An empirical relation between fatal accident involvement per accident involvement and speed

Data on the frequency of fatal and of injury accident involvement per accident involvement, by speed, for several states are compared. It is found that the frequency of fatal accident involvement per accident involvement increases with speed in the same manner, for speeds above 40 mph, in all states considered.     

Cycling to work in Brazil: Users profile, risk behaviors, and traffic accident occurrence

In 2006, we carried out a cross-sectional study in the urban area of Pelotas, Southern Brazil, with the aim of outlining the profile of bicycle commuters, analyzing their use of safety equipment and risk behaviors and the association between these variables and involvement in traffic accidents in the previous 12 months. This study was based on the baseline survey carried out prior to an educational intervention aimed at reducing accidents among cyclists. The sample included 1133 male subjects aged 20 years or more, and who used a bicycle for commuting. Crude and adjusted analyses were carried out using Poisson regression. We recorded a total of 152 reported traffic accidents in the 12 months preceding the interview, involving 10.8% of subjects. Most risk behaviors studied and the use of safety equipment showed no significant association with accidents. Only commuting by bicycle seven days per week, as opposed to five or six, and a combination of extremely imprudent behaviors such as zigzagging through traffic, riding after ingesting alcohol, and high-speed riding were found to be risk factors for accidents. Our findings suggest that in the context where the study was done (poor road signaling, limited policing, aggressive driving) changing cyclist behavior may not have substantial impact in terms of accident reduction before other road traffic interventions are implemented.     

Applying the random effect negative binomial model to examine traffic accident occurrence at signalized intersections

Poisson and negative binomial (NB) models have been used to analyze traffic accident occurrence at intersections for several years. There are however, limitations in the use of such models. The Poisson model requires the variance-to-mean ratio of the accident data to be about 1. Both the Poisson and the NB models require the accident data to be uncorrelated in time. Due to unobserved heterogeneity and serial correlation in the accident data, both models seem to be inappropriate. A more suitable alternative is the random effect negative binomial (RENB) model, which by treating the data in a time-series cross-section panel, will be able to deal with the spatial and temporal effects in the data. This paper describes the use of RENB model to identify the elements that affect intersection safety. To establish the suitability of the model, several goodness-of-fit statistics are used. The model is then applied to investigate the relationship between accident occurrence and the geometric, traffic and control characteristics of signalized intersections in Singapore. The results showed that 11 variables significantly affected the safety at the intersections. The total approach volumes, the numbers of phases per cycle, the uncontrolled left-turn lane and the presence of a surveillance camera are among the variables that are the highly significant.     

An assessment of the effect of driver age on traffic accident involvement using log-linear models

Statistical models were developed to help understand the relationship between the driver age and several important accident-related factors and circumstances such as injury severity, collision types, average daily traffic (ADT), roadway character, speed ratio, alcohol involvement, and accident location. By using techniques of categorical analysis on the 1994 and 1995 Florida accident database, four log-linear models with three variables in each model with all possible two-way interactions were developed. In order to compare the differences in response between the age groups and a particular accident-related variable, odds multipliers were computed. The effects of age and accident-related factors were examined, and interactions among them were considered. The results indicated significant relationships between the driver age and ADT, injury severity, manner of collision, speed, alcohol involvement, and roadway character. The findings' contribution to the understanding of the effect of age on accident involvement is addressed. A discussion of how log-linear and logit modeling with estimation of `odds multipliers' may contribute to traffic safety studies is also provided.     

Farm safety attitudes and accident involvement

Many safety educators firmly believe that good safety attitudes are a must if people are to avoid accidents in the workplace and elsewhere. This idea has evolved mainly from the industrial safety movement and has been adopted in most fields of safety. However, this fundamental adage has never been tested in agriculture. A random sample of Pennsylvania farmers were asked their attitudes toward nationally recognized farm safety concepts. The Semantic Differential Attitude Test was the instrument used to collect the data. Four hundred and ninety-three respondents indicated they have about the same attitudes toward farm safety concepts regardless of their accident involvement and regardless of other variables studied. The results of this study suggest that the apparent high priority given to safety attitude development as a primary means of accident prevention should be re-examined.     

Analyzing heterogeneous accident data from the perspective of accident occurrence

Clustering and classification approaches have been commonly applied in reducing the heterogeneity in accident data. As part of an effort to understand the features of the heterogeneity, this study assessed accident data from the perspective of accident occurrences. Using the rule-based classification method, rough set theory, rules were derived which consisted of indispensable factors to certain accident outcomes and reflected the process of accident occurrences. The occurring frequency of each derived rule was then adopted as the basis for grouping accidents for further analyses. Empirical results showed that rules with high occurring frequencies were largely related to drivers with high-risk characteristics. On the other hand, road facilities played a key role in rules with low-occurring frequencies. The distinctive features indicated the essential differences between the frequently repeated and the sparsely unique processes of accident occurrences. This suggests that the heterogeneity of accident data is not limited to one single factor, such as age, gender or area. Thus, the proposed approach, which takes the process of accident occurrences into consideration, can be a potential alternative to more comprehensively analyze the heterogeneity in accident data.     

