Perception, attitudes and beliefs, and openness to change: implications for older driver education

With a rapidly aging population, strategies for improving driver safety are beginning to emerge that focus on changing driving behaviors and knowledge. We examined the perceptions of risk, beliefs and attitudes, and openness to change of 86 older participants voluntarily attending a driver education program. It appeared that most people attending these sessions were not necessarily concerned about their own driving, safety or abilities, but were interested in maintaining mobility. They were conservative and reasonably consistent in their attitudes toward traffic regulations and safe driving practices. Some gender differences emerged with more men than women being resistant to changing their driving habits, more men than women reporting that they drive after consuming alcohol and more women than men identifying a role for their families in decision-making regarding driving cessation. This suggests that educational material may need to be targeted differently for men and women. It is anticipated that psychosocial factors related to driving such as driver perception, beliefs and openness to change will be useful for maximizing the fit between education program content and outcomes.     

Overly cautious and dangerous: An empirical evidence of the older driver stereotypes

Negative comments regarding the competency of older drivers are frequently heard in the general population. While negative stereotypes of older drivers seem to be present, their existence has yet to be empirically validated. We thus investigated the stereotypes pertaining to older drivers in two experiments. In both experiments young adults viewed 12 simulated clips of three categories of driving behaviors (i.e., younger adults’ unsafe behaviors, older drivers’ unsafe behaviors and appropriate-safe driving behaviors) without knowing the driver's age. They were asked to rate how representative the behaviors were of a typical younger, middle-aged, or older driver. Experiment 1 showed that older drivers’ unsafe behaviors were rated as significantly more representative of the typical older driver, while young adults’ unsafe behaviors were perceived as significantly more representative of the typical younger driver. In Experiment 2, younger participants viewed the same clips but were only asked to indicate whether the observed behavior was representative or not of the typical older driver. The main findings were replicated. When asked to describe the main features of the typical older drivers, participants qualified them as being overly cautious, uncomfortable behind the wheel, and unsafe and dangerous. The potential implications on driving performance of older drivers and on driving cessation and are discussed.     

Young novice driver subtypes: Relationship to driving violations, errors and lapses

The present study aimed to identify, in a large Italian sample of young, novice drivers, specific subtypes of drivers on the basis of combinations of self-reported personality traits (i.e., driving anger, anxiety, angry hostility, excitement-seeking, altruism, normlessness and driving locus of control) and to evaluate their high-risk driving behaviors not only in terms of traffic rule violations and risk-taking behaviors, but also in terms of driving errors and lapses as measured by the Manchester Driver Behavior Questionnaire. Participants were 1008 high school students between the ages of 18 and 23 years, with valid driver's licenses. On the basis of a cluster analysis of the personality variables, three easily interpretable driver subgroups were identified (risky drivers, worried drivers and careful drivers) that differed on self-reported accident involvement, attitudes toward traffic safety and risk perception, as well as on driving violations, errors, and lapses. The inclusion of internal and external driving locus of control, variables not previously considered in similar cluster studies, provided a relevant contribution to the final cluster solution. Further, the use of the Driving Behavior Questionnaire permitted the differentiation between deliberate deviations from safe driving practices and mistakes due to misjudgments or lapses in attention. This distinction was critical for understanding the behavior of each of the three identified subgroups of drivers, and for planning interventions to promote safe driving.     

Prevalence of teen driver errors leading to serious motor vehicle crashes

Objectives

Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors.

Methods

The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15–18 year old drivers.

Results

822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors.

Conclusions

Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training.     

