Professional Driver Training and Driver Stress: Effects on Simulated Driving Performance

Book chapter from Traffic and Transport Psychology, edited by G. Underwood, published by Elsevier, 2005

How reliable are self-report measures of mileage, violations and crashes?

The use of self-reported driver mileage, violations and crashes is very popular in traffic safety research, but their validity has been questioned. One way of testing validity is with an analysis of test–retest reliability. Three mechanisms might influence reliability in self report; actual changes in the variable over time, stable systematic reporting bias, and random error. Four samples of drivers who had responded twice to an online questionnaire asking them to report their mileage, violations and crashes were used and correlations between self reports for this data were calculated. The results for crashes were compared to expected correlations, calculated from the error introduced by the non-overlapping periods and the variable means. Reliability was fairly low, and controlling for mileage in the violations and crashes calculations did not strengthen the associations. The correlation between self reports of crashes in different time periods was found to be much larger than expected in one case, indicating a report bias, while the other correlation agreed with the predicted value. The correlations for overlapping time periods were much smaller than expected. These results indicate that drivers’ self reports about their mileage, violations and crashes are very unreliable, but also that several different mechanisms are operating. It is uncertain exactly under what circumstances different types of self report bias is operating. Traffic safety researchers should treat the use of self-reported mileage, violations and crashes with extreme caution and preferably investigate these variables with the use of objective data

Individual and group differences in driving behaviour

Road traffic accident involvement rates show that younger males are over represented in accidents. A number of studies have shown individual differences in accident involvement. Questionnaire-based methods to investigate individual and group differences in driver stress and risk perceptions reported in chapter 2 and 3 revealed that neuroticism was associated with; heightened perception of personal risk, driver stress, and inefficient coping strategies. Younger drivers and female drivers reported higher levels of stress. Young male drivers assessed their personal risk and driving abilities less realistically than did other age and sex groups. Driving simulator-based methods reported in chapter 4 revealed that young drivers and male drivers; drive faster, overtake more often, and commit more `high risk' overtakes than do other age and sex groups. Middle-aged and elderly drivers were poorer at maintaining a fixed distance from a lead `vehicle'. Older drivers adopt a slower, more cautious driving style, but appear to be worse at controlling distance from a `lead' vehicle. Results are consistent with individual and group differences in accident involvement rates. Findings are discussed with reference to the implementation of driver education programs to reduce stress, the adoption of more realistic perceptions of risk among younger drivers, and the training of compensation strategies to counteract age-related changes in older drivers

Work related road safety: Age, length of service and changes on crash risk

Age and experience are known to be major factors in road traffic collisions (Maycock et al., 1996) and are commonly used as predictors of crash frequency (Evans and Courtney, 1985). But age and experience are difficult to separate when investigating crash risk (Brown, 1982; Ryan et al., 1998; Mayhew and Simpson, 1990; Bierness, 1996). Experience is closely related to age but independently influences crash risk. For age, mileage-adjusted crash risk declines with age but then rises for drivers over 65 (Maycock et al., 1991). This is thought to be due to physical and cognitive declines in older people and to increased risk-taking in younger drivers (Chipman et al., 1992; Clarke et al., 1998; McGwin and Brown, 1999). For experience, even limited driving experience has a major effect on road safety. For example, there is a disproportionately higher crash rate during the first year of driving, particularly in the first few months after licensure (Sagberg, 1998). For age and experience, Mayhew et al. (2003) found larger decreases in crash risk amongst younger novices compared with older novices during the first few months of driving. This was interpreted as due to greater initial risk-taking amongst younger novices, with on-road driving experience facilitating a more rapid learning rate compared with older novices. They suggest that this was an appropriate point at which to provide training intervention. There is reasonable literature on the effects of age and experience on accident involvement, but little is known about whether these effects can be generalised to professional drivers, especially since professional drivers differ substantially from the general population of drivers

Experience as a safety factor in driving; Methodological considerations in a sample of bus drivers

Experience is generally seen as an important factor for safe driving, but the exact size and details of this effect has never been meta-analytically described, despite a fair number of published results. However, the available data is heterogeneous concerning the methods used, which could lead to very different results. Such method effects can be difficult to identify in meta-analysis, and a within-study comparison might yield more reliable results. To test for the difference in effects between some different analytical methods, analyses of data on bus driver experience and crash involvement from a British company were conducted. Effects of within- and between-subjects analysis, non-linearity of effects, and direct and induced exposure methods were compared. Furthermore, changes in the environmental risk were investigated. Between-subject designs yielded smaller effects as compared to within-subjects designs, while non-linearity was not found. The type of exposure control applied had a strong influence on effects, as did differences in overall environmental risk between years. Apparently, “the effect of driving experience” means different things depending upon how calculations have been undertaken, at least for bus drivers. A full meta-analysis, taking several effects of methodology into account, is needed before it can be said that the effect of driving experience on crash involvement is well understood

Behavioural culpability for traffic accidents

This study presents a description of the concept of behavioural culpability, a step-by-step manual for using it, and an empirical test of a suspected mis-classification of culpability. Behavioural culpability is defined as whether the driver’s actions contributed to a crash and that non-culpable crashes are not caused by any specific behaviour and can only be predicted from exposure. Drivers with non-culpable crashes are therefore a random sample of the population. However, if the criteria for culpability and/or the individual judgements are not reflective of the principle of behavioural culpability, no fault drivers will not be a random sample of the driving population. To test the predictions from the definition of randomness in a sample assumed to have sub-optimal coding, the categorization of crash involvement undertaken by a British bus company was tested for associations between at fault and no fault crashes, age and experience. As predicted from the low percentage of at fault accidents in the sample, correlations between the variables indicated that a fair percentage of at fault crashes had been coded as no fault of the bus driver, suggesting a too lenient criterion. These results show that within fleet-based companies, culpability for a crash is probably allocated for legal reasons, which means that the predictability of accident involvement taking into account individual differences is not fully utilized. The aim of behavioural culpability coding is to increase effect sizes in individual differences in safety research and to improve our capability of predicting accident involvement