The optimism bias and traffic accident risk perception

Research suggests that people are excessively and unrealistically optimistic when judging their driving competency and accident risk. In this study, college-age drivers compared their risk of being involved in a variety of described traffic accidents relative to their peers. They also rated each of the accidents along a number of dimensions hypothesized as being related to optimism. In addition, subjects provided global estimates of their driving safety, skill, and accident likelihood. Significant optimism was evident for both the accidents and the global ratings. Optimism increased with driving experience and marginally with age. Those with more driving experience considered human factors to be more important in accident causation; those assigning more importance to human factors also rated themselves as more skillful drivers. For the specific accidents, perceived controllability was a strong predictor of optimism. The findings for controllability are interpreted in terms of other recent data and hypothesized explanations of the optimism bias. In general, it appears that optimism arises because people persistently overestimate the degree of control that they have over events.     

Risk,especially risk of traffic accident

This paper discusses various definitions of risk, risk compensation, subjective risk, and compares risk with exposure and accident proneness.     

Formulating accident occurrence as a survival process

A conceptual framework for accident occurrence is developed based on the principle of the driver as an information processor. The framework underlies the development of a modeling approach that is consistent with the definition of exposure to risk as a repeated trial. Survival theory is proposed as a statistical technique that is consistent with the conceptual structure and allows the exploration of a wide range of factors that contribute to highway operating risk. This survival model of accident occurrence is developed at a disaggregate level, allowing safety researchers to broaden the scope of studies which may be limited by the use of traditional aggregate approaches. An application of the approach to motor carrier safety is discussed as are potential applications to a variety of transportation industries. Lastly, a typology of highway safety research methodologies is developed to compare the properties of four safety methodologies: laboratory experiments, on-the-road studies, multidisciplinary accident investigations, and correlational studies. The survival theory formulation has a mathematical structure that is compatible with each safety methodology, so it may facilitate the integration of findings across methodologies.     

Drug use and the severity of a traffic accident

Several studies have showed that driving under the influence of alcohol and/or certain illicit or medicinal drugs increases the risk of a (severe) crash. Data with respect to the question whether this also leads to a more severe accident are sparse. This study examines the relationship between the use of alcohol, illicit drugs and/or medicinal drugs and the severity of an accident within a group of drivers that were involved in a crash in The Netherlands. Blood samples of 993 drivers, collected in the period from October 1998 through September 1999, were linked to accident characteristics as available from the National Transport Research Centre. The outcome measure was the severity of the accident. An accident was considered severe when the accident had resulted in hospital admission or death. All the blood samples obtained after the accident were screened for the presence of alcohol, illicit drugs (opiates, amphetamines and amphetamine-like substances, cocaine and metabolites, methadone, cannabinoids) and medicinal drugs (benzodiazepines, barbiturates and tricyclic antidepressants). The strength of the associations between exposure to the different classes of alcohol/drugs/medicines and the severity of the accident was evaluated using logistic regression analysis and were expressed as odds ratios (OR), adjusted for age, gender, time of the day, day of the week and urban area. The most frequently detected drugs were cannabinoids, benzodiazepines and cocaine. Our results showed no clear association between the use of alcohol, illicit drug and/or medicinal drug use and the severity of the accident. Given the process of obtaining blood samples from drivers involved in accidents and the retrospective nature of the study, we cannot rule out the occurrence of selection bias. Therefore, our findings need further confirmation.     

Road accident involvement per miles travelled—III

This paper continues a series [Foldvary 1975, 1976] reporting on methods and results of the Queensland Vehicle-Mile Performance Survey. The variables treated in this part are: type of accident, type of vehicle, age of vehicle and design characteristics of vehicle.     

Road accident involvement per miles travelled—I

This paper is the first in a series reporting on a comprehensive survey carried out in the Australian state of Queensland during 1963–1964. About ten percent of 480,000 registered vehicle owners were sent a questionnaire, with about 87% response. The results were compared with police records on all significant acidents during the year 1961. Part I deals with methodology and vehicle use variables. Subsequent parts will discuss type of accident and type of vehicle variables, age of driver and sex of driver. It is suggested in this Part that private cars may have significantly higher exposure-corrected involvement rates than commercial vehicles.     