Car driver attitudes,perceptions of social norms and aggressive driving behaviour towards cyclists

The interaction of car drivers and cyclists is one of the main causes of cycle incidents. The role of attitudes and social norms in shaping car drivers’ aggressive behaviour towards cyclists, is not well understood and merits investigation. A sample of 276 drivers completed an online questionnaire concerning their attitudes towards cyclists, attitudes towards risky driving, perception of social norms concerning aggressive driving towards cyclists, and the frequency with which they engage in such aggressive driving behaviours. The results showed that attitudes towards cyclists, as well as social norm perceptions concerning aggressive driving towards cyclists, were associated with aggressive driving towards cyclists. Negative attitudes towards cyclists were more pronounced in non-cyclists than cyclists and their association with aggressive driving behaviour was stronger in cyclists than non-cyclists. The perception of social norms concerning aggressive driving towards cyclists had a stronger association with aggressive driving in non-cyclists than cyclists. Attitudes towards risk taking did not affect aggressive driving towards cyclists. These findings can inform campaigns that aim to improve cyclist and car driver interaction on the roads, making them safer to use for cyclists.     

Teen driver crash risk and associations with smoking and drowsy driving

Motor vehicle crashes are the leading cause of death for young people in the United States. The goal of this study was to identify risk factor profiles of teen and young adult drivers involved in crashes. General demographic and behavioral as well as driving-related factors were considered. Analysis of a nationally representative telephone survey of U.S. young drivers ages 14 to 22 (N = 900) conducted in 2005 was restricted to 506 licensed drivers (learners excluded). Statistically significant univariate associations between factors of interest and the primary outcome, crash involvement (ever) as a driver, were identified and included within a multivariate logistic regression model, controlling for potential demographic confounders. Aside from length of licensure, only driving alone while drowsy and being a current smoker were associated with having been in a crash. Gaining a better understanding of these behaviors could enhance the development of more customized interventions for new drivers.     

A multinomial choice model approach for dynamic driver vision transitions

Exploring the continual process of drivers allocating their attention under varying conditions could be vital for preventing motor vehicle crashes. This study aims to model visual behaviors and to estimate the effects of various contributing factors on driver’s vision transitions. A visual attention allocation framework, based on certain contributing attributes related to driving tasks and environmental conditions, has been developed. The associated logit type models for determining driver choices for focal points were successfully formulated and estimated by using naturalistic glance data from the 100-car event database. The results offer insights into driver visual behavior and patterns of visual attention allocation. The three focal points that drivers most frequently rely on and glance at are the forward, left and rear view mirror. The sample drivers were less likely to demonstrate troublesome transition patterns, particularly in mentally demanding situations. Additionally, instead of shifting vision directly between two non-forward focal points, the sample drivers frequently had an intermediate forward glance. Thus, seemingly unrelated paths could be grouped into explanatory patterns of driver attention allocation. Finally, in addition to the vision-transition patterns, the potential pitfalls of such patterns and possible countermeasures to improving safety are illustrated, focusing on situations when drivers are distracted, traveling at high speeds and approaching intersections.     

Identification of differences between rural and urban safety cultures

The prevailing risk of traffic fatalities is much larger in rural areas compared to urban areas. A number of explanations have been offered to explain this including road design, emergency medical service proximity, and human factors. This research explored the potential contribution of rural driver attitudes that may underlie the increased fatal crash risk in rural environments. This analysis examined differences between rural and urban drivers in terms of self-reported risk taking for driving behaviors associated with fatal crashes and attitudes toward safety interventions using a large-scale survey. The results suggested that rural drivers engage in riskier behavior, such as not wearing seatbelts, because they have lower perceptions of the risks associated with such behaviors. Results also suggested that vehicle type (e.g., pickup trucks versus passenger vehicles) may be related to seatbelt compliance and frequency of driving under the influence of alcohol. Rural drivers perceived the utility of government-sponsored traffic safety interventions to be lower than their urban counterparts. This study provides insights into the role of the human factor in rural fatal crashes and provides policy suggestions for developing safety interventions that are designed with respect to the psychosocial factors that define the rural culture.     

