Committing driving violations: An observational study comparing city, town and village

Introduction

This article compares observed driving behavior in a city, a town, and a village.

Method

Unobtrusive observations were made at intersections in each residential type. Five violation types were observed: (a) not wearing a seat belt (seat belt violation); (b) not using a safety seat for a child (safety seat violation for children); (c) not using a speaker while speaking on the phone (on-phone violation); (d) failing to comply with a ‘give way’ sign (‘give way’ sign violation); and (e) stopping in an undesignated area (undesignated stop violation). It was expected that in accordance with the anonymity hypothesis that the bigger residential areas' rate of traffic violations would be higher. The effects of the residential type, drivers' gender, and age were assessed using the multiple regression model. The stepwise method of evaluation was employed. The model converged on step 3 (Adjusted R square = 0.039). Residential type and gender contributed significantly to the model. Results: Consistent with prior research, male drivers committed more violations than female drivers. Chi-square analyses were used to test the distribution of violations by the settlement types. Overall, more drivers committed violations in the two small residential areas than in the city, with 30% of city drivers, 43% of town drivers, and 51% of village drivers committing at least one violation (χ2 (2) = 37.65, p < 0.001). Moreover, in the town and the village, a combination of one or more violations was committed more often than in the city (χ2 (1) = 34.645, p < 0.001). Accordingly, more drivers committed violations in the two small settlements (48.4%) than in the city (30.6%). Possible explanations for the observed results were provided in the Discussion section.

Impact on Industry

The conclusions of this paper are that drivers in small villages tend to disobey traffic laws. Therefore, efforts have to be made in companies to take this issue in consideration while running fleets in companies located in small places far from the center.     

Investigating the self-reported behavior of drivers and their attitudes to traffic violations

IntroductionDriving behavior theoretical models consider attitudes as an important determinant of driver behavior. Moreover, the association between the self-reported tendency to commit violations and accident involvement is widely recognized. This research investigates drivers’ self-reported behavior and attitudes to risky behaviors related to the traffic violations of speeding, drink-driving, and cell phone use using cluster analysis.MethodA sample of 601 Greek drivers participating at the SARTRE 4 pan-European survey is utilized. The analysis identified three clusters of drivers. Drivers in Cluster 1 commit traffic violations more often; drivers in Cluster 2 favor traffic violation countermeasures while having moderate views toward compliance with traffic rules; and drivers in Cluster 3 strongly support traffic violation countermeasures and also have strong views toward compliance with traffic rules. Risky behaviors and related attitudes that differentiate the three distinct groups of drivers (clusters) were determined.ResultsThe findings indicate that differences in attitudes and behaviors may be attributed to factors such as age, gender, and area of residence. The research findings also provided some insight about the current level of drivers’ attitudes to traffic violations, especially those that negatively affect traffic safety. The pattern of their views on violations may form the basis of risk behavior-related interventions tailored to the identified groups, aiming at informing, educating, and raising the awareness of the public.Impact on IndustryAgencies focused on safety interventions could exploit this information in designing and implementing education campaigns, enforcement programs and in defining relevant priorities.     

Influence of personality traits on aberrant driving behaviors: A comparison of Japanese,Chinese, and Vietnamese drivers

Introduction: This study aims to explore the influence of Big Five personality traits in combination with various socio-demographic factors and experiences of accident involvement on aberrant driving behaviors. The study also compares the effects of the level of development (i.e., developed or developing) of three countries on the personality traits and driving behaviors. Method: The four-factor Driver Behavior Questionnaire was used to collect data on aberrant driving behaviors, while a short version of the 10-item Big Five Inventory was used to collect data on personality traits. Responses were collected from Japan (1,250 responses), China (1,250), and Vietnam (1,000). A latent variable model was applied after controlling data in each category (e.g., age). Results: This study revealed that respondents who experienced accidents in the past and scored higher on Agreeableness were less likely to commit aggressive violations in Japan, China, and Vietnam. Further, Japanese and Vietnamese female drivers who scored high on Conscientiousness were found to be less likely to commit ordinary violations. Neuroticism was positively correlated with aggressive violations only in the case of Vietnamese drivers, irrespective of the history of accident involvement. Conclusions: Drivers with particular personality types that are linked with aberrant driving behavior may need to receive additional training on behavior management. Practical Applications: This study may help road traffic policymakers predict future driving behaviors of Vietnamese and Chinese drivers based on those of Chinese and Japanese drivers, respectively, and act accordingly.     

