Two Driver Behavior Red Flags
TASA ID: 9075
I’m a psychologist who has devoted my career to traffic safety, in particular fleet safety. Two psychological laws of human behavior are the Law of Individual Differences and the Law of Behavioral Consistency (Holland, 1975). In any group of people, such as a fleet of drivers, one can expect wide differences in behavioral tendencies. Psychological differences most relevant to safe driving include sensation-seeking, risk perception, impulsivity, and conscientiousness (i.e., obeying rules). At the same time, each individual’s behavioral tendencies are likely to stay remarkably consistent over time and across various situations. Indeed, the psychological definition of personality is behavioral consistency over time and across situations. Future behavior and risk can be predicted based on past behaviors and events. That’s why we screen fleet drivers for their driving histories and more broadly for their personal histories in other areas of their lives.
Fleet managers should think positively and seek to recognize and reward safe driving and loyal service. Yet one must be alert for red flags signaling risk. One bad driver can damage the reputation and even the viability of a whole fleet. Among those red flags are safety belt non-use and involvement in single-vehicle crashes such as rollovers and run-off-road.
Commercial driver safety belt use in the U.S. has improved to nearly 90%, but that still leaves just over 10% of drivers who do not buckle up. These drivers are obviously at greater risk for higher severity injuries in any crashes that may occur. Is it also possible that they are more likely to be involved in crashes? Research says, “yes.” In the Large Truck Crash Causation Study (LTCCS), crash-involved, non-belt-using truck drivers were 30% more likely to be assigned the Critical Reason (i.e., at-fault; made the critical error) in their crashes than were belt users (Knipling, 2009b).
Studies of light vehicle drivers corroborate the link between non-belt use and driver risk. In an observational study of 20,000 drivers, Eby et al. (2003) found that non-belt users were 80% more likely to also be using a cell phone. Bloomberg and Thomas (2010) found that non-belt users drank more alcohol and were about twice as likely to have past alcohol citations. They also had histories of more speeding, reckless driving and license-related violations. They even had more past criminal offenses, including violent crimes. In a summary of past research, Eby (2010) posited individual risk perception as the key factor underlying belt use/non-use. Non-appreciation of risk was the most frequent driver reason for non-belt use; more common than forgetting, discomfort, inconvenience, and other reasons.
For non-belt users, there is a multiplicative relationship between increased crash risk and increased injury risk in crashes that occur. If they have a 1.5x probability of being in a crash, and a 3x increase in injury severity in crashes that occur, that gives them an overall 4.5x severe injury risk per mile of driving. These are reasonable extrapolations based on available statistics (Knipling, 2009a).
Non-belted truck drivers in the LTCCS were 84% more likely to be involved in single-vehicle crashes, relative to involvement in multi-vehicle crashes. Single-vehicle crashes are, for the most part, fundamentally different from multi-vehicle crashes in their causation. They typically indicate a failure of driver vehicle control, whereas multi-vehicle crashes reflect primarily a failure of response to traffic events (Knipling, 2009a). Compared to at-fault multi-vehicle crash involvements, LTCCS single-vehicle crash involvements were 13 times more likely to have a proximal cause of asleep-at-the-wheel, three times more likely to involve a heart attack or other medical event, three times more likely to be due to a response-execution failure (e.g., over-correction after a swerve), and more than twice as likely to involve excessive speed (Knipling, 2009b).
Knipling (2017) compared LTCCS truck statistics for trucks to car driver statistics from the National Motor Vehicle Crash Causation Survey or NMVCCS. These two studies were similar except that one focused on large trucks while the other focused on cars.
Driver Critical Reasons (proximal errors) in each study were divided into six main categories:
(1) non-performance (e.g., asleep);
(2) inadequate surveillance (“looked but did not see”);
(3) other recognition failure;
(4) too fast;
(5) other decision failure (e.g., decision to tailgate or cross traffic); and
(6) maneuver execution error.
For both kinds of drivers, single-vehicle crashes were much more likely to be caused by impairment or by dangerous behavioral choices such as the choice to speed. In contrast, at-fault multi-vehicle crashes were more likely due to driver mistakes such as “looked but did not see.” Which type of driver error could you more easily forgive - an intentional misbehavior or an unintentional mistake?
Fleet safety directors should monitor their drivers’ behaviors, both good and bad. In surveys, safety directors say that most drivers will respond positively and improve their driving when safe behaviors are recognized and rewarded (Knipling et al., 2004). Recurring driver mistakes can be reduced with constructive feedback. Yet these same safety directors say that there are big individual differences in driver risk which endure over time. Risky drivers are less responsive to feedback. Safety belt non-use and single-vehicle crash involvements are two behavioral red flags signaling that a driver’s risk level is not likely to markedly change in the foreseeable future.
Bloomberg, R. & Thomas, D. Characteristics of non-belt users: day and night. Presentation in Session 649, National Academies’ Transportation Research Board (TRB) 89th Annual Meeting, Washington, D.C. 2010.
Eby, D. Potential mechanisms underlying part-time belt use. Presentation in Session 649, TRB 89th Annual Meeting, Washington, D.C. 2010.
Eby, D.W., Kostyniuk, L.P., & Vivoda, J.M. Risky driving; relationship between cellular phone and safety belt use. Trans. Res. Record No. 1843, TRB ISSN 0361-1981, ISBN 0-309-08577-2, Pp. 20-32, 2003.
Holland, M.K. Using Psychology; Principles of Behavior and Your Life. Little, Brown, & Co. Boston, 1975.
Knipling, R.R., Safety for the Long Haul; Large Truck Crash Risk, Causation, & Prevention. American Trucking Associations (ATA). ISBN 978-0-692-00073-1, 2009a. Available here.
Knipling, R.R. Three large truck crash categories: what they tell us about crash causation. Proceedings of the Driving Assessment 2009 conference, Pp. 31-37, Big Sky, Montana, June, 2009b.
Knipling, R.R. Crash heterogeneity: implications for naturalistic driving and for understanding crash risks. Paper 17-02225, Session 247, TRB Annual Meeting, Washington DC, 2017. Published in Transportation Research Record No. 2663. Available online here.
Knipling, R.R., Boyle, L.N., Hickman, J.S., York, J.S., Daecher, C., Olsen, E. C. B., and Prailey, T.D. Synthesis Report #4: Individual Differences and the High- Risk Commercial Driver. Project Final Report, Transportation Research Board Commercial Truck & Bus Synthesis Program. ISSN 1544-6808, ISBN 0-309-08810-0, available here, 2004.
Bio
This expert is the author of Safety for the Long Haul; Large Truck Crash Risk, Causation, & Prevention, the only comprehensive textbook on large truck safety. In recognition of the book, he received the International Road Transport Union (IRU) Order of Merit award, the first given to an American scientist. He is a traffic safety researcher, consultant, and expert witness based in the Washington, DC area. For more information click here.
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