Heterogeneous impacts of gender-interpreted contributing factors on driver injury severities in single-vehicle rollover crashes

In this study, a mixed logit model is developed to identify the heterogeneous impacts of gender-interpreted contributing factors on driver injury severities in single-vehicle rollover crashes. The random parameter of the variables in the mixed logit model, the heterogeneous mean, is elaborated by driver gender-based linear regression models. The model is estimated using crash data in New Mexico from 2010 to 2012. The percentage changes of factors’ predicted probabilities are calculated in order to better understand the model specifications. Female drivers are found more likely to experience severe or fatal injuries in rollover crashes than male drivers. However, the probability of male drivers being severely injured is higher than female drivers when the road surface is unpaved. Two other factors with fixed parameters are also found to significantly increase driver injury severities, including Wet and Alcohol Influenced. This study provides a better understanding of contributing factors influencing driver injury severities in rollover crashes as well as their heterogeneous impacts in terms of driver gender. Those results are also helpful to develop appropriate countermeasures and policies to reduce driver injury severities in single-vehicle rollover crashes.     

Statistical implications of using moving violations to determine crash responsibility in young driver crashes

Traditional methods for determining crash responsibility – most commonly moving violation citations – may not accurately characterize at-fault status among crash-involved drivers given that: (1) issuance may vary by factors that are independent of fault (e.g., driver age, gender), and (2) these methods do not capture driver behaviors that are not illegal but still indicative of fault. We examined the statistical implications of using moving violations to determine crash responsibility in young driver crashes by comparing it with a method based on crash-contributing driver actions. We selected all drivers in police-reported passenger-vehicle crashes (2010–2011) that involved a New Jersey driver <21 years old (79,485 drivers < age 21, 61,355 drivers ≥ age 21). For each driver, crash responsibility was determined from the crash report using two alternative methods: (1) issuance of a moving violation citation; and (2) presence of a driver action (e.g., failure to yield, inattention). Overall, 18% of crash-involved drivers were issued a moving violation while 50% had a driver action. Only 32.2% of drivers with a driver action were cited for a moving violation. Further, the likelihood of being cited given the presence of a driver action was higher among certain driver subgroups—younger drivers, male drivers, and drivers in single-vehicle and more severe crashes. Specifically among young drivers, those driving at night, carrying peer passengers, and having a suspended or no license were more often cited. Conversely, fatally-injured drivers were almost never cited. We also demonstrated that using citation data may lead to statistical bias in the characterization of at-fault drivers and of quasi-induced exposure measures. Studies seeking to accurately determine crash responsibility should thoughtfully consider the potential sources of bias that may result from using legal culpability methods. For many studies, determining driver responsibility via the identification of driver actions may yield more accurate characterizations of at-fault drivers.     

Crash risk of older drivers after attending a mature driver education program

PURPOSE: The primary aim of this study was to determine if the crash rate of aging drivers can be mitigated by post-license driver education. DESIGN AND METHODS: This study of 884 older drivers who attended the 55 Alive/Mature Driving program was conducted in three phases. Phase 1, which examined self-selection bias of seniors attending the driver education program, and Phase 2, which examined changes in crash rate after attending the program, were carried out through analysis of driving records before and after attending the course. In Phase 3, the use of selection, optimization, and compensation strategies by older male drivers who attended 55 Alive/Mature Driving was addressed through focus group interviews. RESULTS: Findings showed a self-selection bias among older drivers who attended 55 Alive/Mature Driving. Results also showed attendance at the program was associated with an increased number of crashes for men aged 75 years and older, but no effect on subsequent crashes of younger men and women of all ages. Focus group sessions suggested older men who attended the program used fewer strategies to cope with their declining skills. IMPLICATIONS: Recognizing and understanding characteristics and behaviors of older drivers who attend remedial driver education is essential to the design and delivery of successful driver safety programs.     

Factors associated with hit-and-run pedestrian fatalities and driver identification

As hit-and-run crashes account for a significant proportion of pedestrian fatalities, a better understanding of these crash types will assist efforts to reduce these fatalities. Of the more than 48,000 pedestrian deaths that were recorded in the United States between 1998 and 2007, 18.1% of them were caused by hit-and-run drivers. Using national data on single pedestrian-motor vehicle fatal crashes (1998–2007), logistic regression analyses were conducted to identify factors related to hit-and-run and to identify factors related to the identification of the hit-and-run driver. Results indicate an increased risk of hit-and-run in the early morning, poor light conditions, and on the weekend. There may also be an association between the type of victim and the likelihood of the driver leaving and being identified. Results also indicate that certain driver characteristics, behavior, and driving history are associated with hit-and-run. Alcohol use and invalid license were among the leading driver factor associated with an increased risk of hit-and-run. Prevention efforts that address such issues could substantially reduce pedestrian fatalities as a result of hit-and-run. However, more information about this driver population may be necessary.     