Exploring the factors affecting motorway accident severity in England using the generalised ordered logistic regression model

ProblemThe severity of motorway accidents that occurred on the hard shoulder (HS) is higher than for the main carriageway (MC). This paper compares and contrasts the most important factors affecting the severity of HS and MC accidents on motorways in England.MethodUsing police reported accident data, the accidents that occurred on motorways in England are grouped into two categories (i.e., HS and MC) according to the location. A generalized ordered logistic regression model is then applied to identify the factors affecting the severity of HS and MC accidents on motorways. The factors examined include accident and vehicle characteristics, traffic and environment conditions, as well as other behavioral factors.ResultsResults suggest that the factors positively affecting the severity include: number of vehicles involved in the accident, peak-hour traffic time, and low visibility. Differences between HS and MC accidents are identified, with the most important being the involvement of heavy goods vehicles (HGVs) and driver fatigue, which are found to be more crucial in increasing the severity of HS accidents.Practical applicationsMeasures to increase awareness of HGV drivers regarding the risk of fatigue when driving on motorways, and especially the nearside lane, should be taken by the stakeholders.     

Understanding factors associated with misclassification of fatigue-related accidents in police record

IntroductionFatigue is one of the riskiest causes of traffic accidents threatening road safety. Due to lack of proper criteria, the identification of fatigue-related accidents by police officers largely depends on inferential evidence and their own experience. As a result, many fatigue-related accidents are misclassified and the harmfulness of fatigue on road safety is misestimated.MethodIn this paper, a joint model framework is introduced to analyze factors contributing to misclassification of a fatigue-related accident in police reports. Association rule data mining technique is employed to identify the potential interactions of factors, and logistic regression models are applied to analyze factors that hinder police officers' identification of fatigue-related accidents. Using the fatigue-related crash records from Guangdong Province during 2005–2014, factors contributing to the false positive and false negative detection of the fatigue-related accident have been identified and compared.ResultsSome variables and interactions were identified to have significant impacts on fatigue-related accident detection.ConclusionsBased on the results, it can be inferred that the stereotype of certain groups of drivers, crash types, and roadway conditions affects police officers' judgment on fatigue-related accidents.Practical applicationsThis finding can provide useful information for training police officers and build better criteria for fatigue identification.     

Traffic climate and driver behaviors: The moderating role of driving skills in Turkey and China

Introduction: While road traffic accidents and fatalities are a worldwide problem, the rates of road traffic accidents and fatalities show differences among countries. Similarly, driver behaviors, traffic climate, and their relationships also show differences among countries. The aim of the current study is to investigate the moderating effect of driving skills on the relationship between traffic climate and driver behaviors by country. (Turkey and China). Method: There were 294 Turkish drivers and 292 Chinese drivers, and they completed the Traffic Climate Scale, the Driving Skills Inventory, and the Driver Behavior Questionnaire. The moderated moderation analyses were conducted with Hayes PROCESS tool on SPSS. Results: The results showed that safety skills moderated the relationship between internal requirements and violations both in Turkey and China. Safety skills also moderated the relationship between internal requirements and errors only in China and the relationship between functionality and violations in Turkey. Perceptual-motor skills moderated the relationships between external affective demands and errors, and also the relationship between internal requirements and positive driver behaviors in Turkey. It can be inferred that driving skills has different influences on traffic climate-driver behaviors relationship in different cultures and there might be cultural differences in the evaluation of drivers’ own driving skills. Practical Applications: Among driving skills, safety skills have a more critical role to increase road safety by decreasing number of violations. Interventions to increase safety skills of drivers might be promising for road safety.     

