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6 CHAPTER TWO LITERATURE REVIEW A literature review was conducted to identify and summarize distraction, driver tasks, driver workload, distraction counter- findings relating to commercial truck and bus driver distrac- measures, safety culture, safety climate, crash reduction, driver tion research conducted thus far. The literature reviewed in training, and driver supervision. this task consisted of reports and analyses available from aca- demic, government, and industry sources. The review was NATURE OF DISTRACTED DRIVING conducted primarily through Internet searches of online data- bases, publications, and other industry resources. The reports A wide range of studies have addressed distracted driving identified have been summarized and are described in the and it continues to be a very active research topic. Studies of following sections: most relevance to this project are summarized here for the general driver population; the next section addresses commer- The nature of distracted driving. cial vehicle drivers specifically. The issues can be grouped Driver tasks unique to professional drivers. into the following topics. Countermeasure technologies and their effectiveness. Operational strategies and recommended practices. Detailed Definition of Distracted Driving The primary focus of this review was to examine and fur- ther understand driver distraction and its impact on commer- Pettitt et al. (2005) developed a comprehensive definition of cial vehicle safety. Because available truck and bus technology distraction that accounts for all key components. In this def- capabilities have been changing dramatically since the mid- inition, driver distraction occurs: 1990s, the literature cited herein was published since that time. When a driver is delayed in the recognition of informa- tion necessary to safely maintain the lateral and longitu- LITERATURE REVIEW METHODOLOGY dinal control of the vehicle (the driving task) (Impact). Owing to some event, activity, object, or person, within Literature searches were performed using websites, aca- or outside the vehicle (Agent). demic databases, books, trade press publications, and arti- When a device that compels or tends to induce the driver's cles. The following databases were used to conduct the shifting attention away from fundamental driving tasks reviews: (Mechanism). By compromising the driver's auditory, biomechanical, Transportation Research Information Database (TRID): cognitive, or visual faculties or combinations thereof The largest online bibliographic database of transporta- (Type). tion research, containing more than 900,000 records of published research. Problem Extent--How Does Distracted Driving Business Source Premier: Features the full text for more Relate to Crash Risk? than 2,200 journals. Full text is provided back to 1965, and searchable cited references back to 1998. McEvoy et al. (2005) examined crash data for cell phone use LexisNexis: Provides access to many popular articles before a crash and found that crash likelihood was four times as well as some scholarly works. There is also access to greater if drivers had used their phones in the minutes before congressional records, court decisions, and government a crash. Backer-Grndahl and Sagberg (2009) noted that, statistical reports. based on more recent crash data, driver distraction plays a role in between 8% and 25% of crashes. ZoomSafer (2011a) These databases were searched using a variety of topic-related conducted a general survey of 500 business managers and key words and phrases, often in combinations to improve noted that, although 32% of all companies surveyed have had focus. Key words included commercial motor vehicles, truck- instances of crashes linked to driver distraction, trucking had ing, motor coaches, commercial drivers, safety, safety man- a higher occurrence (between 41% and 53% of companies) agement, risk management, operations management, driver of distraction-related crashes.

