc- tivity, and customer and employee retention, all aspects of operations were examined: hiring; training, and supervi- sion; bonus and awards programs; maintenance and equip- ment; safety meetings; work environment; and accident investigations. Conclusions included the finding that satis- fied and committed employees are one of the keys to safety, and employees would therefore be included in important decisions and rewarded or recognized for their performance. Safety begins with hiring the right people, training them suf- ficiently, supervising or monitoring them to ensure proper performance, and using quality control program to mini- mize the potential for safety incidents. Governors Highway Safety Association, Distracted Drivingâ What Research Shows and What States Can Do, 2011 [Online]. Available: www.ghsa.org. This report summarizes distracted driving research to inform states as they consider distracted driving counter- measures, concentrating on distractions produced by cell phones, texting, and other electronic devices. The report con- cludes that cell phone use increases crash risk, but there is no consensus on the degree of increase, and that conclusive evidence does not exist as to whether hand-held cell phone use is riskier than hands-free. As to countermeasures, the report found that laws banning hand-held cell phone use are effective initially even though the effect lessens over time; however, the laws do appear to have some long-term effect. At the same time, it noted there is no evidence that cell phone or texting bans have reduced the number of crashes. The reportâs recom- mendations include that states enact cell phone and texting bans for novice drivers, existing cell phone and texting laws be enforced, public awareness programs be implemented, and states assist employers to develop and implement distracted policies. Hickman, J., R. Hanowski, and J. Bocanegra, Distraction in Commercial Trucks and Buses: Assessing Prevalence and Risk in Conjunction with Crashes and Near-crashes, Report No. FMCSA-RRR-10-049, Federal Motor Carrier Safety Administration, Washington, D.C., 2010. This study analyzed 12 months of naturalistic truck and bus driver data provided by DriveCam, whose onboard safety monitoring systems record videos of drivers and data from kinematic sensors on safety-related events. One data set included data whereby kinematic sensors were triggered by nonsafety triggered events (e.g., driving over train tracks) to serve as a baseline in calculating odds ratios. Truck and bus drivers operating under a fleet cell phone policy were 0.83 times less likely to use a cell phone, whereas driving in a state that prohibited cell phone use while driving had no effect on driversâ decisions to use their phones behind the wheel (odds ratio = 0.97, ns). Hickman, J., R. Knipling, R. Hanowski, D. Wiegand, R. Inderbitzen, and G. Bergoffen, CTBSSP Synthesis 11: Impact of Behavior-Based Safety Techniques on Commercial
Motor Vehicle Drivers, Transportation Research Board of the National Academies, Washington, D.C., 2007. This synthesis report documents various Behavior-Based Safety (BBS) strategies that reduce risky driving behaviors in CMV drivers. Several studies have reported that specific driving behaviors are significant contributing factors in many crashes. Motor carrier safety managers were surveyed to obtain information on which strategies were currently being used, as well as their opinions on the effectiveness of those strategies. Findings from the extensive literature review and survey indi- cated that although BBS techniques have been widely used in other industrial workplaces, comprehensive BBS programs have not been extensively used in the trucking industry. The lack of more complete programs is most likely the result of the solitary nature of the occupation and the difficulty in observ- ing accurate, unbiased, safety-critical behaviors. The majority of survey participants indicated that some type of observation technique was used to assess driversâ behavior, including peer observation and feedback (63%), ride-alongs (59%), covert observations (37%), and self- observation (32%). The highest rated BBS technique by respondents was a targeted training approach and education programs directed at specific driving behaviors. Knipling, R., J. Hickman, and G. Bergoffen, CTBSSP Syn- thesis 1: Effective Commercial Truck and Bus Safety Man- agement Techniques, Transportation Research Board of the National Academies, Washington, D.C., 2003. This synthesis report provides a summary of safety man- agement techniques in commercial truck and bus transporta- tion. Twenty safety problem areas and 28 safety management techniques were identified through a literature review, dis- cussions and interviews with industry experts, and sugges- tions from the TRB synthesis panel. Problem areas included both driver and vehicle issues, and safety management tech- niques ranged from driver recruiting and selection to advanced safety technologies. A questionnaire was distributed to fleet safety managers and other industry safety experts through several trade asso- ciations and industry-related professional organizations to assess their relative importance. The top three problem areas for safety manager respondents were found to be at-risk driving behaviors (e.g., speeding and tailgating), high-risk drivers (all causes combined), and driver health and wellness. The three most common management techniques practiced by safety managers were continuous tracking of driversâ crashes, inci- dents, and violations; regularly scheduled vehicle inspec- tions: and maintenance and hiring based on criteria related to