Has the difference in accident patterns between male and female drivers changed between 1984 and 2000?

The motorcar accident pattern of culpable young (18-25 years old) and middle-aged (35-55 years old) male and female drivers was studied in Finland. The aim was to see whether the difference in accident patterns between males and females has remained constant or whether it has changed over a 16-year period. Two different sets of traffic accident data were used. The first set of data covered all motorcar accidents for which damages were paid between 1987 and 2000, a total of 140802 accidents. The second set of data covered all fatal motor vehicle accidents in Finland during the time period between 1984 and 2000, a total of 2401 accidents. The results are analysed and discussed in the framework of a four-level hierarchical model of driving behaviour [Keskinen, E., 1996. Why do young drivers have more accidents? In: Junge, F., Fahrerinnen (Eds.), Young Drivers (in German and in English). Berichte der Bundesanstalt für Strabetaenwesen, Mensch und Sicherheit, Heft M 52, Bergisch Gladbach, Germany; Hatakka, M., Keskinen, E., Gregersen, N.P., Glad, A., Hernetkoski, K., 2002. From control of the vehicle to personal self-control; broadening the perspectives to driver education. Transportation Res. Part F 5 (3), 201-215]. Female drivers had proportionally more accidents that were connected to vehicle manoeuvring and control of traffic situations, e.g. reversing and loss-of-control accidents in a sober state and when not speeding. Male drivers, and especially young male drivers, had proportionally more accidents connected to higher levels of driving behaviour like motives for driving and attitudes. Factors that characterised these accidents were speeding and alcohol consumption. Male drivers also had previous traffic offences more often than female drivers. The study concludes that the difference in accident patterns between male and female drivers has remained constant, i.e. the accident pattern of female drivers was as dissimilar to the accident pattern of male drivers in the year 2000 as in the middle of the 1980s.     

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.     

Voluntary risk taking and skill deficits in young driver accidents in the UK

In absolute terms, young drivers have three to four times as many accidents per year as older drivers; and even allowing for their relative numbers in the population, their accident involvement is about 2.5 times higher than older drivers. A sample of 3437 accident reports was considered, including 1296 in detail, from midland police forces in the UK, involving drivers aged 17-25, and covering the years 1994-1996 inclusive. Four types of accident were identified as being of particular concern due to their high frequency: 'cross-flow'-turns; rear-end shunts; loss of control on bends; and accidents in darkness. (The term 'cross-flow' is used in relation to turns to denote an intersection accident where a driver is turning across the path of oncoming traffic, i.e., left turns in the US and continental Europe, but right turns in the UK and other countries where driving on the left side of the road is the norm.) An examination of driver risk taking behaviours as revealed in police interviews gave an insight into some of the motivational factors underlying young driver behaviour. Young driver accidents of all types are found to be frequently the result of 'risk taking' factors as opposed to 'skill deficit' factors. It had previously been thought that one of the main problems that young drivers have is in the area of specific skills needed in the driving task. However, it appears that a large percentage of their accidents are purely the result of two or three failures resulting from voluntary risk taking behaviour, rather than skill deficits per se. It is shown that specific groups of young drivers can even be considered as above average in driving skills, but simultaneously have a higher accident involvement due to their voluntary decisions to take risks.     

Difficulties with quasi-induced exposure when speed varies systematically by vehicle type

The attractiveness of quasi-induced exposure lies in the simplistic nature of its theory and application. As opposed to vehicle miles of travel, quasi-induced exposure is developed solely from the accident data themselves. Involvement ratios (IRs) are used to describe the relative over- or under-involvement of different driver-vehicle combinations in traffic accidents. The issue of systematic bias in the involvement ratios is explored, and it is shown both theoretically and empirically that the variation in average speeds between vehicle types can affect relative accident involvement ratios. For vehicle types that routinely travel faster, the IRs will likely be underestimated; while for slower-moving vehicle types, the IRs will be overestimated. In the case of speed, the magnitude of the effect on the IRs is dependent both on the magnitude of the speed differential and the percentage of slower vehicles in the traffic stream. Conclusions can be extended to whenever there are speed or other behavior disparities associated with the driver-vehicle combinations in the traffic stream. Other examples include the speed discrepancy caused by different drivers (e.g., younger versus older drivers). Caution must be used in interpreting results from applications of the quasi-induced technique whenever such biases might be encountered.     