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7 Traditional Distraction versus Electronic Devices a distraction task; however, they also braked harder, indicat- ing individuals in these conditions may stop sooner rather Backer-Grndahl and Sagberg (2009) factored in exposure than later when a distraction is present. However, Morgan rates to determine the relative crash risk of various types of et al. (2011) reviewed driving performance parameters as they distraction. Looking at billboards, searching for addresses, relate to distraction and found there were more lane devia- and moving objects in automobiles were identified as having tions, less consistent and slower speeds, and poorer responses the highest relative risk. Molino et al. (2009) reviewed liter- to emergencies. The study also noted that drivers allocate part ature addressing the effects of electronic billboards and found of their cognitive resources to the secondary task, resulting in a 5 to 1 ratio of studies showing negative effects. Based on a a form of "tunnel vision" such that they do not scan the road driver survey, NHTSA (2010) identified the most common scene as well. Rakauskas et al. (2004) employed a driving forms of distraction to be talking to passengers, radios/music, simulator to assess the relationship between distraction and eating and drinking, and using a cell phone (in that order). three levels of conversation difficulty on a cell phone. Review- Klauer et al. (2010) analyzed naturalistic driving data from ing speed, lateral tracking, crash avoidance, and mental work- the 100-car study to analyze the crash risk of simple, moderate, load it was found that speed was, on average, slower during and complex secondary tasks. Although simple tasks had no conversation. No significant decline in safety measures was effect, moderate tasks such as talking and listening on a hand- noted for any of the various levels of conversation difficulty; held device increased crash risk by a factor of 1.3. Complex however, the researchers concluded that this relationship tasks such as dialing a hand-held device increased risk by a fac- could be examined further. tor of 2.1. Another survey asked drivers to assess the degree to which distraction relates to crash involvement. The results Smith et al. (2005) examined a variety of visual tasks to were found to have some consistency with an analysis of the determine which types of visual stimuli present a threat. The 100-car data: 30% of the time a situation outside the vehicle study revealed that, as the visual task complexity increased, was responsible for the distraction, whereas objects inside the the inter-vehicle distance from the vehicle ahead increased; car were the cause 20% of the time. Among other factors, cell additionally, given similar eye glance patterns of two sec- phone use was responsible for 2% of the distractions. ondary tasks, longer lasting secondary tasks present a greater crash risk. They concluded that, assuming similar eye glance Rakauskas and Ward (2005) examined the level of driver patterns, as the time to complete a secondary task increases a distraction associated with cell phone use, alcohol impair- safety threat becomes more imminent. 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) Are Hands-Free Devices Safer Than Hand-Held Devices? describes a NHTSA survey of distracting behaviors across 4,010 drivers. Looking for an object inside the car was the The World Health Organization (WHO) (2011) examined a most common answer; only 2% of the responses dealt with wide range of literature to conclude that, although using a technology, noted as being primarily radio. For participants mobile phone is detrimental to driving, it is not clear that involved during in a crash in the previous five years, only hands-free phones are safer. Additionally, in a review of 0.6% attributed the cause to cell phone use. Cades et al. four experimental studies (Burns et al. 2002; Consiglio et al. (2011) cites multiple sources to argue that eyes-on-road dis- 2003; Pattern et al. 2004; Trnros and Bolling 2005, 2006) tractions impair the driver, whether they relate to electronic pertaining to cell phone conversations during driving-related devices or conversations with passengers. activities, Ishigami and Klein (2009) generally found that both hands-free and hand-held phones, as compared with the When Do Drivers Choose to Engage in experimental controls, impaired detection reaction times but Distracting Behaviors? not vehicle lane keeping tasks. This meta-analysis of cell phone research also found that, particularly with hands-free Lerner et al. (2008) examined when drivers are willing to take phones, drivers slow down when conversing on a cell phone a risk and engage in nondriving-related tasks. The study (Ishigami and Klein 2009). Ishigami and Klein (2009) attrib- found their willingness to do this is related more to task issues uted this slowing effect to a compensatory behavior for main- and lifestyle than driving issues, and also noted that drivers taining performance for keeping the vehicle in the lane. A were unlikely to plan ahead for either technology usage or more inclusive meta-review of 30 experimental and epi- delay usage until the driving demands were relatively low. demiological studies, including the 10 studies reviewed by Ishigami and Klein (2009), found similar trends (National How Does Distraction Relate to Safety Council 2010). In the McEvoy et al. (2005) study, Driving Performance? both hands-free and hand-held phones were determined to increase risk, with no difference found in risk depending on Hancock et al. (2003) studied individuals driving on a test track the type of phone. Conversely, an examination of naturalis- who were presented with a dual task to create a distraction. tic driving data of commercial vehicle drivers found that talk- The results showed that drivers braked later when engaged in ing or listening on a hands-free phone (i.e., driver talking