driver crash, violation, or incident history. Each of these 26 techniques was practiced by 90% or more of the safety man- ager respondents. Based on the survey results and reviewed literature, four âsafety opportunity areasâ were selected for further research and discussion: driver health, wellness, and lifestyle; high- risk drivers; behavioral safety management; and safety man- agement professionalism. Several opportunities to improve safety were identified for each area: â¢ Driver health, wellness, and lifestyle â Motor carrier wellness programs. â¢ High risk drivers â Predicting crash rate based on past behaviors, and â Intervention programs. â¢ Behavioral safety management â Self-management programs, â Driver incentive programs, â Safety placards, and â On-board recording. â¢ Safety management professionalism â Certification of fleet safety practices, and â Certification of safety managers. Lueck, M.D. and D.C. Murray, Predicting Truck Crash Involvement: A 2011 Update, American Transportation Research Institute, Alexandria, Va., 2011. Recognizing the responsibilities and roles that motor carriers can play in managing driver behavior, ATRI inter- viewed safety executives from major reputable carriers to identify effective industry strategies that could potentially help prevent and mitigate dangerous driver behaviors. The interview questions were designed to solicit information on safety programs, tools, and training strategies that effectively target identified problem behaviors and events. Based on surveys and in-depth interviews conducted with these safety directors, it became clear that safety-oriented trucking companies had several common attributes. These included: â¢ Clear, documented, and well-distributed policies and strategies relating to specific driver behaviors and events; â¢ Accessible and engaged safety directors and managers; a willingness to test and/or use different training tools and onboard safety systems; and â¢ Direct involvement in the development or customiza- tion of company safety programs and policies. During the interview process each of the carriers also emphasized that proactive safety measures, such as initial and orientation and sustainment training, are key lynchpins
27 to ensuring that negative safety incidents do not occur. The value of these safety programs, however, must be comple- mented by remedial safety training programs that mitigate a problem driver behavior after a negative safety incident has occurred. Mejza, M.C., R.E. Barnard, T.M. Corsi, and T. Keane, Best Highway Safety Practices: A Survey of the Safest Motor Carriers About Safety Management Practices, Fed- eral Motor Carrier Safety Administration, Washington, D.C., 2003. This study used federal safety ratings to identify 148 high- performing carriers. Researchers then surveyed these compa- niesâ safety management programs and policies, including detailed questions about carrier, driver, and vehicle-related practices. Most questions centered on hiring, training, and supportive or motivational activities. Some of their survey findings were disaggregated by fleet size into three cate- gories: small (1â24 trucks), medium (25â94 trucks), and large (95+ trucks); however, they all pointed toward extensive hiring and training practices, multiple methods for evaluat- ing those practices, and a wide array of rewards to encour- age drivers to have positive safety records. For instance, more than 90% of good carriers reported verbally praising safe drivers, whereas 72% used public recognition and 66% used cash rewards. Network of Employers for Traffic Safety (NETS), âEle- ments of Model Distracted Driving Programs,â Sympo- sium on Prevention of Occupationally-Related Distracted Driving, 2011. NETS panel members (e.g., ExxonMobil, Coca-Cola, and Johnson and Johnson) representing 52,000 fleet vehicles and 1 billion miles driven discussed key topics related to address- ing distracted driving, including cell phone use policies, imple- mentation and sustainability, technology, and critical success factors. From a 2010 NETS benchmarking report, 93% of NETS members have a cell phone policy in place, 40% have a total ban in place, 57% permit only hands-free use, and 2% ban only texting. When policy violations occur, 67% of NETS members discipline the driver and 21% terminate him or her. Panel members discussed the importance of clearly com- municating distracted driving policies so that all employees are educated and fully aware of the issue, as well as conse- quences for disobeying the policy. Buy-in and total support from top management is crucial, and good behaviors must be reinforced to create a strong safety culture. Some useful strategies include using safety videos and safety information available on the companyâs website. Additionally, compa- nies can be prepared to deal with incidents by having a post- incident coaching tool (or metric) that addresses potential distraction issues that could have played a role in the safety- critical event. NHTSA, Countermeasures That Work: A Highway Safety Countermeasure Guide for State Highway Safety Offices, 6th ed., National Highway Traffic Safety Administration, Washington, D.C., 2011. This guide was created as a reference to help State Highway Safety Offices select empirically proven counter- measures when addressing major highway safety problem areas, including distracted driving. As part of the analysis the authors describe the use, effectiveness, costs, and imple- mentation time required for each prospective countermeasure, citing the most recent and accurate literature, where relevant. Empirical support for the ratings listed here can be found in NHTSAâs guide (see Table 3). For instance, cell phone laws are given a poor rating because studies show cell phone use among drivers returning to baseline levels within a year of a law going into place, unless the law was accompanied by sustained, tough enforcement targeting violators. Likewise, general laws and company policies are ineffective if they simply send a generic âstay alertâ message. Drivers already know what behaviors are not smart, but they will continue to occasionally engage in them unless they are strictly moni- tored and held accountable. Short, J., L. Boyle, S. Shackelford, B. Inderbitzen, and G. Bergoffen, CTBSSP Synthesis 14: The Role of Safety Culture in Preventing Commercial Motor Vehicle Crashes, Transportation Research Board of the National Academies, Washington, D.C., 2007. The authors reviewed methods for improving safety cul- ture through changes in an organizationâs safety policies, values, attitudes, and norms. Although the safety culture con- cept is much broader in scope than individual safety issues, the problem of distracted driving can likely be mitigated through an organizationâs safety culture. The research indicated that an organization with a strong safety culture will identify distracted driving issues through an awareness of organizational beliefs and behaviors and through knowledge of safety performance data and informa- tion. Once identified, aspects of distracted driving will likely be addressed in several ways within a safe culture. First, an organization with a strong safety culture might create internal definitions and messages related to the dis- tracted driving problem and disseminate such information throughout the company. The distracted driving message may be part of initial and ongoing training within the organi- zation, and might also be found as part of regular safety mes- sages that are communicated to employees. It is also likely,
within a strong safety culture, that members of a trucking companyâs leadership disseminate information and messages to drivers on the importance of preventing distracted driving situations. The message should be delivered through other areas of the organization as well; for example, dispatchers may ask drivers if bills have been paid prior to extensive travel as a means to avoid cognitive distractions. Thus, the key point of this concept is that a safety message, such as one that addresses distracted driving, flow from the very top of the organization and be pervasive throughout the organization. Staplin, L., K. Loccoco, L. Decina, and G. Bergoffen, CTBSSP Synthesis 5: Training of Commercial Motor Vehicle Drivers, Transportation Research Board of the National Academies, Washington, D.C., 2005. This synthesis report focuses on several training tools and techniques used in existing driver training programs and identifies those that appear to have the greatest potential for improving CMV safety. A review of available literature was done to pinpoint which training techniques work (and which do not) to adequately train CMV drivers to perform in vari- ous situations. Information was also obtained from several truck driving schools and truck and bus companies to supple- ment the literature findings. 28 Several recommended practices for improving driver safety performance were identified in the report, including: â¢ Implementing industry-wide use of standards put for- ward by the Professional Truck Driving Institute as a minimum requirement for entry-level drivers and for the certification of driver trainers. â¢ Requiring finishing training for first seat (solo) drivers. â¢ Substituting multimedia instruction materials to better engage students and reduce training costs through dis- tance learning. â¢ Introducing or expanding the use of driving simulators. â¢ Expanding the use of skid pads to train beginning drivers about stopping distances under different load configu- rations; to use different brake systems [including all anti-lock brake (ABS), mixed ABS, and non-ABS], and to experience the consequences of driving on a wet sur- face for handling and stopping the vehicle, including skid control. â¢ Employing videos and testimonials by experienced drivers to provide entry-level trainees with a realistic orientation to health, wellness, and lifestyle issues. ZoomSafer, Inc., Measuring Corporate Attitudes About Employee Distracted Driving, 2011 [Online]. Available: TABLE 3 EXCERPT FROM NHTSA HIGHWAY SAFETY COUNTERMEASURE GUIDE
29 http://ZoomSafer.com/assets/Whitepapers/Survey-Results- White-Paper.pdf. ZoomSafer, an organization that develops software to prevent distracted driving, surveyed 500 North American business managers to identify corporate attitudes and best practices related to mobile phone use among drivers. From the overall sample, which included long-haul and short-haul trucking companies; construction companies; utility compa- nies; taxi, limo, and bus companies; sales and service com- panies; home and business services; and government, they found that 32% of all companies have knowledge or evi- dence of their employees having vehicle crashes as a result of cell phone distractions. Despite this, only 62% of the compa- nies had a written cell phone policy in place and only 53% of companies with a policy actually enforced it, with 61% dis- ciplining employees after a crash or incident and only 2% proactively utilizing technology to manage compliance. When focusing solely on trucking (long-haul and local/ short-haul), findings showed higher rates of cell phone-related crashes (53% and 41%, respectively), but also higher levels of policy implementation (71% and 83%, respectively) and enforcement (71% and 59%, respectively).