The role of motorcyclist and other driver behaviour in two types of serious accident in the UK

Motorcycle accidents have somewhat different characteristics from accidents involving other classes of road user. They include in particular 'right of way' accidents, and accidents involving loss of control on curves or bends. A sample of 1790 accident cases was considered, including 1003 in detail, from UK midland police forces, involving motorcyclists of all ages, and covering the years 1997-2002 inclusive. Significant differences were discovered in the sample with respect to types of accidents involving motorcyclists (and their blameworthiness). There seems to be a particular problem surrounding other road users' perception of motorcycles, particularly at junctions. Such accidents often seem to involve older drivers with relatively high levels of driving experience who nonetheless seem to have problems detecting approaching motorcycles. Motorcyclists themselves seem to have far more problems with other types of accident, such as those on bends or curves. The implications of these findings are discussed.     

Personality domains and traits that predict self-reported aberrant driving behaviours in a southeastern US university sample

Personality traits are meaningful predictors of many significant life outcomes, including mortality. Several studies have investigated the relationship between specific personality traits and driving behaviours, e.g., aggression and speeding, in an attempt to identify traits associated with elevated crash risk. These studies, while valuable, are limited in that they examine only a narrow range of personality constructs and thus do not necessarily reveal which traits in constellation best predict aberrant driving behaviours. The primary aim of this study was to use a comprehensive measure of personality to investigate which personality traits are most predictive of four types of aberrant driving behaviour (Aggressive Violations, Ordinary Violations, Errors, Lapses) as indicated by the Manchester Driver Behaviour Questionnaire (DBQ). We recruited 285 young adults (67% female) from a university in the southeastern US. They completed self-report questionnaires including the DBQ and the Personality Inventory for DSM-5, which indexes 5 broad personality domains (Antagonism, Detachment, Disinhibition, Negative Affectivity, Psychoticism) and 25 specific trait facets. Confirmatory factor analysis showed adequate evidence for the DBQ internal structure. Structural regression analyses revealed that the personality domains of Antagonism and Negative Affectivity best predicted both Aggressive Violations and Ordinary Violations, whereas the best predictors of both Errors and Lapses were Negative Affectivity, Disinhibition and to a lesser extent Antagonism. A more nuanced analysis of trait facets revealed that Hostility was the best predictor of Aggressive Violations; Risk-taking and Hostility of Ordinary Violations; Irresponsibility, Separation Insecurity and Attention Seeking of Errors; and Perseveration and Irresponsibility of Lapses.     

Personality and behavioral predictors of traffic accidents: testing a contextual mediated model

A contextual mediated model was proposed to distinguish the distal (i.e. personality factors) and proximal (i.e. aberrant driving behaviors) factors in predicting traffic accident involvement. Turkish professional drivers (N=295) answered a questionnaire including various measures of personality factors, driver behaviors, and accident history. Results of the latent variable analysis with LISREL indicated that latent variables in the distal context (i.e. psychological symptoms, sensation seeking, and aggression) predicted at least one of the proximal elements (i.e. aberrant behaviors, dysfunctional drinking, and preferred speed) with relatively high path coefficients. While aberrant driver behaviors yielded a direct effect on accident involvement, psychological symptoms yielded an indirect effect mediated by driver behaviors. Further analyses revealed that personality factors had an impact on road accidents via their effects on actual driving-related behaviors although the path coefficients in predicting accidents were relatively weaker than those predicting risky driving behaviors and habits. Results were discussed considering the implications for classifying the accident correlates in a contextual framework and binominal-poisson distribution of self-reported accidents.     

Errors and violations in relation to motorcyclists' crash risk

This study was conducted to: (a) develop a questionnaire that reliably measures the behaviour of motorcyclists and (b) test which types of behaviour predict motorcyclists' crash risk. A Motorcycle Rider Behaviour Questionnaire (MRBQ), consisting of 43 items to measure the self-reported frequency of specific riding behaviours, was developed and administered to a sample of motorcyclists (N=8666). Principal components analysis revealed a 5-factor solution (traffic errors, control errors, speed violations, performance of stunts and use of safety equipment). Generalised linear modelling showed that, while controlling for the effects of age, experience and annual mileage, traffic errors were the main predictors of crash risk. For crashes in which respondents accepted some degree of blame, control errors and speed violations were also significant predictors of crash risk. Implications of the findings are discussed in relation to deciding which countermeasures may be most effective at reducing motorcycle casualty rates.     

