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8 CMV in interstate commerce. FMCSA provides guidance Driver physical qualifications focus primarily on major to medical examiners (and motor carrier companies) in an medical conditions such as cardiovascular conditions, or online handbook (FMCSA n.d.), and the training specifica- basic "static" psychomotor abilities such as visual acuity tions for medical examiners who conduct the examinations and color vision. Dynamic physical driving skills such as are available in the core curriculum. attentional focus and decision making are not assessed, nor are work-related functional requirements such as lifting and FMCSA (2008) cites the following, from 49 CFR 391.41, entering/exiting tractors and trailers. The nature of these as examples of its physical requirements for drivers: skills and tests designed to assess them will be discussed later in this chapter and the next. · Has no loss of a foot, a leg, a hand, or an arm, or has been granted a skill performance evaluation certificate pursuant to 49 CFR 391.49. SAFETY-RELEVANT DRIVER TRAITS AND OTHER · Has no impairment of a hand or finger which interferes CHARACTERISTICS with prehension or power grasping or has been granted a skill performance evaluation certificate pursuant to A trait is a personal characteristic that differs among peo- 49 CFR 391.49. ple and tends to be persistent over time. This report con- · Has no impairment of an arm, foot, or leg which inter- cerns personal traits and related characteristics that are (1) feres with the ability to perform normal tasks associ- relevant to driving safety, and (2) potentially discernible ated with operating a CMV or has been granted a skill through some kind of test, measurement, or other evalua- performance evaluation certificate pursuant to 49 CFR tion. Psychologists distinguish traits from states. Traits are 391.49. enduring, often lifetime, characteristics, whereas states are · Has no established medical history or clinical diagnosis temporary conditions (Pervin 2003). A consistent and per- of diabetes mellitus currently requiring insulin for con- sistent disposition toward anger, aggression, and/or hostility trol or has been issued a diabetic or vision exemption. would be a trait. Temporary anger after an argument would · Has no current clinical diagnosis or any disqualifying be a state. heart disease. · Has no established medical history or clinical diagno- People differ from each other in many fundamental ways. sis of a respiratory dysfunction. These differences may be related to heredity, developmental · Has no current clinical diagnosis of high blood environments, chronic life conditions, or a combination of pressure. these. Evidence points to the following types of human traits · Has no established medical history or clinical diagno- and other characteristics as being most relevant to driv- sis of arthritis. ing safety (Lancaster and Ward 2002; Murray et al. 2003, · Has no clinical diagnosis or clinical history of epilepsy. Thiffault 2011), and thus of greatest potential interest for · Has no mental, nervous, organic, or functional disease commercial driver assessments: or psychiatric disorder. · Has 20/40 vision or better with or without corrective · Personality lenses. · Attitudes · Has distant binocular acuity of at least 20/40 in both · Psychomotor skills and cognitive functions eyes with or without corrective lenses. · Medical status and conditions · Has the ability to recognize the colors (red, green, and · Behavioral history (not a trait per se but a similar amber) of traffic signals. indicator) · Has hearing to perceive a forced whisper voiced equal · Mental ability. to or greater than 5 feet with or without hearing aid, or average hearing loss in the better ear equal to or less These six categories are not entirely mutually exclusive. than 40 dB. Most notably, personality is a source of attitudes, and then · Has no history of drug use or any other substance iden- both are sources of behavioral history differences. Psycho- tified in Schedule 1. motor and cognitive skills are conceptually separable from · Has no clinical diagnosis of alcoholism. medical conditions, but in practice the two may be conflated. In both research and practice, however, the six areas are gen- Many detailed medical definitions and fine distinctions erally addressed separately. are applied in determining disqualifications. FMCSA's website and the FMCSRs have specific interpretations Each of these kinds of driver differences are defined and of the qualifications and the latest changes. Changes and discussed here. Most can be further classified into more spe- refinements to these requirements are continuously under cific categories, like different personality types and differ- consideration, and there are exemption programs for some ent medical conditions. Evidence for the safety-relevance of conditions such as monocular vision. each is presented.