Multidisciplinary in-depth investigations of head-on and left-turn road collisions

To enhance traffic safety, a multidisciplinary Road Accident Investigation Team was established in Denmark for a 2-year trial period. The objective was to conduct in-depth investigations of specific types of accidents, and to identify effective preventive measures. The team consisted of a road engineer, a vehicle inspector, a police superintendent, a psychologist and a physician. Seventeen serious head-on collisions as well as 17 left-turn collisions were analysed. In collecting data, police reports were supplemented by the team's investigation of accident sites and vehicles involved, and interviews were carried out with the involved road users and witnesses. The drivers, to whom the accident factors were primarily related in the head-on collisions, were characterised by their conscious risk-taking behaviour. They were all males; several of them were under age 40 and had earlier traffic and/or drug convictions. The main accident factors were excessive speed, drunk driving and driving under the influence of illegal drugs. In the left-turn accidents, the most common accident factors were attention errors, and it was also noted that elderly drivers ( > 74) were over-represented. The synergy effect of working as a multidisciplinary team proved fruitful. It resulted in a more precise knowledge of the road accident circumstances and of contributing factors leading up to the accidents. Due to the great demand on resources, only a limited number of accidents could be analysed, but the results provide a basis for further and more targeted research.     

The effectiveness of antilock braking systems in reducing accidents in Great Britain

Antilock braking systems (ABS) are fitted to many new cars with the aims of improving their ability to steer while braking heavily and of reducing stopping distances on some road surfaces. This paper presents the findings of a project that assessed the effectiveness of ABS in reducing accidents in Great Britain. A large postal survey was carried out of the owners of modern cars. asking for details of any accidents in which they had been involved during the previous year as well as factors that might influence their likelihood of being involved in an accident. Questions were also asked to test respondents' knowledge of ABS. ABS cars ditfered in several respects from non-ABS cars, as did the two groups of drivers. Consequently, a sophisticated statistical analysis was required to provide unbiased estimates of the effectiveness of ABS. Various results did not achieve statistical significance, but the overall stability of the results indicates that real effects have been measured. They confirm that ABS does have the potential to reduce the number of accidents, but show that this has not been fully achieved. One reason may be that many drivers have little or no knowledge of ABS.     

Jerky driving--An indicator of accident proneness?

This study uses continuously logged driving data from 166 private cars to derive the level of jerks caused by the drivers during everyday driving. The number of critical jerks found in the data is analysed and compared with the self-reported accident involvement of the drivers. The results show that the expected number of accidents for a driver increases with the number of critical jerks caused by the driver. Jerk analyses make it possible to identify safety critical driving behaviour or “accident prone” drivers. They also facilitate the development of safety measures such as active safety systems or advanced driver assistance systems, ADAS, which could be adapted for specific groups of drivers or specific risky driving behaviour.     

Storybuilder—A tool for the analysis of accident reports

As part of an ongoing effort by the ministry of Social Affairs and Employment of The Netherlands a research project is being undertaken to construct a causal model for the most commonly occurring scenarios related to occupational risk. This model should provide quantitative insight in the causes and consequences of occupational accidents. The results should be used to help selecting optimal strategies to reduce these risks taking the costs of accidents and of measures into account. The research is undertaken by an international consortium under the name of Workgroup Occupational Risk Model. One of the components of the model is a tool to systematically classify and analyse past accidents. This tool: “Storybuilder” and its place in the Occupational Risk Model (ORM) are described in the paper.The paper gives some illustrations of the application of the Storybuilder, drawn from the study of ladder accidents, which forms one of the biggest single accident categories in the Dutch data.     

A study of driver experience and vehicle familiarity in accidents

A separate study was performed as part of a major accident investigation project to (1) test the hypothesis that drivers of vehicles involved in investigated accidents had less driving experience than the general driving population, and (2) test the hypothesis that accident involved drivers were less familiar with their vehicles than the general driving population. A Kolmogorov-Smirnov one-tail test was employed to evaluate the differences in the distributions of driver experience and vehicle familiarity between the “accident sample” and a “control sample.” Results indicated that drivers involved in the investigated accidents had less driving experience in general and had less driving experience with the accident vehicles than drivers in the general population. These effects are discussed briefly and further studies are suggested.     