Driver celeration behaviour and accidents – an analysis

A theory of changes in speed of a vehicle (termed ‘celerations’) as an overall measure of driver behaviour regarding the control of the vehicle, and as a predictor of traffic accidents, is described. The driver behaviours that result in speed changes of vehicles are speed, close following, braking and steering control actions. Assuming that all speed change indicates risk, several testable predictions follow. The most important of these is that there is a positive association between drivers’ celeration sum and their accidents. Formulas for the measurement of celeration and the association with crashes are presented, as well as methodological principles for this. Relevant literature is reviewed, as well as the tests of various hypotheses undertaken so far. The suggested way of measuring driver behaviour and predicting accident involvement would be useful in many kinds of studies of driver behaviour, and also for testing and screening purposes and especially for large-scale monitoring of professional drivers.     

Self-reported motorcycle riding behaviour among school children in India

Studies on traffic accidents among underage users of motorcycles are seldom seen in literature. This study was done in Yamunanagar, India where boys as young as 8 years ride motorcycles. It attempts to find out the behavioural and non-behavioural factors leading to motorcycle use and the predisposition to accidents among male school children aged between 10 and 16 years. A questionnaire was used to evaluate those factors among 1760 subjects in 38 schools. Fifteen percent of subjects had had an accident while riding motorcycle. Most of the behavioural and all the non-behavioural factors have a statistically significant influence on accident proneness. Aggressive behaviour and previous encounter with the police are the two strong predictors of accidents (p<0.001). Children as riders are exposed to higher risks of accident and longer life with disability. It also explains how these children behaviourally take up adult roles and seek adult risk taking attitudes. The implications of child motorcycle riders upon children themselves and on the society are discussed for a greater discourse on road safety motorcycle riding policy and to highlight the behavioural and non-behavioural factors that are associated with traffic accidents.     

Using the Attention Network Test to predict driving test scores

Driving is a complex multi-factorial task that taps underlying mechanisms of cognition and attention. Not surprisingly, therefore, many tests of cognition and attention are significantly associated with driving outcomes. In this article, we introduce driving researchers and clinicians with an interest in driving to the Attention Network Test (ANT), which to our knowledge has not previously been used in driving research. It is a recently developed test that is based on a neural network model of the human attention system. It combines elements of Posner’s cuing paradigm [Posner, M.I., 1980. Orienting of attention. Quarterly Journal of Experimental Psychology 32, 3-25.] with the Eriksen & Eriksen flanker task [Eriksen, B.A., Eriksen, C.W., 1974. Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics 16, 143-149.], and provides measures of three distinct functions of attention: alerting, orienting, and executive function. Our results demonstrate that the ANT has very good concurrent validity with the Useful Field of View (UFOV), and that it is comparable to UFOV in its ability to predict road test scores for a simulated drive. These findings suggest that further investigation of the usefulness of the ANT as a tool for driving researchers and clinicians is merited.     

Killer crashes: Fatal road traffic accidents in the UK

Road traffic accidents are responsible for over 3000 deaths per year in the UK, according to Department for Transport (2004a) figures. Although progress is being made in a number of areas, vehicle occupant fatalities have not been falling in line with casualty reduction targets for the year 2010. A sample of 1185 fatal vehicle occupant cases was considered, from ten UK police forces, from the years 1994-2005 inclusive. The main findings were: (1) over 65% of the accidents examined involved driving at excessive speed, a driver in excess of the legal alcohol limit, or the failure to wear a seat belt by a fatality, or some combination of these. (2) Young drivers have the great majority of their accidents by losing control on bends or curves, typically at night in rural areas and/or while driving for ‘leisure’ purposes. These accidents show high levels of speeding, alcohol involvement and recklessness. (3) Older drivers had fewer accidents, but those fatalities they were involved in tended to involve misjudgement and perceptual errors in ‘right of way’ collisions, typically in the daytime on rural rather than urban roads. Blameworthy right of way errors were notably high for drivers aged over 65 years, as a proportion of total fatal accidents in that age group.     