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9 Personality The major personality dimensions relevant to safety include impulsivity/risk-taking, sensation-seeking, aggres- This report employs a broad and simple definition of human siveness/anger/hostility, "Type A" personality, consci- personality: any enduring tendency or consistency in a per- entiousness, and stress level. In some cases, similar or son's behavior or psychological makeup. Personality traits overlapping personality dimensions are also discussed. The are consistent tendencies in emotional adjustment, interper- focus here is on the personality dimensions themselves rather sonal relations, motivation, attitudes, and behavioral "style." than on occupational tests of them. Chapter three presents "Personality traits are deep individual characteristics, most specific tests known to predict driving safety. often biologically rooted, that determine the broad emo- tional and behavioral orientations of the person" (Thiffault Impulsivity/Risk-Taking 2007). Psychological consistencies extend in two dimen- sions: consistency over time and consistency across diverse An impulsive person is one who makes hasty actions situations. Of course, such consistencies are not absolute. and therefore is prone to error. Often, the hard-to-control People change in both predictable and unpredictable ways impulses are related to risky behaviors or even violence. through life, and sometimes people behave markedly dif- Whenever a person reacts quickly and without forethought, ferent in different situations. But there is enough individual he or she will be at higher risk for errors. Impulsivity and risk- behavioral consistency across time and across situations that taking are largely inseparable as personality traits because it is considered a pervasive principle of psychology and a the perception of risk is what constrains most people from major determinate of behavior (Holland 1975; Pervin 2003). hasty actions (Shinar 2007). Many motor vehicle crashes are This includes commercial driver safety behavior. the result of voluntary at-risk behaviors, such as excessive speed, improper following distance, and illegal maneuvers. CTBSSP Synthesis 4 on individual differences (Knipling et al. 2004) found that both carrier safety managers and other Drivers' perception of the risk of their actions under- experts considered personality dimensions like aggressive- lies, to a great extent, the extent to which they engage in ness and impulsivity/risk-taking to be among the top predic- at-risk behaviors. Risk perception is a cognitive process tors of driver risk. Other research has also shown that these underlying an individual's perceived level of risk and that traits are associated with driver crash risk or safety-related determines, or strongly influences, risk-taking behaviors behaviors. Other safety-relevant personality traits include (Thiffault 2007). Safety belt use provides a good example. sensation-seeking, "Type A" personalities, lack of conscien- Eby (2010) reviewed the reasons why some drivers do not tiousness, and high stress level. wear safety belts. Reasons include forgetting, discomfort, inconvenience, social motivations, and complaints about Personality dimensions are not unitary physical dimen- how belts are installed in some vehicles. The biggest reason, sions like height or weight. Rather, they are constructs or however, was the perception that there was little risk in not explanatory labels for something that is not directly observ- wearing the belt. Here, "risk" included both injury risk and able or cannot be captured by a single observation or mea- traffic violation risk. Laws and company policies mandating sure (DOL 2000; Pervin 2003). Personality constructs are safety belt use are effective because they "up the ante" in theoretical concepts that attempt to capture a cluster of regard to violation risk, even though, objectively, the legal closely related personal behaviors, attitudes, or emotions. consequences of not wearing a belt are small compared with "Conscientiousness," for example, cannot be directly seen the potential injury consequences. Young male drivers have or measured, but it exists as a human trait because its mul- the highest rates of not wearing a belt, consistent with their tiple manifestations are visible in behavior that is considered high rates of risky driving behaviors. to be morally correct. This report will also discuss construct validity, the degree to which research confirms predictions Beck et al. (2006) queried 2,030 U.S. drivers (mainly based on the construct. In other words, construct validity is noncommercial) about their driving beliefs, attitudes, and the degree to which a personality label is robust and useful behaviors. Of the 2,030, 305 were designated "aggressive" as an explanation of behavior. based on a self-report that they had driven aggressively, trav- eled 20 mph or more above the speed limit, violated a traffic The research literature on personality includes numer- sign or signal, or driven while under the influence in the past ous constructs representing personal traits and dimensions. month. About 12% of the aggressive drivers admitted that For example, one major personality questionnaire uses mul- they did not "always/nearly always" wear their belts, com- tiple-choice answers to classify people on five dimensions pared with just 2% of the remaining drivers. or scales: neuroticism (anxiety), extraversion, openness to experience, agreeableness, and conscientiousness (Larson Not wearing a safety belt appears to be an indicator of com- and Buss 2005). These have been called the "Big Five" per- mercial driver risk as well. In the LTCCS, truck crash involve- sonality dimensions, although not all are strongly related to ments could be separated into three categories: single-vehicle, driving safety. multivehicle where the truck/truck driver is assigned the Criti-
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10 cal Reason (CR) (i.e., is "at-fault"), and multivehicle where the aggressive driving, lack of rule following (e.g., speed limits), other vehicle/driver is assigned the CR (Knipling 2009b). Sin- and driver loss of concentration at critical times. gle-vehicle crashes suggest the greatest driver failure, as they generally occur as a result of a catastrophic loss of vehicle con- Drivers who seek sensation and/or experience negative trol. In truck-CR multivehicle involvements, the truck driver emotions while driving are more likely to be in crashes and is at fault, but the error is usually a traffic interaction mistake to commit violations. Matthews et al. (1996) developed a such as "looked but did not see" or false assumption. Truck Driver Stress Inventory (DSI) to capture emotions during driver error is minimal or nonexistent in multivehicle crashes driving, including aggressive feelings toward other drivers, where the other driver is assigned the CR. Not wearing a safety active dislike of driving, worry over hazards, thrill-seeking, belt is strongly associated with these three crash categories and and fatigue. Subjects taking the inventory answer 48 Likert levels of driver culpability, as shown in Figure 1. Thus, not scale items which together generate scores on these various wearing a safety belt is associated not only with the risk of aspects of stress. DSI scale scores for both U.S. and U.K. injuries in crashes, but also with the risk of causing crashes. subject groups were compared with separate questionnaire responses relating to driving behaviors, crashes, and viola- tions. Crash-involved drivers scored higher than non-crash- involved ones on feelings of thrill-seeking and aggression/ hostility while driving. Thrill-seeking and aggressive emo- tions also correlated in the +0.4 to +0.6 