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8 through a headset) provided a significant protective effect Citation Summaries (odds ratio of 0.4), similar to the talking or listening to a cit- izen's band (CB) radio (odds ratio of 0.6), therefore decreas- Backer-Grndahl, A. and F. Sagberg, "Relative Crash Involve- ing the risk of a safety-critical event (Olson et al. 2009). ment Risk Associated with Different Sources of Driver Olson et al. (2009) suggested that dialing a phone requires Distraction," presented at the First International Driver Dis- substantial visual attention, taking the driver's eyes off the traction and Inattention Conference, Gothenburg, Sweden, forward roadway, whereas listening or talking on the phone Sep. 2829, 2009. engages the driver and may provide an alerting mechanism (FMCSA 2009). The authors introduce three types of research on driver distraction. First, there are experimental (e.g., simulator) or The contrasting conclusions from these studies are the result naturalistic studies that show the effects of distraction on at least in part from the different approaches used to obtain driving behavior. Next, there are prevalence studies that use the results. The fundamental difference between Ishigami and crash databases to show that driver distraction plays a role in Klein (2009) and Olson et al. (2009) is the level of experi- between 8% to 25% of crashes. Finally, there are crash risk menter manipulation; where experimental studies are tightly studies that improve on the former by factoring in exposure controlled, naturalistic studies continuously capture data from rates (i.e., how often the driver population engages in dis- drivers under normal driving texts without experimenter tracting behaviors). intervention. The McEvoy et al. (2005) study interviewed drivers who were hospitalized after a crash and researchers This study took the latter approach by recruiting 4,307 examined these drivers' cell phone records to determine if crash-involved driver participants and determining relative a cell phone had been used up to 10 min prior to the crash. crash risk through quasi-induced exposure. The most fre- By contrast, Olson et al. (2009), by examining naturalistic quently occurring distractions were talking with passengers driving data, were able to examine the events that occurred and attending to children in rear seats; however, the distrac- seconds before the safety-critical event and distinguish the tions with the highest relative risk were looking at billboards risk of the manual phone manipulation as compared with outside, searching for addresses, and moving objects inside the the driver's phone conversation. car. Lower on the list were talking with passengers, attending to children in the rear seats, and adjusting a music device or As WHO (2011) recommends, there continues to be a radio tuner. need for more research to understand the degree to which cell phone subtasks (e.g., visual/manual demands and conversa- Cades, D.M., S.R. Arndt, and A.M. Kwashniak, "Driver tion demands) contribute to driver impairment. Distraction Is More Than Just Taking Eyes Off the Road," ITE Journal, July 2011, pp. 2633. How Risky Is Text Messaging While Driving? The authors synthesize previous research to make the case that, although eyes-off-road distraction is clearly a safety haz- WHO (2011) concluded that text messaging is a considerable ard, distractions occurring with eyes-on-road also carry a sig- risk. Drews et al. (2009) used a driving simulator to show a nificant potential for driver impairment. They cite research greatly increased crash rate from text messaging. showing that eyes-on-road drivers when presented with dis- tractions do not necessarily perceive or encode objects they Section Summary are looking at, are less likely to respond to traffic events, make riskier judgments regarding gaps in traffic, and are slower to Although a few topics are clear, there remain areas that respond to safety-critical events. Furthermore, the studies require further research. The studies reviewed indicated a clear cited show that these drivers have smaller fields of view and link to an increased risk of being involved in safety-critical thus do not scan as wide a range of the traffic scene. The types events as a result of cell phone use while driving. Although of distractions introduced in the studies included electronic the degree of risk is not clear, the risk from texting and dial- devices as well as conversations with passengers. The authors ing appears to be significantly greater. This result must be assert that a high cognitive workload of the type associated tempered with work showing the significant risk associated with electronic in-vehicle devices may reduce the driver's with nonphone distraction sources. Driving performance appar- ability to process visual information available in the road- ently does change when drivers are distracted; however, the way environment. consequences of this are not yet well understood given the contradictory results noted. Although some early research Drews, F.A., H. Yazdani, C.N. Godfrey, J.M. Cooper, and indicated that hands-free phones are no less risky than hand- D.L. Strayer, "Text Messaging During Simulated Driving," held phones, more recent work examining naturalistic driving Human Factors: The Journal of the Human Factors and data shows a protective effect in using hands-free phones. Ergonomics Society, Vol. 51, 2009, pp. 762770.