The Driver Behaviour Questionnaire in Arab Gulf countries: Qatar and United Arab Emirates

Manchester Driver Behaviour Questionnaire (DBQ) is one of the most widely used instruments for measuring self-reported driving style and investigating the relationship between driving behaviour and accident involvement. In spite of the fact that Arab Gulf countries have a higher road accident fatality rate compared to European countries and USA, the DBQ has not been used in Arab countries so far. The aim of the present study was to investigate the factor structure of the DBQ, then to examine the relationships between the factors of the DBQ and accident involvement, and finally to compare DBQ scores between the two gulf countries: Qatar and United Arab Emirates (UAE). In this study, 1110 Qatari (263 females and 847 males) and 1286 UAE drivers (294 females and 992 males) filled a survey questionnaire including the DBQ and background information. The results showed that UAE drivers scored higher on almost all DBQ items than Qatari drivers. Surprisingly, only very small differences between men and women on the DBQ item scores were found in UAE. Factor analysis resulted in four factors, which were named as errors, pushing-speeding violations, lapses, and aggression-speeding violations. However, there were a number of differences in the factor structure of the DBQ in UAE and Qatar when compared to the theoretical four-factor structure of the DBQ. Reliabilities of some subscales were also questionably lower than in the original British data. Logistic regression analyses showed that errors, lapses, and aggression-speeding violations predicted accident involvement in Qatar but not in UAE after controlling the effect of the demographic variables (age, sex, and annual mileage).     

Road accidents caused by drivers falling asleep

About 29600 Norwegian accident-involved drivers received a questionnaire about the last accident reported to their insurance company. About 9200 drivers (31%) returned the questionnaire. The questionnaire contained questions about sleep or fatigue as contributing factors to the accident. In addition, the drivers reported whether or not they had fallen asleep some time whilst driving. and what the consequences had been. Sleep or drowsiness was a contributing factor in 3.9% of all accidents, as reported by drivers who were at fault for the accident. This factor was strongly over-represented in night-time accidents (18.6%), in running-off-the-road accidents (8.3%), accidents after driving more than 150 km on one trip (8.1%), and personal injury accidents (7.3%). A logistic regression analysis showed that the following additional factors made significant and independent contributions to increasing the odds of sleep involvement in an accident: dry road, high speed limit, driving one's own car, not driving the car daily, high education, and few years of driving experience. More male than female drivers were involved in sleep-related accidents, but this seems largely to be explained by males driving relatively more than females on roads with high speed limits. A total of 10% of male drivers and 4% of females reported to have fallen asleep while driving during the last 12 months. A total of 4% of these events resulted in an accident. The most frequent consequence of falling asleep--amounting to more than 40% of the reported incidents--was crossing of the right edge-line before awaking, whereas crossing of the centreline was reported by 16%. Drivers' lack of awareness of important precursors of falling asleep--like highway hypnosis, driving without awareness, and similar phenomena--as well as a reluctance to discontinue driving despite feeling tired are pointed out as likely contributors to sleep-related accidents. More knowledge about the drivers' experiences immediately preceding such accidents may give a better background for implementing effective driver warning systems and other countermeasures.     

Drink driving and traffic accidents in young people

The relationship between drink driving behaviours and rates of traffic accidents was analysed in a birth cohort of 907 New Zealand young people studied to the age of 21. Drink driving was significantly (P<0.0001) related to active traffic accidents in which the driver’s behaviour contributed to the accident but was not related to passive accidents in which driver behaviours did not contribute to the accident (P>0.15). Those engaging in high rates of drink driving had rates of active traffic accidents that were 2.6 times higher than those who did not drink and drive. Further analysis suggested that much of this association was explained by confounding factors (and notably driver behaviour) that were associated with both drink driving and accident rates. After adjustment for confounding factors, those engaging in high rates of drink driving had rates of active accidents that were 1.5 (P<0.01) times higher than those who did not drink and drive. It is concluded that although the study findings support the view that the regulation of drink driving behaviour amongst young people is likely to contribute to a reduction in traffic accidents, to be fully effective attempts at regulation of drink driving also need to be accompanied by a similar level of investment in regulating other aspects of risky or illegal driving behaviour amongst young people.     

An experimental study of factors associated with driver frustration and overtaking intentions