range with traffic violations and with self-reported speeding. Sensation-seekers appear to be generally more suscep- tible than other drivers to fatigue and drowsiness. Because 16 Driver Characteristics and Risk: Safety Manager Ratings FIGURE 1 Association of truck driver safety belt nonuse and crash involvement category in the LTCCS. (Source : Knipling (Arranged Highest to Lowest) 2009b.) 1. Aggressive/angry Impulsivity overlaps strongly with sensation-seeking, 2. Impatient/impulsive aggressiveness/anger, "Type A" personalities, and (lack of) conscientiousness. Thus, the research findings relating to 3. Inattentive these traits generally apply qualitatively to impulsivity as well. 4. Inexperienced (new CMV driver) Sensation-Seeking 5. Unhappy with job/company Sensation-seeking is the desire for varied, novel, and arous- 6. Young driver (e.g., less than 25) ing experiences. It has well-established links to unsafe driving behaviors, traffic violations, and crash involvement (Schwebel 7. Sleep apnea/other sleep disorder et al. 2006). Sensation-seeking overlaps with other personality traits like impulsivity and aggressiveness. Sensation-seeking 8. Unhappy marriage/family problems people tend also to be extraverts. Studies reviewed by Dewar and Olson (2002) and Knipling (2009a) link sensation-seeking 9. Debt or other financial problems with unsafe driving behaviors, traffic violations, and crash 10.Heart or other medical condition involvement. A meta-analysis by Jonah (1997) documented correlations between sensation-seeking and risky driving 11.Dishonest behaviors such as speeding, frequent lane changes, alcohol use, and failure to wear safety belts. Iverson and Rundmo (2002) 12.Older driver (e.g., 60 or older) also found a significant association between sensation seeking and risky driving. Rimmo (2002) found that sensation-seeking 13.New to company is strongly associated with violations of rules (e.g., speed lim- 14.Obese/overweight its and other traffic restrictions) but only weakly associated with driving mistakes not associated with rule violations, such 15.Introverted/unsociable as "looked but did not see." Dahlen and White (2006) found sensation-seeking to be related to unsafe driving behavior, 16.Did not attend truck driving school although they noted that the exact path in which it affects driv- Source: Knipling et al. (2003). ing is unknown. They speculated that the link was related to
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11 they become bored with routine tasks more easily, sensation- other high-achieving individuals, but has a negative con- seekers need and seek more stimulation to keep them awake; notation if it implies chronic anger, dissatisfaction, impa- without it (as during long, boring drives), they become vul- tience, overcompetitiveness, and hostility. The "Type A" nerable to drowsiness. In contrast, non-sensation-seekers personality encompasses these characteristics. In a review generate their own internal stimulation to sustain alert- of several studies, Dewar and Olson (2002) note that the ness. This finding is based on a driving simulator study by Type A personality is reflected in people's choice of vehi- Thiffault and Bergeron (2003), as well as other studies and cles, driving style, violation rates, crash rates, and heart theories of individual differences in brain function. attack rates. They also report a surprising association with psychomotor skills: Relative to controls, Type A individu- Aggressiveness/Anger/Hostility als have slower reaction times and generally perform worse. Type A individuals often exhibit life stress both at home In the CTBSSP Synthesis 1 Safety Manager survey (Knipling and at work, are quickly irritated by other drivers, tend to et al. 2003), respondents rated "aggressive/angry" as the dehumanize other drivers, and express anger outwardly driver characteristic most highly associated with driver risk. rather than inwardly. For them, the shell of a car or truck The textbox shows the rank-ordered list of characteristics cab can be an insulated and "safe" environment from which presented in the questionnaire. Other research corroborates to project anger and hostility. this strong association. Numerous studies show relation- ships between aggression/anger and crashes and violations Nabi et al. (2005) compared questionnaire responses (Knipling et al. 2004; Schwebel et al. 2006; Thiffault 2007). on the Bortner Rating Scale for Type A Behavior Patterns "Road rage" incidents are the most extreme and highly pub- (TABP) to responses relating to risky driving behaviors and licized manifestation of driver anger, but such incidents rep- past crash involvements. The subject group for this com- resent only the most visible part of a larger problem. parison was 11,965 French national utility (electricity and gas) company employees. The researchers found a signifi- Dahlen and White (2006) compared the "Big Five" per- cant association between Type A behaviors and both crash sonality factors, sensation-seeking, and driving anger to driv- rates and serious crash rates. The study controlled for annual ing behaviors and history. Subjects were 312 undergraduate mileage, gender, and age. Figure 2 shows driving "hazard students who drove more than 60 miles weekly. Driving anger ratios" for low, medium, and high scorers on the TABP scale. was measured by a 14-item questionnaire, an abridged ver- Explanations for the association include that Type A drivers sion of a 33-item Driving Anger Scale (DAS; Deffenbacher et engage in more risky driving behaviors (e.g., talking on cel- al. 2001). Although other measured personality traits (includ- lular phones, eating), are less patient, and are more prone to ing sensation-seeking) showed correlations with driving risk, anger in frustrating or stressful driving situations. the trait driving anger had the clearest associations. Scores on the 14-item DAS correlated positively with close calls (+0.18), risky driving (+0.31), and aggressive driving (+0.38). The authors considered individual differences in anger while driving to be important in assessing crash risk, and recom- mended driving anger as a principal factor to include in any personality inventory to screen for risky drivers. Schwebel et al. (2006) compared personality traits with both driving behavioral history and performance on a simu- lated virtual environment task designed to assess risk-taking FIGURE 2 Driving "hazard ratios" for low, medium, and high during driving. Traits examined included anger/hostility, Type A questionnaire scorers in French utility company study. sensation-seeking, and conscientiousness, all of which previ- (Source : Nabi et al. 2005.) Note : Normed relative to "Low" ous studies had linked to risky driving. Anger/hostility was hazard (1.00). measured using the DAS and behavioral history using a Driver Behavior Questionnaire (DBQ; Parker et al. 1995). Subjects Conscientiousness high in anger/hostility took more chances in the simulated driving and also had stronger histories of speeding, violations, Conscientious people have a strong sense of right and wrong and crashes. Findings for sensation-seeking were similar, and believe in an obligation to act accordingly. Thus, they whereas those for conscientiousness were similar but inversed. tend to be careful, scrupulous, responsible, and reliable. Unconscientious people are at the opposite extreme. Level "Type A" Personality of conscientiousness in the population may follow a skewed distribution much like that of driver risk. That is, most people "Hard charging" is a description that may have a positive are in the "hump" at the good end of the spectrum, whereas a connotation when applied to successful entrepreneurs or relatively small number are in the long "tail" at the bad end.