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9 The authors used a laboratory study involving a driving Ishigami, Y. and R. Klein, "Is a Hands-free Phone Safer Than simulator to evaluate the driving performance of 40 partici- a Handheld Phone?" Journal of Safety Research, Vol. 40, pants engaged in a single task (i.e., driving) versus a dual task No. 2, 2009. (i.e., driving and text messaging). Participants in the dual task experimental group took their eyes off the road an aver- The authors conducted a review of experimental, observa- age of 5 s to engage in texting activities and were involved in tional, and epidemiological studies pertaining to the use of six times as many accidents as their control group counter- cell phones and driving-related activities. In most instances, parts. The texting drivers also took significantly longer to hands-free communication was found to be as hazardous (or respond to brake lights ahead and demonstrated poor forward no less hazardous) to driving skills as using hand-held phones. and lateral control of the simulator vehicle. This was true in nondriving studies, simulated driving studies, field driving studies, and epidemiological studies. In some Although these results were in line with findings from nat- cases, the authors concluded that hands-free devices were uralistic studies, the severity of distraction effects may differ more dangerous than hand-held phones because the driver because simulator participants are aware they are being stud- underestimates the threat and does not attempt to counteract ied in a laboratory environment, and college student partici- potential negative effects (e.g., reaction time). pants may differ in meaningful ways from professional truck drivers. Klauer, S.G., F. Guo, J. Sudweeks, and T.A. Dingus, An Analysis of Driver Inattention, Using a Case-crossover FMCSA, Driver Distraction in Commercial Vehicle Opera- Approach on 100-car Data: Final Report, Report No. tions, Tech Brief, Publication No. FMCSA-RRR-09-045, DTNH22-00-C-07007, National Highway Traffic Safety FMCSA, Washington, D.C., 2009. Administration, Washington, D.C., 2010. This tech brief provides a summary of the Olson et al. The authors analyzed the 100-Car Study database using (2009) study. logistic regression to identify behaviors that increased crash risk. They focused on three types of secondary tasks: com- Hancock, P.A., M. Lesch, and L. Simmons, "The Distrac- plex, moderate, and simple. Examples of simple secondary tion Effects of Phone Use During a Crucial Driving Maneu- tasks included adjusting a radio or other vehicle manufactured ver," Accident Analysis and Prevention, Vol. 35, 2003, devices, talking to a passenger(s) in an adjacent seat, talking pp. 501514. or singing with no passenger present, drinking, smoking, and thinking. As a group, these simple secondary behaviors were In this study, dual tasks were examined where individuals found not to increase crash risk. were required to respond to an in-vehicle telephone and make stopping decisions. A total of 42 participants were included in Next, the authors looked at moderate secondary behaviors, the study that resulted in a final sample of 36. Participants com- including talking and listening or other hand-held device pleted the driving tasks on a one-fifth-mile loop-shaped track. activities, inserting or retrieving a compact disc, reaching for A combination of distraction and stopping conditions were objects, grooming and other hygiene activities, eating, and presented in addition to a controlled environment as follows: looking at something outside of the vehicle. As a group, mod- erate secondary behaviors increased the crash risk 1.3 times, Control--Driving only, compared with no secondary behaviors. Distracter only, Stopping only, and Finally, complex secondary behaviors included dialing a Distracter and stopping. hand-held device; locating, reaching, and answering a hand- held device; reading; live animals or insects in the vehicle; Younger participants tended to approach the intersection reaching for a moving object; and applying makeup. As a faster than their older peers, but there were no gender differ- group, drivers engaged in complex secondary tasks were ences. In terms of brake response time, participants braked 2.1 times more likely to be involved in a crash than drivers significantly slower when a distraction task was presented. who did not perform these tasks. Older drivers drove much more slowly than their younger counterparts during a distraction. The study concluded that Lerner, N., J. Singer, and R. Huey, Driver Strategies for the older groups as well as females tended to be more affected Engaging in Distracting Tasks Using In-vehicle Technolo- by distractions than the other groups (younger and male). gies, Report No. HS DOT 810919, National Highway Traffic Results also indicated that participants would brake harder in Safety Administration, Washington, D.C., 2008. the presence of a distraction, which in turn stopped the vehi- cle sooner. Therefore, the research suggests that individuals Rather than conduct another study demonstrating the may indeed stop sooner rather than later when a distraction link between driver distraction and safety-critical events, the is present. authors investigated when drivers are willing to take a risk