This study examined directly the impact of various factors associated with driving on ‘A-class’ roads in the United Kingdom (specifically length of platoon, proportion of heavy goods vehicles (HGVs), speed and opportunities for overtaking) on self-reported frustration and overtaking intentions. The impact of situational variables (being under time pressure, and time behind a slower moving platoon) were also examined, as was the association between frustration and self-reported overtaking intentions. 183 members of the public from the areas around Perth and Inverness, Scotland took part in the study. Participants viewed simulated ‘driver’s viewpoint’ clips representing all the combinations of the experimental variables (except time pressure, which was a between-groups variable, and time behind platoon, which was examined separately in four specific clips). After each clip, participants responded on a paper questionnaire as to the level of frustration they would feel for a given clip, and the likelihood that at some point during the clip they would have attempted an overtake manoeuvre. The findings show that the links between traffic variables such as speed and platoon length, and behaviourally-relevant variables such as frustration and overtaking intentions, are not simple. Although there are broad and predictable effects of speed and platoon length (lower speeds and longer platoons leading to greater frustration) these are mediated by other variables, and it is not always the case that more frustration leads to more intention to overtake. Analysis of driver attitudes identified three clusters (low, medium and high risk drivers) and suggests that higher risk drivers’ levels of frustration are more affected by situational changes than those of lower risk drivers.     

A comparison of the hazard perception ability of accident-involved and accident-free motorcycle riders

Hazard perception is the ability to read the road and is closely related to involvement in traffic accidents. It consists of both cognitive and behavioral components. Within the cognitive component, visual attention is an important function of driving whereas driving behavior, which represents the behavioral component, can affect the hazard perception of the driver. Motorcycle riders are the most vulnerable types of road user. The primary purpose of this study was to deepen our understanding of the correlation of different subtypes of visual attention and driving violation behaviors and their effect on hazard perception between accident-free and accident-involved motorcycle riders. Sixty-three accident-free and 46 accident-involved motorcycle riders undertook four neuropsychological tests of attention (Digit Vigilance Test, Color Trails Test-1, Color Trails Test-2, and Symbol Digit Modalities Test), filled out the Chinese Motorcycle Rider Driving Violation (CMRDV) Questionnaire, and viewed a road-user-based hazard situation with an eye-tracking system to record the response latencies to potentially dangerous traffic situations. The results showed that both the divided and selective attention of accident-involved motorcycle riders were significantly inferior to those of accident-free motorcycle riders, and that accident-involved riders exhibited significantly higher driving violation behaviors and took longer to identify hazardous situations compared to their accident-free counterparts. However, the results of the regression analysis showed that aggressive driving violation CMRDV score significantly predicted hazard perception and accident involvement of motorcycle riders. Given that all participants were mature and experienced motorcycle riders, the most plausible explanation for the differences between them is their driving style (influenced by an undesirable driving attitude), rather than skill deficits per se. The present study points to the importance of conceptualizing the influence of different driving behaviors so as to enrich our understanding of the role of human factors in road accidents and consequently develop effective countermeasures to prevent traffic accidents involving motorcycles.     

Previous convictions or accidents and the risk of subsequent accidents of older drivers

The over-involvement of elderly drivers in collisions has a potentially adverse effect on highway safety. The question for most experts in traffic research is whether we can predict the individual risk of accidents and which variables are the best predictors, especially for this population. For a better understanding of the elderly drivers' problems, this study aimed to describe the most common types of accidents in the elderly population of drivers living in Quebec (> or = 65 years of age). The second objective of the study was to analyse the relationship between previous accidents or convictions and the risk of subsequent accidents. The results show that: (1) elderly drivers are characterised by error accidents involving more than one car, especially at intersections, (2) prior accidents are a better predictor for accident risk than prior convictions and (3) these trends steadily increase with each age group (drivers 65 years old to 80 years or more). The results are discussed in relation to the literature on risk behaviour of the elderly drivers.     

Validity of the traffic conflicts technique

The traffic conflicts technique was developed as a tool for estimating accident potential at intersections and for indicating methods of reducing hazardous conditions. A review of evaluation studies fails to confirm that the method can perform these tasks. This results partly from methodological problems in the studies. Differences in the definitions of both accidents and conflicts have produced results which often are incomparable simply because different pairs of variables have been used in the analyses. Other theoretical inconsistencies appear to limit the likelihood of predicting accidents from conflicts. It is suggested that a hierarchy of traffic events ranging in severity from slight conflicts to fatal accidents exists. Certain fundamental characteristics of these events (including time of occurrence, type of manoeuvre, location and probable cause) differ so markedly that the prediction of one from the other may not be possible. Evidence is presented which indicates that neither accident nor conflict data, recorded using present methods, is of much value in predicting future accidents or conflicts, respectively. It is suggested that a new method of recording conflicts which overcomes the conceptual problems of previous definitions may be useful in evaluating countermeasures at least as an experimental tool. This would require a change in the criterion used for assessing the benefits of countermeasures from one of the reduction in accidents to one of eliminating predetermined improper driving behaviour or operational problems.     