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12 Arthur and Graziano (1996) administered question- naires on conscientiousness and five other personality traits to nearly 500 subjects, including both college students and workers. Conscientious individuals were those who charac- terized themselves as self-disciplined, responsible, reliable, and dependable. Of the six traits measured, conscientious- ness was found to have the strongest relation (in this case, an inverse relation) to crash involvement for both students and workers. The authors noted that "conscientious individuals may be especially sensitive to social responsibility norms," FIGURE 3 Correlations among social deviance, thoroughness, making them less likely to engage in dangerous activities. speeding, and crashes. (Source : Redrawn from West et al. Controlling for other factors, the correlation between consci- 1993.) entiousness and number of at-fault crashes was -0.22, which may be considered a moderate correlation given the various Neuroticism measurement difficulties and confounding factors affecting such a study. Neuroticism is a personality trait characterized primarily by anxiety and stress. Other characteristics include irritability, Extreme lack of conscience is seen in antisocial per- discontent, self-consciousness, and moodiness. The opposite sonalities. Individuals with this personality disorder have of neuroticism is termed emotional stability. Moen (2007) been called "sociopaths" or "psychopaths." "Antisocial" in found that highly anxious people had lower self-assessments this context does not mean introverted, but rather that the of their driver skill and higher stress levels during driving. individual has little social regard for others. These individu- This was reflected in higher crash rates. Driving stress is als tend to be sensation-seekers who do not appreciate the also related to anger while driving. As noted earlier, Dahlen potential consequences of their actions for themselves or and White (2006) found that DAS scores were predictive of others. The antisocial personality type is often seen among unsafe driving behaviors and high crash histories. criminals and among individuals with a history of traffic vio- lations and crashes. Thus, hiring individuals with criminal Personal stress and unhappiness can be caused entirely backgrounds poses safety and security concerns (Knipling by one's life situation rather than by internal, constitutional 2009a). factors. There is, however, clear evidence that chronic stress level can also be a true personality trait like others described In a large poll of more than 700 general population driv- above. Moreover, many people's adverse life situations, such ers, West et al. (1993) related "social deviance" to self- as family and financial problems, are long term. Thus, from reports of speeding while driving and crashes. Socially the perspective of motor carriers seeking to hire low-risk deviant individuals were characterized as being selfish, drivers, applicant stress level might be seen as an enduring focused on immediate gratification, and having a disregard personal characteristic. The positive opposite is unstressed for the law and for other people. Questionnaires were used emotional stability. to assess socially deviant attitudes and behaviors. Ques- tionnaires were also used to assess subjects' "thorough- Individual stress level may be related to locus of control. ness" and their driving histories and behaviors. Figure 3 A person with internal locus of control believes that he or summarizes correlations seen among these personal char- she has mastery, or at least strong influence, over life events acteristics and histories. Negative correlations indicate and outcomes. One with external locus of control believes an inverse relationship. Although none of the correlations that personal efforts to control events are futile. External was particularly high (probably reflecting the difficulty of locus of control is associated with greater stress and anxi- precisely measuring these traits), the highest seen were ety. Knipling et al. (2004) reviewed several studies indicat- between social deviance and speeding, and between social ing that external locus of control is associated with higher deviance and crashes. crash risk. For example, Jones and Foreman (1984) classified bus driver applicants with two or more moving violations as Several project interviews mentioned an "attitude of high-risk and those with no moving violations as low-risk. compliance" as an important safety-related characteristic of On a personality profile, 79% of the high-risk group scored good commercial drivers. One bus company safety director high on external locus of control, versus only 31% of the believed that drivers who were "passive" and nonassertive low-risk group. in traffic were the safest drivers because they avoided con- flicts with other vehicles. A truck company safety director A nondriving study of 283 hospital workers compared regarded ex-service members as a good bet for success as individual "safety locus of control" to their on-job accidents commercial drivers because they were used to complying (Jones and Wuebker 1993). Thirty-eight percent of the low with rules and orders. safety consciousness group was involved in one or more
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13 major accidents during the study period, compared with which in turn become behaviors. Perceived behavioral con- 28% of the medium safety and 21% of the high safety con- trol is related to a person's expectations of rewards or pun- sciousness groups. ishments associated with the behavior, and the degree to which they control those consequences. Figure 4 shows this Attitudes schematically. Interwoven with the concept of human personality is the con- cept of attitude. An attitude is an individual's positive or nega- tive evaluation of a particular thing, where "thing" can be any object of thought. Attitudes toward particular driving behav- iors, including both positive behaviors (e.g., safety belt use) and negative behaviors (e.g., speeding), are of greatest interest. Attitudes have two internal components: cognitive (knowledge and beliefs) and emotional (Dewar and Olson, 2002). Attitudes are revealed in individual statements and, most important, in behavior. Extreme behaviors like aggres- sive driving strongly reflect negative attitudes, such as a FIGURE 4 Simple schematic of the Theory of Planned general hostility toward society and rules. Less extreme Behavior. (Source : Ajzen 1991.) behaviors also reflect attitudes, although situational factors also affect such behaviors. For example, a driver with a nega- The TPB is a theoretical framework for studies of individ- tive attitude toward safety belt use may still wear one if there ual factors in driving safety. Numerous studies have related is a strong company belt-use policy and clear negative con- attitudes, subjective norms, or perceived behavioral control sequences for non-use. to intentions and to behavior. All