Rough set approach for accident chains exploration

This paper presents a novel non-parametric methodology--rough set theory--for accident occurrence exploration. The rough set theory allows researchers to analyze accidents in multiple dimensions and to model accident occurrence as factor chains. Factor chains are composed of driver characteristics, trip characteristics, driver behavior and environment factors that imply typical accident occurrence. A real-world database (2003 Taiwan single auto-vehicle accidents) is used as an example to demonstrate the proposed approach. The results show that although most accident patterns are unique, some accident patterns are significant and worth noting. Student drivers who are young and less experienced exhibit a relatively high possibility of being involved in off-road accidents on roads with a speed limit between 51 and 79 km/h under normal driving circumstances. Notably, for bump-into-facility accidents, wet surface is a distinctive environmental factor.     

The stability of driving record over time

In summary, then, 6-year driving records (accidents and convictions for traffic violations) were obtained for a representative sample of 7841 California drivers, of both sexes and all ages. From analysis of these driving record data the following conclusions appear warranted: (1) By far the vast majority of accidents involve previously accident-free drivers, that is. the accident-repeater is responsible for only a small portion of the accident problem. Therefore, traffic safety efforts directed toward the so-called “normal” driver will have a better chance of pay-off. (2) Conviction experience is more stable over time than is accident experience, and both are more stable over time for males than for females. Therefore, predicting future driving performance will be more successful for convictions than for accidents, and more successful for males than for females. (3) Driving record information becomes more reliable as the period of time over which it is accumulated increases. Therefore, for prediction of future performance, or generalizing for any other purpose, it is desirable to use as long a period of time as possible as a driving record base.     

ARAMIS project: a comprehensive methodology for the identification of reference accident scenarios in process industries

In the frame of the Accidental Risk Assessment Methodology for Industries (ARAMIS) project, this paper aims at presenting the work carried out in the part of the project devoted to the definition of accident scenarios. This topic is a key-point in risk assessment and serves as basis for the whole risk quantification.

The first result of the work is the building of a methodology for the identification of major accident hazards (MIMAH), which is carried out with the development of generic fault and event trees based on a typology of equipment and substances. The term “major accidents” must be understood as the worst accidents likely to occur on the equipment, assuming that no safety systems are installed.

A second methodology, called methodology for the identification of reference accident scenarios (MIRAS) takes into account the influence of safety systems on both the frequencies and possible consequences of accidents. This methodology leads to identify more realistic accident scenarios. The reference accident scenarios are chosen with the help of a tool called “risk matrix”, crossing the frequency and the consequences of accidents.

This paper presents both methodologies and an application on an ethylene oxide storage.     

What you find is not always what you fix—How other aspects than causes of accidents decide recommendations for remedial actions

In accident investigation, the ideal is often to follow the principle “what-you-find-is-what-you-fix”, an ideal reflecting that the investigation should be a rational process of first identifying causes, and then implement remedial actions to fix them. Previous research has however identified cognitive and political biases leading away from this ideal. Somewhat surprisingly, however, the same factors that often are highlighted in modern accident models are not perceived in a recursive manner to reflect how they influence the process of accident investigation in itself. Those factors are more extensive than the cognitive and political biases that are often highlighted in theory. Our purpose in this study was to reveal constraints affecting accident investigation practices that lead the investigation towards or away from the ideal of “what-you-find-is-what-you-fix”. We conducted a qualitative interview study with 22 accident investigators from different domains in Sweden. We found a wide range of factors that led investigations away from the ideal, most which more resembled factors involved in organizational accidents, rather than reflecting flawed thinking. One particular limitation of investigation was that many investigations stop the analysis at the level of “preventable causes”, the level where remedies that were currently practical to implement could be found. This could potentially limit the usefulness of using investigations to get a view on the “big picture” of causes of accidents as a basis for further remedial actions.     