A cluster randomised controlled trial (cRCT) evaluation of a pre-driver education intervention using the Theory of Planned Behaviour

Road traffic injuries are the leading of cause of death of 5–29-year-olds worldwide (World Health Organisation, 2018) making young driver safety a global public health concern. Pre-driver road safety education programmes are popular and commonly delivered with the aim of improving safety amongst this at risk group but have rarely been found to be effective (Kinnear, Lloyd, Helman, Husband, Scoons, Jones et al., 2013). A pre-driver education intervention (DriveFit) was designed and evaluated with a cluster randomised controlled trial (cRCT) using the Theory of Planned Behaviour (TPB) (Ajzen, 1991). The responses of 16–18-year-old students (n = 437) from 22 schools/colleges in Devon, UK were analysed and showed that the DriveFit intervention led to some small improvements in risk intentions, attitudes, and other measures, which differed by sub-group. Speed intentions improved immediately post- intervention (T2), whereas a composite measure of all intentions and mobile phone use intentions improved at 8–10 weeks post-intervention (T3). Apart from speed intentions, a trend towards intentions becoming safer at T3 was noted. Mobile phone use and speeding attitudes, a composite measure of attitudes, as well as attitudes to driving violations and perceptions of risk, improved at T2 and T3, with the size of the effect slightly reduced at T3. Participants expressed safe views at baseline (T1), which overall left minimal room for improvement. Whilst previous research has found that education interventions deliver small self-reported effects, that diminish over time (i.e., Poulter and McKenna, 2010), this study finds small, but lasting attitude effects (which diminish in magnitude over time) and a trend towards improving intentions, over and above the control group. The findings provide some guidance on future research to design and evaluate educational interventions for pre- and novice drivers

Design and development of a bus simulator for bus driver

The bus industry is plagued by high accident costs and risks of passenger injuries. A bus simulator may offer a method of reducing accident rates by delivering targeted training to bus drivers who are most at risk. The first part of this thesis describes the design of the UK's first bus simulator, the fidelity of which was based on a thorough analysis of bus crashes. The second part describes the first studies in a multi-staged method to evaluate the training effectiveness of the simulator: face validity, effects of bus driver experience and stress on simulated performance and simulator sickness. This approach ensured that the ABS has a reasonable level of fidelity, is capable of eliciting behaviourally valid responses from bus drivers and is the first step is achieving training transfer effectiveness. The final study investigated the occurrence of self-bias in bus drivers. The conclusions drove the design of simulated scenarios to be used for bus driver training. Keywords: Bus, Simulator, Fidelity, Validity, Accidents, Driving, Stress, TrainingEThOS - Electronic Theses Online ServiceGBUnited Kingdo

The effects of Electronic Stability Control (ESC) on fatal crash rates in the United States

Problem: Electronic Stability Control (ESC) is believed to be among the most efficient vehicle safety interventions with reported effects around 50% for fatal single and rollover crashes. However, such estimates have used sample data, which have not controlled for the possibilities of self-selection, behavioral adaptation, increased access to the technology by less safe drivers, and the calculation of effects on very specific categories of crashes. Effects of ESC in the population can therefore be expected to be smaller than is currently believed. Method: National U.S. data for fatal crashes, driving exposure and other control factors, and market penetration of ESC over 1991–2021 were used to calculate whether the trends in fatalities over time in crash rates for singles, rollovers, and fatal crashes in general matched projections from estimates of effectiveness. Results: It was found that downward trends in the relevant crash types were generally present before ESC was introduced, and that the trends thereafter were weaker. Although some trends were consistent with effects of ESC, they were markedly smaller than the projected ones, and could be explained by other factors such as the number of vehicles per capita. At best, the effect for rollovers could be up to two-thirds of previous estimates, no effect was detected for singles, while for all fatal crashes results depended upon the type of analysis performed. These results conflict with conclusions in all published ESC crash sample studies, which have compared vehicles with and without ESC. This discrepancy can be explained by methodological errors in the previous studies using induced exposure methods and self-selected samples. Practical applications: Traffic safety may not be as much improved by technological interventions as believed. Alternative approaches to traffic safety are needed, which do not rely on technology that interferes with driver behavior.Engineering and Physical Sciences Research Council: grant number: EP/V026763/

Accident proneness of bus drivers; controlling for exposure

It is argued that the reason that previous evidence apparently did not support the accident proneness hypothesis was faulty methodology and erroneous interpretations of results. Between time periods correlations of traffic accident records actually show an impressive stability over time when restriction of variance is controlled for. However, stability can be caused by stable differences in exposure. Correlations of accident records between time periods were analysed comparing full time and part-time bus drivers. For drivers who worked full time, the amount of exposure was held semi-constant while part-time drivers could be expected to work differing hours. If differential exposure causes stability in crash record, then part-time drivers should yield stronger correlations between time periods for crashes compared with full-time drivers. Between time periods accident correlations for part-time drivers were weaker than the corresponding ones for full time drivers. Correlations increased with increasing variance in the data. Results for all crashes fit in well with other meta-data, while culpable crashes did not, probably due to faulty coding. The current results support the notion of the tendency to cause traffic accidents as a stable trait within individuals as this is apparently not caused by stable differences in exposure