three have been shown to be predictors of dangerous driving behaviors (Parker et People tend to attribute their own behavior to external al. 1998; Thiffault 2007, 2011; Poulter et al. 2008). Chapter circumstances (e.g., "I didn't have time to react to the sig- three will discuss how "slack" driver attitudes toward rule nal change.") while attributing the behavior of others more violations (e.g., speeding) are related to both a relative lack to their character or personality ("red-light runner"). This of concern about crashing and to violation frequency (Ma et difference in how individuals view their own behavior ver- al. 2010). sus that of others is called the attribution bias (Dewar and Olson 2002). The truth lies somewhere in between. People Several of the personality traits discussed in the previous do have persistently different personalities and attitudes, and section are intertwined with safety attitudes. Conscientious thus these are "fair ground" in driver selection. However, the individuals, for example, value morality and safety highly, environment can change specific behaviors and even specific are strongly influenced by safety-related social norms, or attitudes. For example, individuals forced to comply with a perceive controls on their behavior to be strong. An "attitude rule (e.g., safety belt policy) will often develop more positive of compliance" appears to characterize many of the most attitudes toward the rule and required behavior over time. conscientious and reliable commercial drivers. Social norms are an important part of the human environ- ment; a company driver will be more likely to buckle up if he In Britain, Poulter et al. (2008) tested the application of or she believes that all the other drivers are doing so. the TPB to truck driver safety. Based on past studies, they identified two principal driver factors associated with crash One can conceptualize a loose causal relationship con- involvement: (1) driving behavior and (2) driver compli- necting individual personality, attitudes, intentions, and ance with driver- and vehicle-related regulations. Driver behaviors. This is illustrated as: behavior is reflected by moving traffic violations, whereas The Theory of Planned Behavior (TPB; Ajzen 1991) has driver compliance is reflected by driver-related (e.g., hours been formulated to explain how attitudes and other factors of driving) and vehicle-related (e.g., overloading, mechani- combine to become behavioral intentions, and then behav- cal problems) roadside violations. The researchers recruited ior. At any given time, an individual's attitudes (the positive 232 truck drivers from several companies and other sources or negative value of a behavior) combine and interact with to complete a questionnaire assessing attitudes toward both subjective norms (social norms as perceived by the person) specific driving behaviors and specific regulatory violations. and perceived behavioral control to determine intentions, In subject comparisons, they found positive interrelation-
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14 ships among all of the TPB elements shown in Figure 4. The driving or similar maneuvering. Sensorimotor and cognitive intention to observe traffic laws had the greatest association (mental) skills are of paramount importance for high per- with driving behaviors, whereas behavioral control had the formance in video games but not generally for safe driving. greatest association with regulatory compliance. If they were, then teenagers and young adults would be the best drivers, and safe performance would decline in later A key point for driver selection is that well-constructed adulthood along with sensorimotor and quick reaction skills. questionnaires can assess persistent individual differences Instead, middle-age and "young old" drivers up to their late in safety attitudes and that such attitudes can be predic- 60s or even older are generally the safest drivers (Knipling tive of driving behaviors. However, one should not view all 2009a). safety-related attitudes as fixed. They may change based on new knowledge, experience, and maturation. Although they Driving involves many dynamic skills. The Trucking are outside of the realm of driver selection, Behavior-Based Research Institute (Llaneras et al. 1995) analyzed the dynamic Safety programs (e.g., Hickman et al. 2007) often result in perceptual, cognitive, and psychomotor (sensorimotor) skills positive changes in driver safety attitudes even though their involved in driving. The text box lists these skills. Tests on focus is on specific behaviors. a group of commercial drivers compared these dynamic skills to performance on an interactive truck driving simula- Psychomotor Skills and Cognitive Functions tor. Dynamic or "neurocognitive" skills most predictive of simulator performance included depth perception, peripheral vision/field-of-view, field independence/dependence, atten- Dynamic Skills in Driving tion sharing, and range of motion. The tests showed that many dynamic skills generally declined with age, but that age alone Perceptual: was not a good predictor of performance. Even if age did reli- ably predict dynamic skills, it appears "that behavior usually Static Visual Acuity trumps performance in driving safety" (Knipling 2009a). Dynamic Visual Acuity Although dynamic performance generally declines for older commercial drivers in their 50s and 60s, these drivers are Visual Contrast Sensitivity among the best when it comes to crash rates and likelihood Peripheral Vision/Field-of-View of being at fault in crashes. Detection of Objects in a Visual Field Dynamic skill tests are not likely to be highly predic- Depth Perception tive of crash rates across the wide range of drivers, but they may be useful to identify those with significant deficits. This Cognitive (Mental): might include the assessment of some serious medical con- ditions or impairments from drug or alcohol use (Llaneras Information Processing/Thinking et al. 1995). They might also be useful to provide baseline Decision Making performance measures for later comparisons should drivers undergo significant health changes or show other signs of Selective Attention possible increased risk. Attention Sharing (multitasking) Most perceptual information in driving is visual. A com- mon estimate is that 90% or more of the information a driver Psychomotor Coordination: receives is visual, though this estimate is not based on rigor- Reaction Time ous studies (Dewar and Olson 2002). Driver licensing tests to measure visual acuity screen out most of those with bad Multilimb Coordination vision, but otherwise they are not known to be predictive of Precision Control driving safety. Tracking (following a target or path) The visual skill apparently most related to safe driv- Range-of-Motion ing is not a static skill but rather a dynamic one related to peripheral vision. It is called Useful Field-of-View (UFOV) Adapted from Llaneras et al. 1995. and has been studied mostly in older drivers. UFOV can be described as an "occupational visual field" test, in contrast Driving is a demanding sensory-motor task that requires to a clinical visual field test using flashing peripheral lights keen perception, quick thinking and decisions, and precise in an ophthalmologic setting. Young adult fixed-head field- execution of responses. In some respects, it is like a com- of-view is about 180°, but this generally declines by age 70 puter or video game, and indeed many such games involve to about 140° (Dewar and Olson 2002). Head and eye move-