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.     

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.     

Can it be true that most drivers are safer than the average driver?

Surveys finding that a large majority of drivers regard themselves as safer than the average driver have been ridiculed as showing that most drivers are overconfident about their safety and as showing something which is logically impossible, since in a normal distribution exactly half are below average and half above. This paper shows that this criticism is misplaced. Driver accident involvement does not follow a normal distribution, and it is mathematically entirely possible that a huge majority of drivers could be safer than the average driver. The distribution of accidents in a population of drivers is typically skewed, with a majority of drivers not reporting involvement in any accident in the period covered by the data, often a period of 1–3 years. In this paper, examples are given of data sets in which the percentage of drivers who are safer than the average driver ranges from about 70% to 90%. The paper explains how, based on knowing the mean and variance of the distribution of accidents in a population of drivers in a given period, the long-term expected number of accidents for drivers who were involved in 0, 1, 2, or more accidents can be estimated. Such estimates invariably show that the huge majority of drivers are safer than the average driver.     

Factors contributing to young moped rider accidents in Denmark

Young road users still constitute a high-risk group with regard to road traffic accidents. The crash rate of a moped is four times greater than that of a motorcycle, and the likelihood of being injured in a road traffic accident is 10–20 times higher among moped riders compared to car drivers. Nevertheless, research on the behaviour and accident involvement of young moped riders remains sparse.Based on analysis of 128 accident protocols, the purpose of this study was to increase knowledge about moped accidents. The study was performed in Denmark involving riders aged 16 or 17. A distinction was made between accident factors related to (1) the road and its surroundings, (2) the vehicle, and (3) the reported behaviour and condition of the road user. Thirteen accident factors were identified with the majority concerning the reported behaviour and condition of the road user. The average number of accident factors assigned per accident was 2.7. Riding speed was assigned in 45% of the accidents which made it the most frequently assigned factor on the part of the moped rider followed by attention errors (42%), a tuned up moped (29%) and position on the road (14%). For the other parties involved, attention error (52%) was the most frequently assigned accident factor. The majority (78%) of the accidents involved road rule breaching on the part of the moped rider.The results indicate that preventive measures should aim to eliminate violations and increase anticipatory skills among moped riders and awareness of mopeds among other road users. Due to their young age the effect of such measures could be enhanced by infrastructural measures facilitating safe interaction between mopeds and other road users.     

Annual mileage, driving violations, and accident involvement in relation to drivers' sex, age, and level of education.

The paper presents results of some analyses on a Dutch database that contains disaggregated data on both the traffic system input variables of the driver population (characteristics of drivers, including their annual mileage) and the output variables of the driver population in terms of habitual driving behaviour (operationalised in number of fines) and accident involvement. Accidents increased as annual mileage increased. A relationship between violations and accidents turned out to exist in different classes of annual mileage. Moreover, multivariate analyses showed that--corrected for annual mileage--male and female drivers do not differ in accident involvement; younger drivers have the highest rate of accidents and level of education is not related to accident involvement.     

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.     

Scenario analysis of freight vehicle accident risks in Taiwan

This study develops a quantitative risk model by utilizing Generalized Linear Interactive Model (GLIM) to analyze the major freight vehicle accidents in Taiwan. Eight scenarios are established by interacting three categorical variables of driver ages, vehicle types and road types, each of which contains two levels. The database that consists of 2043 major accidents occurring between 1994 and 1998 in Taiwan is utilized to fit and calibrate the model parameters. The empirical results indicate that accident rates of freight vehicles in Taiwan were high in the scenarios involving trucks and non-freeway systems, while; accident consequences were severe in the scenarios involving mature drivers or non-freeway systems. Empirical evidences also show that there is no significant relationship between accident rates and accident consequences. This is to stress that safety studies that describe risk merely as accident rates rather than the combination of accident rates and consequences by definition might lead to biased risk perceptions. Finally, the study recommends using number of vehicle as an alternative of traffic exposure in commercial vehicle risk analysis. The merits of this would be that it is simple and thus reliable; meanwhile, the resulted risk that is termed as fatalities per vehicle could provide clear and direct policy implications for insurance practices and safety regulations.