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10 and engage in nondriving-related tasks. A focus group was to focus some attention on nondriving tasks). The surplus used to become familiarized with the types of in-vehicle capacity is reduced or eliminated as the driver takes on addi- technologies commonly used, followed by an on-road study tional demands (e.g., fixed hazards such as dangerous road in which drivers kept a log of how willing they would be to layouts or transient hazards such as bad weather) and so it engage in certain behaviors at specified points along pre- makes sense to prohibit billboards or other distracters from determined routes. Findings showed that driver willingness locations that already have known fixed hazards (e.g., sharp was associated more with task-related motivations and life- turns or difficult intersections). Further research must be con- styles than with driving-related issues such as roadway or ducted to review the effect of sign idiosyncrasies (e.g., infor- traffic characteristics. Drivers were also not very likely to mation density, font size, message content, and dynamic plan ahead for their technology use or delay use until road messages) that could play a role in the severity of distraction. conditions and driving demands were low. The authors present a list of independent and dependent vari- ables that could be studied, as well as the research strategies McEvoy, S.P., M.R. Stevenson, A.T. McCartt, M. Wood- that might be employed. Table 3 in the study's appendix out- ward, C. Haworth, P. Palamara, and R. Cercarelli, "Role of lines the associated advantages and disadvantages of the Mobile Phones in Motor Vehicle Crashes Resulting in Hos- various field and lab approaches. pital Attendance: A Case-crossover Study," BMJ, Vol. 331, 2005, pp. 15. Morgan, J.F., T.E. Trimble, D.S. Bowman, S. Baker, R. Pickett, D. Murray, and G. Bergoffen, Synthesis of Literature Cell phone activity was examined for defined intervals Relating to Cellular Telephone/Personal Digital Assistant before and after a crash. The sample consisted of 456 partic- Use in Commercial Truck and Bus Operations, Report No. ipants. Researchers concluded that crash likelihood was four FMCSA-RRR-11-015, Federal Motor Carrier Safety Admin- times higher for participants that had used their phone within istration, Washington, D.C., 2011. 10 min before the crash. There were no differences of crash likelihood between gender, age, or cell phone type. Both hands- This article reviewed four aspects of driving performance free and hand-held cell phone use resulted in an elevated that have empirically been shown to be harmed by driver crash risk. distraction. First, lateral control of a vehicle is impaired by distraction, with distracted drivers experiencing more un- Although this study found an increased crash risk associ- intentional lane departures; greater variability in the vehicle's ated with cell phone use, it was suggested that enforcing laws position inside the lane; and sharper, more frequent steering that limit use may be difficult. Bluetooth technology has wheel inputs and corrections, compared with undistracted become increasingly prevalent in newer vehicles to promote drivers. Second, distraction has been shown to be detrimen- hands-free cell phone use. However, the research in this tal to longitudinal (i.e., speed) control of the vehicle, with study did not find a difference of crash likelihood between distracted drivers typically struggling to maintain a constant hands-free or hand-held devices. The presence of Bluetooth speed; this greater variability in speed is accompanied by a technology may encourage more people to use cell phones lower average speed than undistracted drivers. Third, dis- while driving thus contributing to an increase of crashes. tracted drivers have slower reaction times to unanticipated safety-critical events and are less likely to identify these Molino, J.A., J. Wachtel, J.E. Farbry, M.B. Hermosillo, events compared with undistracted drivers. Finally, the arti- and T. M. Granda, The Effects of Commercial Electronic cle describes how workload is also negatively affected by Variable Message Signs (CEVMS) on Driver Attention and distraction, because distracted drivers must divide their cog- Distraction: An Update, Report No. FHWA-HRT-09-018, nitive resources between required driving and extraneous Federal Highway Administration, Washington, D.C., 2009. demands; as a result, distracted drivers attempt to compen- sate by focusing almost entirely on the central visual field The authors reviewed literature addressing whether com- ahead, as opposed to performing normal visual scanning of mercial electronic variable message sign displays (e.g., elec- the entire roadway, again increasing the odds that they will tronic billboards and digital billboards) act to distract drivers fail to identify safety-critical events. and reduce driving safety. That is, as the outdoor advertising industry is moving in the direction of making billboards more National Safety Council, Understanding the Distracted attention-grabbing, is this causing drivers to substantively Brain--Why Driving While Using Hands-free Cell Phones shift their attention away from the road? Empirical studies Is Risky Behavior, White Paper, 2010 [Online]. Available: were reviewed and, although results were somewhat mixed, distracteddriving.nsc.org. there was a 5 to 1 ratio of studies finding some negative driver safety effects as opposed to no effects of billboards. As cell phone usage has increased over the past 15 years, the National Safety Council estimates that 25% of vehicle From a mental workload perspective, it can be concluded crashes can now be attributed to cell phone use, which that drivers have a finite amount of capacity to focus on driving amounts to 1.6 million crashes and 645,000 injuries. More plus some spare capacity (i.e., a buffer that allows drivers than 80% of drivers admit to talking on their cell phones