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15 ments allow a wider field, of course. The UFOV test flashes proportion of the population. Chapter three discusses Way- peripheral lights while a subject focuses on a center target. Point's use in selecting safe fleet drivers. Subjects' ability to see and react to the peripheral lights determines their UFOV. The UFOV test is different from the Medical Status and Conditions standard ophthalmological vision tests because it measures the central processing speed at which visual information is The past decade has seen increasing interest, research, and analyzed. It includes subtests that evaluate speed of informa- regulatory activity relating to the issue of commercial driver tion processing, ability to divide attention, and susceptibility health and medical conditions. This activity has reflected to distraction. The test expresses the patient's UFOV as a concerns about driver wellness and longevity, and also con- percentage reduction from the ideal (Crabb et al. 2004). cerns about driving safety. Two previous synthesis reports (Orris et al. 2005; Krueger et al. 2007) have addressed Studies among older drivers and those with known atten- commercial driver health issues. Commercial drivers as a tion or mental impairments find that UFOV is predictive of group compare unfavorably to other Americans in measures crash rates, especially for intersection crashes. The UFOV of personal health (Roberts and York 2000; Krueger et al. is much less predictive for younger and unimpaired drivers 2007). FMCSA's medical program acknowledges these con- (Dewar and Olson 2002). In driving, UFOV varies inversely cerns. The following is a characterization of U.S. commer- with speed; that is, the higher the speed, the less the angle cial drivers, excerpted from the FMCSA Medical Examiner of the useful visual field. This may be one reason why many Handbook: drivers drive slower as they age. The Average Driver. The [commercial] driver population exhibits characteristics similar to the general population, Clay et al. (2005) completed a cumulative meta-analy- including an aging work force. Aging means a higher sis on the relationship of UFOV and driving performance risk exists for chronic diseases, fixed deficits, gradual or in older adults. A meta-analysis combines previous stud- sudden incapacitation, and the likelihood of comorbidity. All of these can interfere with the ability to drive safely, ies' results as data to analyze the same research questions. thus endangering the safety and health of the driver and Among older drivers, the UFOV correlation with safety is the public (FMCSA 2010). robust across multiple indices of driving performance and several research laboratories. This convergence of evidence from numerous studies using different methodologies con- The following is the profile of the average truck or bus firms the importance of the UFOV assessment as a valid driver: index of driving competence and safety (Clay et al. 2005). · Male Sumer et al. (2005) administered computer-based cogni- · More than 40 years of age tive and psychomotor tests to 716 professional and nonprofes- · Sedentary sional drivers. Tests included traffic monotonous attention, · Overweight selective attention, visual pursuit/tracking, eye-hand coordi- · Smoker nation, reaction time, and peripheral perception. Scores on · Poor eating habits. these tests were compared with self-reported driving behav- iors, skills, violations, and inattention errors. The peripheral The following is the medical profile: perception test, similar to the UFOV test, was found to have the strongest positive correlations with driving and safety · Less healthy than the average person skills, as well as the strongest negative correlations with · More than two medical conditions driving violations and inattention errors. · Cardiovascular disease prevalent. The Trail-making test and WayPoint are two similar psy- Although a detailed review of the safety relevance of spe- chomotor tests of visual attention and task switching. The cific medical conditions is beyond the scope of this report, Trail-making test task requires a subject to "connect the medical conditions can reduce driver and fleet safety in three dots" of 25 consecutive targets using paper and pencil or a primary ways (Knipling 2009a). The first two relate to driv- computer screen. Scoring is based primarily on speed but ing performance and crash risk while driving, whereas the also on errors. Two versions are available. Version A is sim- third relates to more to the long-term stability of a carrier's pler: The targets are simply numbered (1, 2, 3, etc). Version driving workforce: B requires the subject to switch from numbers to letters (1, A, 2, B, 3, C, etc.). WayPoint is similar to Trail-making Ver- · Chronic performance decrements. Medical conditions sion B, but adds distractors in some parts to make the task could affect driver safety by causing general decreases more difficult. Trail-making is used primarily to diagnose in psychomotor skill and cognitive functions. Such brain damage (Corrigan and Hinkeldey 1987), but scores on chronic performance decrements might include these tests may be related to driving behavior across a larger decreases in flexibility, decreases in alertness, or
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16 increases in reaction time. Psychomotor/cognitive per- Obstructive Sleep Apnea formance has a weak relationship to crash risk unless a driver has significant deficits. Therefore, predicting Obstructive sleep apnea (OSA) is a medical condition of crash risk based on medical conditions causing such great concern to motor carriers and many others involved in deficits has been difficult. Moreover, most physicians truck and bus safety. It is a common illness among middle- do not have the time or the tools to assess functional aged males, the principal commercial driver demographic. impairments associated with illness. OSA is a breathing disorder that disrupts sleep and causes · Catastrophic performance failures. Medical condi- often-severe daytime drowsiness. OSA is associated with tions can cause episodic losses of the ability to control obesity, which is prevalent, and perhaps the norm, in the U.S. a vehicle, usually by loss of consciousness. Medical commercial driver population (FMCSA 2010). crises such as heart attacks, seizures, or diabetic insu- lin shock are significant proximal causes of serious The increase in crash risk associated with OSA is