Age group differences in collision risk

Introduction

The purpose of the current study was to examine differences in factors associated with self-reported collision involvement of three age groups of drivers based on a large representative sample of Ontario adults. Method: This study was based on data from the CAMH Monitor, an ongoing cross-sectional telephone survey of Ontario adults 18 years and older from 2002 to 2005. Three age groups were examined: 18-34 (n = 1,294), 35-54 (n = 2,428), and 55+ (n = 1,576). For each age group sample, a logistic regression analysis was conducted of self-reported collision involvement in the last 12 months by risk factor measures of driving exposure (kilometers driven in a typical week, driving is stressful, and driving on busy roads), consuming five or more drinks of alcohol on one occasion (past 12 months), cannabis use (lifetime, and past 12 months), and driving after drinking among drinkers (past 12 months), controlling for demographics (gender, region, income, and marital status). Results: The study identified differences in factors associated with self-reported collision involvement of the three age groups of adult drivers. The logistic regression model for the youngest group revealed that drivers who reported that driving was stressful at least some of the time, drank five or more drinks on an occasion, and drove after drinking had an increased risk of collision involvement. For the middle age group, those who reported using cannabis in the last 12 months had significantly increased odds of reporting collision involvement. None of the risk factor measures showed significant associations with collision risk for older drivers (aged 55+). Impact: The results suggest potential areas for intervention and new directions for future research.     

Cultural and socio-demographic predictors of car accident involvement in Norway,Ghana, Tanzania and Uganda

The prevalence of road traffic accidents is increasing towards endemic proportions in developing countries. The present study investigated cultural and demographic predictors of car accident involvement in a developed country in Europe and three developing countries in Sub-Saharan Africa. The comparison was carried out with questionnaires among a randomly obtained representative sample of the Norwegian population (n = 247) as well as stratified samples in Accra and Cape-Coast in Ghana (n = 299), Dar-es-Salaam and Arusha areas in Tanzania (n = 599), and the central Kampala and the Mbarara district in Uganda (n = 415). Measurement instruments of culture as symbol exchange and destiny orientation were used to predict self-reported road traffic accident involvement by car among the respondents. Demographic characteristics, such as gender, age and education, were also included as predictors of car accidents. The results showed that male gender was the only significant predictor of accident involvement in Norway. Introverted and extroverted culture, destiny orientation and written culture were associated with accident involvement in the African countries. Male gender also predicted accidents in these countries. Non-technical injury preventive countermeasures in developing countries could focus on cultural practice and fatalistic beliefs. Countermeasures in both developed and developing countries should target male drivers.     

The effect of organizational justice as perceived by occupational drivers on traffic accidents: Mediating effects of job satisfaction

Introduction: Considerable research supports a positive association between the safety climate (which is a direct organizational factor) and safety performance (such as safe driving). However, indirect organizational variables that influence safe driving have gone largely unexplored. This study contributes to safety research by examining the relationship between organizational justice, which is a distal organizational factor, and traffic accidents and the mediating role of job satisfaction. Method: 233 occupational drivers employed by taxi and bus companies in South Korea participated in the study. Regression analysis was conducted using police records on participants' on-the-job traffic accidents. Results: The analysis shows that the mediation model is statistically significant. That is, drivers with a lower level of perceived organizational justice showed a higher frequency of traffic accidents, and the mediating effect of job satisfaction was also significant. Based on the results, implications and limitations are discussed. Practical applications: The findings demonstrate that in order to decrease traffic accidents, transportation companies would benefit by examining distal factors such as organizational justice. This approach suggests that the conventional framework for safety management should be broadened to include aspects of the entire organization.     