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11 while operating a vehicle, whereas 18% admit to texting other party), not to mention the cognitive capacity needed while driving. To counteract this trend, more than 200 state to understand and communicate. bills were introduced in 2009, along with an Executive Order signed by President Obama. In 2002, NHTSA surveyed 4,010 drivers to identify the most common forms of distraction, which included (from The National Security Council suggests that the reason most common to least common) talking to passengers, chang- cell phones present such a distraction is because drivers do ing radio stations or looking for music, eating or drinking, not realize that talking on the phone takes cognitive resources using a cell phone, dealing with children in the back seat, and away from the road. In addition to this cognitive explanation, reading a map or directions. cell phones can be incrementally distracting when they cause a driver to take his or her eyes off the road and/or hands off In addition, NHTSA surveyed drivers to assess the degree the wheel. Using a hands-free device is seen as a solution by to which distracted driving contributed to crash involvement, the general public (as well as current state laws and company as seen from the survey participant's perspective. It is noted policies); however, the report noted that research has accu- that survey findings were likely underreported owing to mulated to demonstrate that these devices are no better (and response bias and, indeed, a follow-up study (the 100-car nat- potentially worse) than talking on hand-held phones. The uralistic driving study), found that nearly 80% of the 82 human brain processes information sequentially and does not recorded crashes and 65% of the 761 near crashes involved multitask--as a result, drivers encounter inattention blind- drivers who took their eyes off the road just prior to the inci- ness ("looking" but not "seeing") when talking on the phone. dent. Still, there was a degree of consistency between the nat- Because they are not aware of this deficit, research has found uralistic study findings and NHTSA's survey concerning that hands-free drivers are less likely to see high and low rel- which distractions most frequently lead to safety incidents. In evant objects; visual cues; exits, red lights, and stop signs; both studies, roughly 30% of the time something outside the navigational signage; and the content of objects. These find- car was responsible for the distraction, whereas objects ings are unique to hands-free talking compared with talking inside the car were responsible closer to 20% of the time. The with in-vehicle passengers. Adult passengers in the front seat latter included other passengers (19% in this survey; 11% in can actually have a protective effect on crash risk, because the naturalistic driving study) and cell phone use (2% of the they share awareness of the driving situation. time in both studies). As a result, the authors report that cell phone users (hand- Olson, R.L., R.J. Hanowski, J.S. Hickman, and J. Bocanegra, held or hands-free) are four times more likely than nonusers Driver Distraction in Commercial Vehicle Operations, Report to be involved in an accident. The report suggests that wide- No. FMCSA-RRR-09-042, Federal Motor Carrier Safety spread education efforts are necessary, as well as comprehen- Administration, Washington, D.C., 2009. sive company policies and state laws banning all cell phone use. In addition, policies and laws will require strong This study examined data from two previous naturalistic enforcement by companies and the law, respectively. Finally, driving studies to calculate the odds ratios and population- new technologies capable of blocking cell phone capabilities attributable risk estimates for distracting tasks present in com- are another avenue worth exploring. mercial vehicle operations. When combined, these datasets included 203 commercial drivers, 7 trucking fleets, and 16 fleet NHTSA, Countermeasures That Work: A Highway Safety locations. These data represented approximately 3 million Countermeasure Guide for State Highway Safety Offices, miles of continuously collected vehicle kinematic and video 6th ed., National Highway Traffic Safety Administration, data. From these data, there were 4,452 safety-critical events Washington, D.C., 2011. (i.e., crashes, near-crashes, crash-relevant conflicts, and un- intentional lane deviations) that were examined. Key findings This guide was created as a reference to help State High- included: way Safety Offices select empirically proven counter- measures when addressing major highway safety problem Of these safety-critical events, 81.5% had some type of areas, including distracted and fatigued driving. The authors driver distraction listed as a potential contributing factor. begin by discussing the nature of distracted and fatigued Drivers were engaged in nondriving related tasks in driving, pointing out the relative difficulty of effectively 71% of crashes, 46% of near crashes, and 60% of all countering these problem areas, because they are in large safety-critical events. part societal issues dependent on lifestyle patterns and The task "talking or listening on a hands-free phone" choices. To date, most research has centered on cell phones, (i.e., driver talking through a headset) provided a signif- despite the prevalence and severity of other distracters. Cell icant protective effect (odds ratio of 0.4), therefore phones are likely singled out because they require the atten- decreasing the risk of a safety-critical event. tion of multiple senses (i.e., vision: locating the phone; touch: Tasks associated with increased risk (high odds ratios) holding or dialing the phone; sound: listening to the party were associated with long eyes-off-forward-roadway at the other end of the phone; and speech: talking to the times.