large truck crashes. Sleep disorders such as obstruc- probably substantial. Various studies of noncommercial tive sleep apnea are often a root cause of asleep-at-the- drivers with OSA put the increase in crash likelihood wheel crashes. In the LTCCS, truck driver physical from two- to sixfold. A case control study by Young et failures, primarily falling asleep and heart attacks, al. (1997) placed the increase at fourfold. However, a case were the CR of 12% of truck at-fault crashes and 6% of control study of commercial drivers found no increased all truck crashes (Starnes 2006). The major purpose of crash risk among truck drivers with OSA (FMCSA 2004). commercial driver medical qualifications is to prevent This unexpected finding is questionable because the study such crises. Medical screenings beyond the minimum involved mostly short-haul drivers and had unverified qualifications can help carriers to reduce the risk of mileage exposure data. such crashes and associated losses. · Absenteeism and reduced employment longevity. This In the 10 safety manager interviews conducted for the effect on fleet safety is less obvious and dramatic, but report case studies, OSA was the most frequently cited may be comparable in its long-term effects on carrier driver medical concern. Carriers know that OSA is not and industry safety. Chronic medical conditions are the always detected through the medical qualifications process most obvious signs of the poor health of many commer- and that it can be a cause of major crashes with high human cial drivers. Many of these individuals would be high- and financial consequences. Chapter five describes several performing and reliable long-term employees were it carrier medical programs addressing OSA and other driver not for their health problems. In the LTCCS, commer- health problems. cial drivers aged 51+ were 17% less likely than younger drivers to be at fault in multivehicle crashes, and yet Individual Differences in Fatigue Susceptibility these drivers are those most like to have reduced ser- vice owing to chronic medical conditions. OSA and other sleep disorders are major causes of individ- ual differences in susceptibility to drowsiness while driv- Cardiovascular Illness ing. However, these differences are also seen among drivers without known sleep disorders (Knipling 2005). For exam- Cardiovascular illness, the number-one cause of death in the ple, sleep-deprived healthy adults show wide variations in United States, includes hypertension (high blood pressure), their progressions of performance deterioration and in over- arteriosclerosis, coronary artery disease, angina (heart pain), all degree of performance impairment (Van Dongen et al. heart attacks, and congestive heart failure. Cardiovascular 2004). Moreover, these differences are consistent over time illness is associated with both catastrophic performance and, based on twin and family studies, have a partial genetic failures while driving (principally heart attacks) and with basis (Van Dongen et al. 2005). Many different patterns and shortened careers among middle-aged commercial drivers. features of human sleep, wakefulness, and sleepiness seem to vary widely among individuals. Moore-Ede (2007) has In the 1990 NTSB study of 182 fatal-to-the-driver truck introduced the term chronotype to refer to an individual's crashes, 17 (9%) were found to involve a heart attack or other vulnerability to drowsiness and other sleep- and alertness- cardiac incident as the primary cause. In the LTCCS, about related characteristics. 6% of large truck single-vehicle crash involvements and 3% of all involvements had a CR of heart attack or other physi- Although there appears to be a partial genetic basis, envi- cal impairment (not including asleep-at-the-wheel). A 2007 ronmental and lifestyle differences also play a role. They report by the FMCSA Medical Review Board reviewed eight include differences in the sleep setting (e.g., room quiet- prior studies and estimated the relative crash risk of drivers ness and darkness, bed comfort) and in sleep hygiene habits. with cardiovascular disease (all types combined) to be 1.43, Although such differences may persist over time, they are or a 43% increase over other drivers. potentially changeable.
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17 88% accuracy based on past crash involvements and viola- tions. Having recent at-fault crash was one factor that made drivers more likely to be at fault in another crash. Miller and Schuster (1983) followed 2,283 drivers in Cali- fornia and Iowa for 10 years or more. They found that past traffic violations were a better predictor of future crashes than were past crashes. Past traffic violations seem to be a better predictor of future crashes (1) because they are more numerous and thus more statistically reliable than crashes, FIGURE 5 Frequency distribution of long-haul truck driver and (2) because violations clearly imply misbehavior and high-drowsiness episodes among 80 drivers. (Source : Wylie et fault, whereas a driver may not been at fault in past crashes. al. 1996.) Murray et al. (2005) analyzed the records of more than The Driver Fatigue and Alertness Study (Wylie et al. 500,000 U.S. commercial drivers to determine factors most 1996) is one of many to show wide variations in driver predictive of future crash involvements. Principal data fatigue susceptibility. Eighty long-haul commercial driv- sources were the Motor Carrier Management Information ers in the United States and Canada were monitored over System (MCMIS) and the Commercial Drivers License a week of driving. Video segments were scored for drowsi- Information System (CDLIS). Three driver history risk ness based on drivers' eyelid droops, facial expressions, and indicators were roadside inspection violations, traffic viola- facial muscle tones. Eleven of the 80 drivers (14%) were tion convictions, and crashes. Rates of involvement in these responsible for 54% of all observed drowsiness episodes. At behaviors over a 3-year period were correlated with future the other extreme, 29 of the drivers (36%) were never judged crash involvement. Table 1 shows the percentage increase in to be drowsy. Figure 5 shows the skewed frequency distribu- driver crash likelihood associated with the top behavioral tion of drowsiness episodes among the 80 drivers, plotted predictors. Note in the table that six different violation and with five frequency bins. Notice the classic skewed shape conviction types were more predictive than were past crashes of the frequency distribution, characteristic of differential themselves. This finding likely reflects the two advantages driver risk. The two drivers in the far right bin had 78 total noted earlier. It is not surprising that an egregious violation drowsiness episodes, which was more than the total number like reckless driving is predictive of future crashes, though of drowsiness episodes exhibited by the best 51 drivers in the strength of the relationship may surprise some. the study. Two driver subjects