The prevalence of seatbelt and mobile phone use among drivers in Riyadh,Saudi Arabia: An observational study

IntroductionRoad traffic injuries (RTIs) are the third leading cause of death in Saudi Arabia. Numerous factors may increase the likelihood of RTIs. The prevalence of risk factors associated with RTIs may vary due to several reasons. Because little is known about these risk factors locally, we examined the prevalence of mobile phone and seatbelt use and their association with spatial locations.MethodsThis is an observational study conducted at major highways and inner intersections throughout Riyadh, the country's capital. Two observers captured seatbelt and mobile phone use among drivers. Logistic regression models were constructed to examine the association between real estate prices and mobile phone or seatbelt use. Observations were categorized as taken place in an affluent neighborhood if the average price per square meter was above 2500 Saudi Riyal.ResultsA total of 1700 drivers were observed in 13 sites citywide. 13.8% of drivers were seen using mobile while driving and only a third of drivers (34%) were wearing seatbelts. Being at an affluent neighborhood was associated with close to three times higher odds of wearing seatbelts (OR = 2.7, 95% CI = 1.9–3.7) and also associated with 42% lower odds of mobile phone use among drivers (OR = 0.58, 95% CI = 0.36–0.92).DiscussionThis study found a high prevalence of traffic violations among drivers in Riyadh. Based on our estimate, 660,000 drivers are roaming the street during daytime while using their phones and they are less likely to wear seatbelts. Unfortunately, this estimate might contribute to increasing RTIs. Despite existing regulations, seatbelt use among drivers is significantly lower than in developed countries (i.e. USA 94%).ConclusionOur study found a high prevalence of traffic violations represented by lack of compliance with seatbelt and mobile phone use laws. These findings provide a basis for their underlying prevalence in SA. Practical applications: Public health prevention programs may use these findings to facilitate support to increasing investment in awareness campaigns and further enforcement by the traffic police to reduce RITs and improve population health.     

交通事故现场警务取证区块化溯源分析方法*

为突破以现场为中心的取证模式，研究基于交通事故过程导向的交通事故现场警务取证系统化方法，以审判为中心理念重构警务取证的新模式，应用区块链溯源方法的思想与技术，提出警务取证区块化溯源分析方法。结果表明:交通事故现场警务取证，应当以交通事故认定的交通事故构成的“七何”要件为证明标准；警务取证包括交通事故全过程的道路交通系统、交通事故现场、交通事故事实3个区块节点；取证具体涉及交通安全风险控制系统的8个系统要素，现场系统的7个系统要素，以及交通事故元素的2个事实要素。该方法的双向溯源技术可确保警务取证的成效，有效提升取证执法效能。     

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey

Introduction

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey.

Method

Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P < 0.05 with spatial autocorrelation analyses.

Results

Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P < 0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R² values. Geographically weighted regression provided values of 0.89-0.99 adjusted R² for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions.

Impact on industry

Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.     

Risk factors for being the at-fault driver: A case–control study

Objective: It is estimated that road traffic accidents are globally responsible for approximately 1.2 million deaths and 20 to 50 million injuries. About 70% of traffic incidences (TIs) occur in developing countries and among countries with high TI rates; Iran is the first. The aim of this study was to measure the association between being responsible for a traffic accident and some vehicle, human; and environmental related factors in Yasuj, a city with a high incidence of road traffic injuries and deaths in Iran.

Methods: This is a time-, date-, and place-matched case–control study conducted in 2015 using all traffic accidents registered and investigated by police during 2012. In total, 194 drivers were considered the at-fault driver in a traffic accident and the 194 drivers in the same collisions were included in the analysis.

Results: Based on the results from multivariate conditional logistic regression, significant associations between vehicle maneuver (OR_{Turn to right or left/Moving forward} = 11.10, 95% confidence interval [CI], 1.77–69.58, P = .01) and age (odds ratio [OR] = 1.11, 95% CI, 1.004–1.22, P = .04) and the chance of being an at-fault driver were found.

Conclusion: Driver behavior–related interventions including training and law enforcement seem to be more effective in reducing road traffic accidents in Iran.     