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12 More detail on this study is provided in the next section. Cell phone conversations, alcohol impairment, and com- mon in-vehicle tasks were analyzed to determine the level of Pettitt, M., G. Burnett, and A. Stevens, "Defining Driver Dis- distraction associated with each. Conversations consisted of traction," presented at the 12th World Congress on Intelligent repeating a sentence, solving a verbal puzzle, or responding Transport Systems, San Francisco, Calif., Nov. 610, 2005. to a specific topic. In-vehicle tasks included pushing a button, adjusting airflow, changing temperatures, and pushing CD The authors developed a comprehensive definition of dis- track buttons. Participants were assigned to either the control traction that accounts for all key components. In this defini- (received cranberry juice) or experimental (received alcohol tion, driver distraction occurs: and cranberry mixture) group. Blood alcohol content was maintained at 0.08 to represent the legal limit. When a driver is delayed in the recognition of informa- tion necessary to safely maintain the lateral and longitu- Results indicated that participants engaged in cell phone dinal control of the vehicle (the driving task) (Impact). conversations or in-vehicle tasks performed worse than those As the result of some event, activity, object, or person, without a secondary task. The control group (no alcohol) per- within or outside the vehicle (Agent). formed worse while completing the in-vehicle tasks than the When something that compels or tends to induce the intoxicated participants without any secondary tasks. It is driver's shifting attention away from fundamental driv- important to note that participants were more distracted by ing tasks (Mechanism). engaging in the in-vehicle tasks than conversing on the cell By compromising the driver's auditory, biomechanical, phone, meaning that cell phones caused less distraction than cognitive, or visual faculties, or combinations thereof pushing buttons in the vehicle, adjusting airflow, changing (Type). temperatures, or pushing CD track buttons. Rakauskas, M.E., L.J. Gugerty, and N.J. Ward, "Effects Researchers suggested that banning hand-held cell phones may be a first step to limiting crashes, but additional studies of Naturalistic Cell Phone Conversations on Driving needed to examine the specific issues associated with cell Performance," Journal of Safety Research, Vol. 35, 2004, phone use while driving (e.g., in-vehicle tasks and text mes- pp. 453464. saging). Also, educating the public on the risks associated with the various cell phone uses may provide a safer environ- A simulator was used to assess the relationship between ment while driving. cell phone distraction and three levels of conversation diffi- culty (none, easy, and difficult). Safety measures used in the Royal, D., National Survey of Distracted and Drowsy study consisted of: Driving, National Highway Traffic Safety Administration, Washington, D.C., 2003. Speed maintenance, Lane positioning maintenance, The NHTSA studied the frequency of 12 distracting Crash avoidance, and behaviors that people engage in while driving. The sample Mental workload. consisted of 4,010 U.S. drivers, and responses received were self-reported. Each driver was asked to estimate the number When participants held conversations while driving, of trips taken each week and the frequency of distracting results indicated more variation in acceleration and speed. activities while driving. Also, the average speed traveled was slower than non- conversation trials. However, the difficulty of cell phone Participants were asked if they have had any crashes dialogue did not result in any significant decreases in safety within the last five years and whether any distractions were performance measures. It is important to note that no sig- involved. Of the participants who did have a crash result- nificant reaction time differences were found between con- ing in damage to a vehicle, only 0.6% of crashes were versation groups when a hazardous event was presented attributed to cell phone use. Table 1 includes the percent- (e.g., vehicle pulling out). Researchers concluded that: age of crashes resulting from various distractions. (1) the complexity of cell phone conversations while driving could be examined further, (2) technology manufacturers The study found that males were more likely to use their are becoming more active in reducing distractions, and phone while driving than females and older participants were (3) policymakers could decide to focus on one driving objec- less likely to use technologies (make or receive calls, change tive (safety or convenience). the radio, use a navigation system, etc.) than younger counter- parts. Of the drivers that did use cell phones while driving, Rakauskas, M. and N. Ward, Behavioral Effects of Driver the average duration of each call was approximately 4.5 min. Distraction and Alcohol Impairment, 49th Annual Human Factors and Ergonomics Society Meeting, Orlando, Fla. Generally, most of the participants supported five pro- Sep. 2630, 2005. posed measures to reduce the use of cell phones while driving.