among the 80 were diagnosed with OSA, but they were not the two highest-risk drivers. TABLE 1 INCREASES IN CRASH LIKELIHOOD ASSOCIATED WITH Behavioral History PAST DRIVER BEHAVIORS Behavioral Predictor Increase in Crash Psychologists widely regard past behavior as the best single Likelihood predictor of future behavior (Ajzen 1991; Parker et al. 2001). Reckless driving violation 325% Behavioral history, sometimes called biodata (which might Improper turn violation 105% also include medical data), includes both driving events and Improper or erratic lane change conviction 100% nondriving events and indices relevant to safety behavior. This section reviews both areas. Failure to yield right-of-way conviction 97% Improper turn conviction 94% Driving Behavioral History Failure to maintain proper lane conviction 91% Past crash 87% There are at least two reasons to expect drivers' past driving Improper lane change violation 78% behaviors and events to be predictive. The first is the "metap- Failure to yield right-of-way violation 70% rinciple" of behavioral consistency over time. The second, of less interest here, is that driving environments and mileage Driving too fast for conditions conviction 62% exposure levels tend also to be consistent. False or no log book violation 56% Any conviction 56% A driver's history of crashes, violations, and other Speeding > 15 mph over speed limit 56% incidents is a well-documented predictor of future crash Source: Murray et al. (2005). involvements, and also whether the driver will be at fault in future crashes. Using a sample of more than 200,000 driv- ers (mostly noncommercial), Chandraratna and Stamatiadis Although violation history appears to be better than crash (2004) were able to predict the at-fault driver in crashes with history as a predictor of future crashes, a history of one par-
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18 ticular crash type might be considered a "red flag" for future risk. The principle of behavioral consistency suggests that peo- crash risk. This crash type is single-vehicle crashes. Single- ple will tend to behave similarly across different types of situa- vehicle crashes generally occur as a result of a catastrophic tions. Comparing people's lifestyles to their driving styles--or, loss of vehicle control, resulting in a road departure, rollover, more specifically, their personal problems and transgressions to or jackknife. In contrast, multivehicle crashes are usually trig- their driving mishaps--may predict driving safety. gered by a traffic interaction mistake such as "looked but did not see" or false assumption. Thus, single-vehicle crashes Criminality and personality traits like aggressiveness suggest a more profound failure of driving safety. In the and impulsivity are related to unsafe driving. In his book LTCCS (Starnes, 2006; Knipling, 2009b), truck single-vehicle Traffic Safety, Leonard Evans (2004) reviews studies show- involvements were much more likely than at-fault multivehicle ing greatly elevated crash risks--twofold or more--associ- involvements to involve asleep-at-the-wheel, driver physical ated with nondriving criminality. In Australia, Brace et al. failure (e.g., a medical event), excessive speeds, aggressive (2009) reviewed studies linking criminal history and road driving (as associated factor), response execution errors, and safety. The study looked at a variety of criminal behaviors vehicle maintenance failures (for which drivers are responsi- (e.g., assault, theft, drug offenses, and fraud) and different ble). Further, single-vehicle crash involvements seen in driver driving safety outcomes. It explored psychological theories records almost always imply culpability, whereas multive- explaining this relationship, including Kohlberg's Stages of hicle crash involvements may not have involved any fault by Moral Development (Kohlberg 1969). In this theory, moral the commercial driver (i.e., the other driver was at fault). The behavior is not just related to knowledge of laws and con- text box shows LTCCS truck/truck driver CR comparisons sequences of violating them, but also related to individu- between single-vehicle crash involvements and multivehicle als' internalization of social responsibilities and universal involvements. The latter includes both at-fault and non-at-fault moral principles. Among the many studies cited was one by involvements, consistent with driver records that show crash Chenery et al. (1999) in Britain where the vehicle status and involvements but not necessarily principal fault or cause. driver histories of vehicles parked illegally in handicapped spaces were compared with those of nearby legally parked vehicles. The study found that 20% of illegally parked vehi- Truck/Truck Driver CR Percentages for Single- vs. cles "would warrant immediate police attention," compared Multi-Vehicle (SV vs. MV) Involvements in LTCCS with just 2% of legally parked vehicles. The driver compari- sons were similar: 33% of the owners/drivers of illegally · Asleep-at-the-wheel (CR): parked vehicles had criminal records, versus 2% of controls. SV: 12.8%; MV: 0.4% A recent Society for Human Resources Management · Other physical failure (CR): survey (cited in Perry 2010) found that 60% of employers SV: 7.5%, MV: 0.9% check credit reports for at least some of their prospective employees, up from 42% in 2006. However, only 13% check · Too fast for conditions or curve (CR): all potential employees. Federal law requires that employers SV: 28.7%; MV: 5.4% obtain written permission from applicants before running a credit check on them. Cited in the same article was a 2008 · Aggressive driving: survey by the Association of Certified Fraud Examiners SV: 2.1%; MV: 0.2% which found that employee workplace fraud was often asso- ciated with personal debt and credit difficulties. · Response execution error (CR): SV: 8.2%; MV: 1.1% Chapter three shows that employers must be careful not to overreach in the use of assessments like credit checks in their · Vehicle failure (CR): hiring. Selection tests must be validated in relation to job SV: 12.7%; MV: 2.9% performance criteria. Credit history may be more directly relevant to driving jobs involving financial responsibilities Note: Includes all MV involvements. (e.g., owner-operators who must make payments on their vehicles) than to those without such responsibilities. Nondriving Behavioral History Cognitive (Mental) Abilities This section focuses on nondriving biographical information Intelligence is the ability to engage in complex thought. that might predict driving safety, including criminal record, General level of intelligence is a persistent characteristic of credit history, past bankruptcies, workers' compensation individuals that shows up in many different kinds of judg- claims, or other predictive behavioral indicators. Although ments, choices, and behaviors. Level of general intelligence these are not personal traits, they could be valid predictors of ("IQ score") is as effective as other major individual char-