Investigation of key factors for accident severity at railroad grade crossings by using a logit model

Although several studies have used logit or probit models and their variants to fit data of accident severity on roadway segments, few have investigated accident severity at a railroad grade crossing (RGC). Compared to accident risk analysis in terms of accident frequency and severity of a highway system, investigation of the factors contributing to traffic accidents at an RGC may be more complicated because of additional highway–railway interactions. Because the proportional odds assumption was violated while fitting cumulative logit modeled by the proportional odds models with stepwise variable selection to ordinal accident severity data collected at 592 RGCs in Taiwan as suggested by Strokes et al. [Strokes, M.E., Davis, C.S., Koch, G.G., 2000. Categorical Data Analysis Using the SAS System, second ed. SAS Institute, Inc., Cary, NC, p. 249], a generalized logit model with stepwise variable selection was used instead to identify explanatory variables (factors or covariates) that were significantly associated with the severity of collisions. Hence, the fitted model was used to predict the level of accident severity, given a set of values in the explanatory variables. Number of daily trains, highway separation, number of daily trucks, obstacle detection device, and approaching crossing markings significantly affected levels of accident severity at an RGC (p-value = 0.0009, 0.0008, 0.0112, 0.0017, and 0.0003, respectively). Finally, marginal effect analysis on the number of daily trains and law enforcement camera was conducted to evaluate the effect of the number of daily trains and presence of a law enforcement camera on the potential accident severity.     

The Driver Behaviour Questionnaire as accident predictor; A methodological re-meta-analysis

IntroductionThe Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include unpublished results.MethodThe present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken.ResultsOutlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, using the mean of accidents as proxy for effect indicated that studies where effects for violations are not reported have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r < .07) for violations versus traffic accident involvement, depending upon which tendencies are controlled for.ConclusionsMethodological factors and dissemination bias have inflated the published effect sizes of the DBQ. Strong evidence of various artefactual effects is apparent.Practical applicationsA greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.     

Powered two-wheeler drivers' risk of hitting a pedestrian in towns

IntroductionThe risk of collision between pedestrians and powered two-wheelers is poorly understood today. The objective of this research is to determine the risk for powered two-wheeler drivers of hitting and injuring a pedestrian per kilometer driven in towns and to compare this risk with that run by four-wheeled vehicle drivers.MethodUsing the bodily injury accidents recorded by the police on nine roads in the city of Marseille in 2011 and a campaign of observations of powered two-wheeler traffic, we estimated the risk per kilometer driven by powered two-wheeler drivers of hitting a pedestrian and compared it with the risk run by four-wheeled vehicle drivers.ResultsThe results show that the risk for powered two-wheeler drivers of hitting and injuring a pedestrian is significantly higher than the risk run by four-wheeled vehicle drivers. On the nine roads studied, it is on average 3.33 times higher (95% CI: 1.63; 6.78). Taking four more years into account made it possible to consolidate these results and to tighten the confidence interval.ConclusionThere does indeed seem to be problems in the interactions between pedestrians and powered two-wheeler users in urban traffic. These interaction problems lead to a higher risk of hitting and injuring a pedestrian for powered two-wheeler drivers than for four-wheeled vehicle drivers. The analysis of the police reports suggests that part of this increased risk comes from filtering maneuvers by powered two-wheelers.Practical applicationsPossible countermeasures deal with the urban street layout. Measures consisting in reducing the width and the number of traffic lanes to a strict minimum and installing medians or pedestrian islands could be an effective way for the prevention of urban accidents between pedestrians and powered two-wheelers.     

Brazilian adaptation of the driving anger expression inventory: testing its psychometrics properties and links between anger behavior,risky behavior,sensation seeking,and hostility in a sample of Brazilian undergraduate students