Road accidents caused by sleepy drivers: Update of a Norwegian survey

The current study tests, updates and expands a model of factors associated with sleepy driving, originally based on a 1997 survey of accident-involved Norwegian drivers (Sagberg, F., 1999. Road accidents caused by drivers falling asleep. Accident Analysis & Prevention 31, 639–649). The aim is to establish a robust model to inform measures to tackle sleepy driving. The original questions on (i) tiredness-related accidents and (ii) incidents of sleep behind the wheel in the last 12 months were again posed in 2003 and 2008, in independent surveys of Norwegian drivers involved in accidents reported to a large insurance company. According to those drivers at-fault for the accident, tiredness or sleepiness behind the wheel contributed to between 1.9 and 3.9 per cent of all types of accident reported to the insurance company across these years. Accident-involved drivers not at fault for the accident reported a reduction in the incidence of sleep behind the wheel for the preceding year, decreasing from 8.3 per cent in 1997 to 2.9 per cent in 2008. The reasons for this are not clear. According to logistic regression analysis of survey responses, the following factors were robustly associated with road accidents involving sleepy driving: driving off the road; good road conditions; longer distance driven since the start of the trip; and fewer years with a driving licence. The following factors are consistently associated with reports of sleep behind the wheel, whether or not it leads to an accident: being male; driving further per year; being younger; and having sleep-related health problems. Taken together these findings suggest that young, inexperienced male drivers who drive long distances may be a suitable target for road safety campaigns aimed at tackling sleepy driving.     

Motorcyclists’ speed and “looked-but-failed-to-see” accidents

Previous research on motorcycle crashes has shown the frequency and severity of accidents in which a non-priority road user failed to give way to an approaching motorcyclist without seeing him/her, even though the road user had looked in the approaching motorcycle's direction and the motorcycle was visible. These accidents are usually called “looked-but-failed-to-see” (LBFS) accidents. This article deals with the effects that the motorcyclist's speed has in these accidents. It is based on the in-depth study and precise kinematic reconstruction of 44 accident cases involving a motorcyclist and another road user, all occurring in intersections. The results show that, in urban environments, the initial speeds of motorcyclists involved in “looked-but-failed-to-see” accidents are significantly higher than in other accidents at intersections. In rural environments, the difference in speed between LBFS accidents and other accidents is not significant, but further investigations would be necessary to draw any conclusions. These results suggest that speed management, through road design or by other means, could contribute to preventing “looked-but-failed-to-see” motorcycle accidents, at least in urban environments.     

Analysis of traffic injury severity: an application of non-parametric classification tree techniques

Statistical regression models, such as logit or ordered probit/logit models, have been widely employed to analyze injury severity of traffic accidents. However, most regression models have their own model assumptions and pre-defined underlying relationships between dependent and independent variables. If these assumptions are violated, the model could lead to erroneous estimations of injury likelihood. The classification and regression tree (CART), one of the most widely applied data mining techniques, has been commonly employed in business administration, industry, and engineering. CART does not require any pre-defined underlying relationship between target (dependent) variable and predictors (independent variables) and has been shown to be a powerful tool, particularly for dealing with prediction and classification problems. This study uses the 2001 accident data for Taipei, Taiwan. A CART model was developed to establish the relationship between injury severity and driver/vehicle characteristics, highway/environmental variables and accident variables. The results indicate that the most important variable associated with crash severity is the vehicle type. Pedestrians, motorcycle and bicycle riders are identified to have higher risks of being injured than other types of vehicle drivers in traffic accidents.     

The deviation concept in occupational accident control—I: Definition and classification

This paper, presented in two parts, assesses the potentialities and limitations of the deviation concept as applied to occupational accident control. A systems variable is classified as a deviation when its value falls outside a norm. In Part I, a systems model of accidents that incorporates the deviation concept is presented. Theories, models, terms, and taxonomies of the occupational accident research literature are analyzed in relation to this model in order to identify general elements. Theoretical and methodological problems concerning the definition of norms and taxonomies of deviations are discussed. In Part II measures of the significance of deviations with respect to the risk of accidents and criteria for the assessment of methods for the collection of data on deviations are operationalized. Empirical research on relations between deviations and accidents and on methods for data collection are reviewed on the basis of these measures and criteria. It is concluded that the deviation concept provides a valid basis for the design of information systems for the efficient control of accidents in production systems in operation. Considerations for the design of information systems for the collection, storing, processing, and feedback of information on deviations for accident prevention purposes are discussed.