Road accident involvement per miles travelled—II

This paper continues a series [Foldvary. 19.75] reporting on the 1963–1964 Queensland Vehicle-Mile Performance Survey. The variables treated in this part are: occupancy, area of vehicle use, hour and day of accident.     

Road accident involvement per miles travelled—V

This paper concludes a series reporting on the methods and results of the Queensland Vehicle-Mile Performance Survey. The earlier parts of the series appeared in Accident Analysis and Prevention7, 191–205; 8, 97–127; 9, 21–54; 10, 143–176. The variable treated in this part is sex of driver. The entire series will be published in book form by Pergamon Press.     

Road accident involvement per miles travelled—IV

This paper continues a series (Foldvary 1975, 1976, 1977) reporting on the 1963–1964 Queensland Vehicle-Mile Performance Survey. The variable treated in this part is age of driver.     

Some methodological deficiencies in studies on traffic accident predictors

The paper discusses some methodological problems in (psychological) research on traffic accident predictors and reviews a convenience sample of the literature. Three methodological aspects are identified as being important: reliability of accident predictors, time period for accidents used as dependent variable, and culpability for accidents. Papers are scrutinized and most are found to be wanting in these aspects. Traffic researchers do not adhere to, or hardly even discuss, these basic methodological problems. It is concluded that the current research into (psychological) accident predictors is fraught with methodological deficiencies. Why most studies seem to be deficient in these aspects is not clear, as several researchers have pointed out these problems.     

Quality function deployment applied to local traffic accident reduction

One of the major tasks of police stations is the management of local road traffic accidents. Proper prevention policy which reflects the local accident characteristics could immensely help individual police stations in decreasing various severity levels of road traffic accidents. In order to relate accident variation to local driving environmental characteristics, we use both cluster analysis and Poisson regression. The fitted result at the level of each cluster for each type of accident severity is utilized as an input to quality function deployment. Quality function deployment (QFD) has been applied to customer satisfaction in various industrial quality improvement settings, where several types of customer requirements are related to various control factors. We show how QFD enables one to set priorities on various road accident control policies to which each police station has to pay particular attention.     

Bayesian networks for maritime traffic accident prevention: Benefits and challenges

Bayesian networks are quantitative modeling tools whose applications to the maritime traffic safety context are becoming more popular. This paper discusses the utilization of Bayesian networks in maritime safety modeling. Based on literature and the author's own experiences, the paper studies what Bayesian networks can offer to maritime accident prevention and safety modeling and discusses a few challenges in their application to this context. It is argued that the capability of representing rather complex, not necessarily causal but uncertain relationships makes Bayesian networks an attractive modeling tool for the maritime safety and accidents. Furthermore, as the maritime accident and safety data is still rather scarce and has some quality problems, the possibility to combine data with expert knowledge and the easy way of updating the model after acquiring more evidence further enhance their feasibility. However, eliciting the probabilities from the maritime experts might be challenging and the model validation can be tricky. It is concluded that with the utilization of several data sources, Bayesian updating, dynamic modeling, and hidden nodes for latent variables, Bayesian networks are rather well-suited tools for the maritime safety management and decision-making.     

Risk factors associated with traffic violations and accident severity in China

With the recent economic boom in China, vehicle volume and the number of traffic accident fatalities have become the highest in the world. Meanwhile, traffic accidents have become the leading cause of death in China. Systematically analyzing road safety data from different perspectives and applying empirical methods/implementing proper measures to reduce the fatality rate will be an urgent and challenging task for China in the coming years. In this study, we analyze the traffic accident data for the period 2006–2010 in Guangdong Province, China. These data, extracted from the Traffic Management Sector-Specific Incident Case Data Report, are the only officially available and reliable source of traffic accident data (with a sample size >7000 per year). In particular, we focus on two outcome measures: traffic violations and accident severity. Human, vehicle, road and environmental risk factors are considered. First, the results establish the role of traffic violations as one of the major risks threatening road safety. An immediate implication is: if the traffic violation rate could be reduced or controlled successfully, then the rate of serious injuries and fatalities would be reduced accordingly. Second, specific risk factors associated with traffic violations and accident severity are determined. Accordingly, to reduce traffic accident incidence and fatality rates, measures such as traffic regulations and legislation—targeting different vehicle types/driver groups with respect to the various human, vehicle and environment risk factors—are needed. Such measures could include road safety programs for targeted driver groups, focused enforcement of traffic regulations and road/transport facility improvements. Data analysis results arising from this study will shed lights on the development of similar (adjusted) measures to reduce traffic violations and/or accident fatalities and injuries, and to promote road safety in other regions.