Introduction: In Brazil, driver aggressiveness in road traffic is a critical issue and could be an important contributing factor to the high number of traffic accidents. Because no instruments are available in Portuguese to register driving aggressiveness or driving anger in Brazil, we adapted English instruments into the Brazilian context. The aims of this study were to provide a Brazilian adaptation of the Driving Anger Expression Inventory (DAX) and to try to validate it by testing its psychometric properties and investigating its relationships with risky driving behaviors (DBQ), road accidents, driving sensation seeking, and hostility. Method: The Brazilian adaptations of the DAX, DBQ, the Driving Sensation Seeking Scale (DSSS) and the hostility Scale were administered to a sample of 512 undergraduate students (with a mean age of 23.7 years, 52.1% men). Results: Confirmatory factor analysis of the Brazilian DAX (DAX-BR) items yielded a four-factor solution with 43 items, which obtained the best goodness-of-fit to the data. Cronbach’s alpha for the DAX-BR factors ranged from 0.69 to 0.88. Other results on validity were a positive correlation (range 0.39–0.59) between the factors of the DAX-BR, DSSS, and DBQ. Conclusion: DAX-BR as the same structure as the original and is a reliable instrument for use with young drivers. Other studies should be conducted to further validate the DAX-BR in different types of populations such as older and more experienced drivers, professional drivers, and traffic regulation offenders whose driver's license has been taken away. Practical applications: This Brazilian version can be recommended for the assessment of driving anger expression in Brazil among young drivers in view of helping them driver more safely, and in particular to reduce traffic violations.     

Differences in urban and rural accident characteristics and medical service utilization for traffic fatalities in less-motorized societies

Introduction

Fatalities from traffic accidents in less-motorized societies are an important global issue. We aimed to characterize the geographic differences of fatalities in such societies to facilitate the development of targeted interventions.

Method

This study linked police reports, hospital data, and vital registration data from Taiwan with special reference to accident factors in pre-hospital deaths and medical care in hospital deaths.

Results

A higher percentage of pre-hospital deaths were observed following rural as compared to urban traffic accidents. The deaths due to rural accidents can be attributed to lower use of restraints (i.e., helmets or seat belts), lower percentage of motorcyclists, and more highway accidents. A higher percentage of victims in rural accidents were transported to distant medical centers rather than to local hospitals.

Conclusion

Specific interventions, such as intelligent emergency medical systems, campaigns for helmets and seat belt usage, enforcement of helmets and seat belt use, and speed control measures should be targeted to rural areas.

Impact on industry

Cooperation between the vehicle industry and emergency medical providers in rural traffic accident rescue teams may decrease the numbers of deaths in these regions.     

Driving anger and its expressions: further evidence of validity and reliability for the Driving Anger Expression Inventory French adaptation

Introduction: The aims of this study were to provide further evidence of validity and reliability for the Driving Anger Expression Inventory (DAX) French adaptation (Villieux & Delhomme, 2008, Le Travail Humain, 71(4), 359-384) and to investigate the relationships between driving anger, how people express their anger while driving, and traffic violations among young drivers in France. Method: The French adaptations of the DAX, of the Driving Anger Scale (DAS), and of the Extended Violations Scale were administered to a sample of 314 drivers. Results: Confirmatory factor analysis of the French DAX items yielded a three factors solution with 11 items, which obtained better goodness-of-fit to the data. Cronbach α reliabilities for DAX factors ranged from .71 to .79. Aggressive forms of anger expression correlated positively with driving anger and traffic violations whereas the 'Adaptive/Constructive Expression' factor correlated negatively with these variables. Discussion: Globally, our results replicated earlier findings and showed that DAX factors are useful predictors of self reported violations and complement established measures like the DAS. Impact on Industry: Implications for driver education and interventions were examined.     

Are drivers' comparative risk judgments about speeding realistic?

Introduction

This study focused on comparative judgments about speeding risks among young drivers who have a high risk of being involved in a traffic accident.

Method

We examined (a) how these drivers assess their risk of sanctions and their risk of causing an automobile crash because of speeding in comparison to the estimated risks of other drivers, and (b) how realistic their comparative risk judgments are. We measured the relationship between the drivers' comparative risk judgments, self-reported speeding, and driving-related sensation-seeking. We hypothesized that (a) they would think they have less risk of sanctions and of causing a car accident than others, and (b) their comparative judgments of speeding risks would be linked to self-reported speeding and driving-related sensation-seeking. The study was based on a computerized questionnaire survey conducted with 3,002 young drivers (mean age = 22.3) administered by professional investigators.

Results

The results confirmed our hypotheses.

Impact on Industry

In order to improve the effectiveness of prevention measures and to evaluate the effect of them, road-safety interventions should take into account comparative risk judgments about the targeted risk behavior.