Older driver population and crash involvement trends, 1974-1988.

North Carolina motor vehicle crash data for even-numbered years 1974-1988, inclusive, are analyzed in conjunction with North Carolina population, licensed driver, and mileage data to examine trends in motor vehicle crash involvement by driver age, sex, and race. Crash rates per licensed driver are presented along with crash rates per estimated vehicle miles travelled calculated on the basis of induced exposure. Results focus particularly on older drivers. They show that older drivers' representation in the licensed driver population has increased at a greater rate than their representation in either the census or crash involvement populations. These trends are particularly strong for females and for nonwhites. Furthermore, crash rates have declined more for drivers aged 55 and older than for younger drivers. The greatest declines, both in terms of crashes per licensed driver and crashes per estimated miles travelled, have been experienced by drivers age 65 and older, particularly nonwhites. Males show higher overall crash rates per miles travelled than females, but this effect decreases with age and disappears entirely in the oldest age categories. Results are discussed in light of the changing nature of the overall driving population and the cohort of older drivers in particular.     

Analyzing fault and severity in pedestrian–motor vehicle accidents in China

The number of pedestrian–motor vehicle accidents and pedestrian deaths in China surged in recent years. However, a large scale empirical research on pedestrian traffic crashes in China is lacking. In this study, we identify significant risk factors associated with fault and severity in pedestrian–motor vehicle accidents. Risk factors in several different dimensions, including pedestrian, driver, vehicle, road and environmental factors, are considered. We analyze 6967 pedestrian traffic accident reports for the period 2006–2010 in Guangdong Province, China. These data, obtained from the Guangdong Provincial Security Department, are extracted from the Traffic Management Sector-Specific Incident Case Data Report. Pedestrian traffic crashes have a unique inevitability and particular high risk, due to pedestrians’ fragility, slow movement and lack of lighting equipment. The empirical analysis of the present study has the following policy implications. First, traffic crashes in which pedestrians are at fault are more likely to cause serious injuries or death, suggesting that relevant agencies should pay attention to measures that prevent pedestrians from violating traffic rules. Second, both the attention to elderly pedestrians, male and experienced drivers, the penalty to drunk driving, speeding, driving without a driver's license and other violation behaviors should be strengthened. Third, vehicle safety inspections and safety training sessions for truck drivers should be reinforced. Fourth, improving the road conditions and road lighting at night are important measures in reducing the probability of accident casualties. Fifth, specific road safety campaigns in rural areas, and education programs especially for young children and teens should be developed and promoted. Moreover, we reveal a country-specific factor, hukou, which has significant effect on the severity in pedestrian accidents due to the discrepancy in the level of social insurance/security, suggesting that equal social security level among urban and rural people should be set up. In addition, establishing a comprehensive liability distribution system for non-urban areas and roadways will be conducive to both pedestrians’ and drivers’ voluntary compliance with traffic rules.     

Traffic accidents involving fatigue driving and their extent of casualties

The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity.     

A model of Beijing drivers' scrambling behaviors

A major, but unstudied, cause of crashes in China is drivers that “scramble” to gain the right of way in violation of traffic regulations. The motivation of this study is to explore the features of drivers’ scrambling behaviors and the attitudes and driving skills that influence them. In this study, we established a scrambling behavior scale, and developed a driving attitude scale and a driving skill scale using factor analysis of an Internet survey of 486 drivers in Beijing. A structural equation model of scrambling behavior toward cars and pedestrians/cyclists was developed with attitudes and skills as predictors of behavior. Skills and attitudes of approval toward violations of traffic rules did not predict scrambling behaviors, while the motivation for safety and attitudes against violating traffic rules led to reduced scrambling behaviors. The current work highlights this peculiar aspect of Chinese roads and suggests methods to reduce the behavior.     

Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways

This study analyzes driver injury severities for single-vehicle crashes occurring in rural and urban areas using data collected in New Mexico from 2010 to 2011. Nested logit models and mixed logit models are developed in order to account for the correlation between severity categories (No injury, Possible injury, Visible injury, Incapacitating injury and fatality) and individual heterogeneity among drivers. Various factors, such as crash and environment characteristics, geometric features, and driver behavior are examined in this study. Nested logit model and mixed logit model reveal similar results in terms of identifying contributing factors for driver injury severities. In the analysis of urban crashes, only the nested logit model is presented since no random parameter is found in the mixed logit model. The results indicate that significant differences exist between factors contributing to driver injury severity in single-vehicle crashes in rural and urban areas. There are 5 variables found only significant in the rural model and six significant variables identified only in the urban crash model. These findings can help transportation agencies develop effective policies or appropriate strategies to reduce injury severity resulting from single-vehicle crashes.     

Driver behaviour profiles for road safety analysis

Driver behaviour is a contributing factor in over 90 percent of road crashes. As a consequence, there is significant benefit in identifying drivers who engage in unsafe driving practices. Driver behaviour profiles (DBPs) are introduced here as an approach for evaluating driver behaviour as a function of the risk of a casualty crash. They employ data collected using global positioning system (GPS) devices, supplemented with spatiotemporal information. These profiles are comprised of common risk scores that can be used to compare drivers between each other and across time and space. The paper details the development of these DBPs and demonstrates their use as an input into modelling the factors that influence driver behaviour. The results show that even having controlled for the influence of the road environment, these factors remain the strongest predictors of driver behaviour suggesting different spatiotemporal environments elicit a variety of psychological responses in drivers. The approach and outcomes will be of interest to insurance companies in enhancing the risk-profiling of drivers with on-road driving and government through assessing the impacts of behaviour-change interventions.     

Fatal accident involvement rates by driver age for large trucks

Survey data on large trucks involved in fatal accidents and on the travel of large trucks provide estimates of fatal accident involvement rates by driver age. The analysis is focused on the implications of lowering the minimum age for drivers of commercial trucks operating interstate from 21 to 19 years. Fatal accident involvement rates for drivers of large trucks are found to increase with decreasing driver age. The younger drivers are over-involved until about age 27. Drivers under the age of 21 are over-involved by a factor of 6 in comparison to the overall rate for all drivers. Other factors known to have significant influences on the probability of involvement in a fatal accident were examined to determine their association with the over-involvement of younger drivers. The general pattern of over-involvement for younger drivers pervades virtually every combination of factors examined. Thus, it is concluded that the basic trend with driver age shown in the aggregate data is primarily associated with age and is not associated with the other factors examined. The results of this analysis substantiate an elevated risk of fatal accident involvement for younger drivers of large trucks.     

Fatal intersection crashes in Norway: Patterns in contributing factors and data collection challenges

Fatal motor vehicle intersection crashes occurring in Norway in the years 2005–2007 were analyzed to identify causation patterns among their underlying contributing factors, and also to assess if the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to do causation pattern analysis. 28 fatal accidents were analyzed. Causation charts of contributing factors were first coded for each driver in each crash using the Driving Reliability and Error Analysis Method (DREAM). Next, the charts were aggregated based on a combination of conflict types and whether the driver was going straight or turning. Analysis results indicate that drivers who were performing a turning maneuver in these crashes faced perception difficulties and unexpected behavior from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers who were going straight on the other hand had less perception difficulties but largely expect any turning drivers to yield, which led to either slow reaction or no reaction at all. In terms of common contributing factors, those often pointed to in literature as contributing to fatal crashes, e.g. high speed, drugs and/or alcohol and inadequate driver training, contributed in 12 of 28 accidents. This confirms their prevalence, but also shows that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, there was an asymmetry in terms of reported obstructions to view due to signposts and vegetation. These were frequently reported as contributing for turning drivers, but rarely reported as contributing for their counterparts in the same crashes. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver held legally liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator approach needs to be addressed to avoid future bias in crash investigation reports.