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3
CHAPTER ONE
INTRODUCTION
BACKGROUND tions) is most indicative, although nondriving behavioral
history (e.g., criminal record) is predictive of risk as well
Research reveals large and enduring individual differences (Knipling et al. 2004).
in crash risk among commercial drivers. These differences
pervade the general population of drivers as well. Most com- Past research highlights the need for valid and usable
mercial drivers are reliable and safe, but a relatively small driver selection procedures for carriers. These selection
percentage (perhaps 10%15%) is heavily overinvolved in procedures seek to measure enduring individual differences
crashes and incidents. This phenomenon has been termed relevant to driving safety. Ideally, companies could employ a
differential driver risk. CTBSSP Synthesis 4 (Knipling et al. battery of tests, measurements, and questionnaires designed
2004) explored differential driver risk and high-risk drivers to fairly measure these driver traits and thereby identify
in particular. Evidence comes from various sources. Most likely high- and low-risk drivers. Research indicates that no
compelling are naturalistic driving studies, which use instru- one test is likely to be definitive. Tests must be validated
mented vehicles to reliably count driver involvements in at- against job performance criteria such as crash, violation, and
fault driving events, including crashes, near-crashes, and other incident rates. The opportunity for improving the quality of
incidents. Event counts can be compared with driver exposure fleet drivers is strongest when, owing to economic or other
(e.g., driving hours) to generate rates of driver involvements conditions, there are larger numbers of commercial driver
in at-fault events. The observed individual differences in applicants and carriers can afford to be more selective in hir-
driver risk are far greater than could possibly occur by chance ing. A caveat, however, is that greater selectivity increases
variation alone. For example, in one major large truck natural- fleet driver quality only if a fleet employs valid selection
istic driving study (Hickman et al. 2005), a subset of drivers procedures and devices. Multiple devices have the greatest
with just 19% of driving exposure was involved in 53% of all combined benefit when they tap into different driver traits
observed at-fault driving events. The remaining drivers, with and dimensions relating to risk.
81% of exposure, had just 47% of at-fault events.
One constraint on the use of selection tests in hiring
Although some drivers may change their driving styles commercial drivers is that all employee selection tests must
for better or worse over time, most individual differences meet Equal Employment Opportunity Commission (EEOC)
in driver risk are persistent (Miller and Schuster 1983; Lan- standards for test validity. These standards help to ensure
caster and Ward 2002). Indeed, many individual differ- that tests fairly capture job performance-related personal
ences in human performance and behavior are influenced dimensions and do not arbitrarily discriminate based on
by heredity (Larson and Buss 2005; Thiffault 2007). Prin- non-performance-related applicant characteristics. There
cipal correlates of differential driver risk include personal- are several ways of demonstrating job test validity. This
ity dimensions such as sensation-seeking, anger/hostility, report will review these requirements as they relate to car-
impulsivity, intensity (i.e., "Type A"), agreeableness, and rier practices to help ensure fair, legal, and safety-effective
conscientiousness. Individual perceptions and attitudes driver selection. This information, together with informa-
about risk are reflective of personality and of course affect tion on the tests themselves and their use within commercial
safety-related behaviors and outcomes. Mental abilities (e.g., transport, can be a useful foundation for carriers to make
spatial, mathematical) are also related to commercial driving greater use of selection devices as well as better choices
safety and other measures of employee success (Burks et al. among available instruments. Selection tests and measure-
2009). Driver risk can also be related to driver physical and ments for use by carriers will be described within the overall
sensorimotor abilities, such as dynamic vision, information framework of commercial driver qualifications, licensing,
processing proficiency, and reaction time. Various medical and federal requirements for the fair use of employee selec-
conditions are also associated with driver risk, including tion instruments.
cardiovascular illness, sleep apnea, other sleep disorders,
diabetes, and obesity. Behavioral history ("biodata") is also The safe selection of commercial drivers may be seen
predictive of commercial driver risk (Murray et al. 2005). within at least two larger contexts. The first of these is crash
Driving behavioral history (i.e., crashes and moving viola- risk factors in general. Much of road safety research seeks to
