Comparison of contributing factors in hit-and-run crashes with distracted and non-distracted drivers

Among different types of crashes, hit-and-run is driver’s failure to stop after a vehicle crash. There are many accidents where drivers could actually be at fault or totally innocent, and leaving the scene would turn an innocent driver into a criminal. The current paper aims to contribute to the literature by exploring the association of different variables pertaining to the condition of infrastructure, environment, driver, population of the area, and crash severity and type with hit-and-run crashes. The analysis is performed for two data sets: (i) crashes where the driver was distracted; and (ii) crashes where driver was not distracted. Hit-and-run crash data with corresponding factors are police-reported data for crashes within Cook County, Illinois, occurring between 2004 and 2012. A logistic regression model assessed 43 variables within 16 categories for statistically significant association with hit-and-run crashes, for drivers with and without distraction. For both driver distraction statuses, 17 variables were associated with a significant increased probability of a hit-and-run crash and 10 variables were associated with a significant decreased probability. Additionally, it was found that crashes on curve level and curve hillcrest road alignment types were associated with increased likelihood of a hit-and-run crash when the driver was distracted and decreased likelihood when the driver was not distracted. Variables related to hit-and-run crashes vary depending on driver’s distraction status. When comparing likelihood to flee the scene after a crash, non-distracted drivers are 27% less likely to do so compared to distracted drivers.     

The perception of bicycle crashes with and without motor vehicles: Which crash types do older and middle-aged cyclists fear most?

Several studies have focused on the perceived risk of bicycle crashes (irrespective of crash types) and concluded that cycling near high volumes of motor vehicles deters people from cycling. The perceived risk of bicycle crash types (with or without motor vehicles) has not yet been studied. Cyclists, both in countries with low and high levels of cycling participation, are substantially more likely to sustain severe injuries in single-bicycle crashes than in bicycle-motor vehicle crashes. This questionnaire study sets out to compare which bicycle crash types are perceived to cause most hospitalizations among cyclists. The study comprised cyclists over 55 years in the Netherlands, and over 40 years in the Belgian regions of Flanders (a region with high cycling participation), Brussels and Wallonia (regions with low cycling participation). The majority of cyclists (60%) perceive bicycle-motor vehicle crashes cause most hospitalizations among cyclists. This percentage is greatest in the areas of Brussels and Wallonia and lowest in the Netherlands. Cyclists who were involved in a bicycle-motor vehicle crash themselves are more likely to regard this crash type as the most common cause of hospitalizations among cyclists, while cyclists over 60 years who were involved in a crash without a motor vehicle are more likely to perceive that crash type as the most common cause. The smaller perception bias in the study areas with higher cycling participation – particularly the Netherlands and to a somewhat lesser degree Flanders – is probably due to bicycle infrastructure being more separated from high-speed motor traffic, leaving cyclists less exposed. The outcomes show that cyclists underestimate the likelihood of severe injuries due to single-bicycle crashes. New interventions should raise the awareness of the risk of single-bicycle crashes and provide solutions to avoid such crashes.     

Contributing factors to motorcycle injury crashes in Victoria,Australia

IntroductionThe increased popularity of powered two wheelers (PTWs) in Australia, combined with their vulnerability in the event of a crash, necessitates new strategies to prevent serious injury crashes. The purpose of this study was to use case-series data collected from a recent motorcycle case-control study to analyse contributing factors to crashes using a safe systems approach.MethodsA total of 235 injured riders were recruited and completed a questionnaire-based interview, each followed by a detailed inspection of the case motorcycle and crash site by a trained crash investigator. Primary and secondary contributors to the crash were judged based on all available information sources. Analysis of the most frequent contributing factors included separation of cases into single and multi-vehicle crashes. A stepwise logistic regression was used to test for factors associated with human error for multi-vehicle crashes.ResultsTwo thirds of crashes investigated involved another vehicle or road user(s). For multi-vehicle crashes the most common crash scenario involved another vehicle failing to give way to the rider, and the primary contributor was a perception failure or traffic scan error on the part of the other road user. A number of secondary factors were found to be significantly associated with human error type (other road user or rider error), including rider age, traffic density, inappropriate speed of the PTW, and a road design issue. For single vehicle crashes, the most common primary contributor was a misjudgement or control error on the part of the rider, with inappropriate speed as the most frequent secondary contributor.ConclusionsDespite the complexity of factors involved in PTW crashes resulting in injury, a number of significant associations exist between road users as the primary contributing factor (rider or other road user) and secondary factors, including rider age, traffic density, speed and road design issues.     

How does glance behavior influence crash and injury risk? A ‘what-if’ counterfactual simulation using crashes and near-crashes from SHRP2

As naturalistic driving data become increasingly available, new analyses are revealing the significance of drivers’ glance behavior in traffic crashes. Due to the rarity of crashes, even in the largest naturalistic datasets, near-crashes are often included in the analyses and used as surrogates for crashes. However, to date we lack a method to assess the extent to which driver glance behavior influences crash and injury risk across both crashes and near-crashes. This paper presents a novel method for estimating crash and injury risk from off-road glance behavior for crashes and near-crashes alike; this method can also be used to evaluate the safety impact of secondary tasks (such as tuning the radio). We apply a ‘what-if’ (counterfactual) simulation to 37 lead-vehicle crashes and 186 lead-vehicle near-crashes from lead-vehicle scenarios identified in the SHRP2 naturalistic driving data. The simulation combines the kinematics of the two conflicting vehicles with a model of driver glance behavior to estimate two probabilities: (1) that each event becomes a crash, and (2) that each event causes a specific level of injury. The usefulness of the method is demonstrated by comparing the crash and injury risk of normal driving with the risks of driving while performing one of three secondary tasks: the Rockwell radio-tuning task and two hypothetical tasks. Alternative applications of the method and its metrics are also discussed. The method presented in this paper can guide the design of safer driver–vehicle interfaces by showing the best tradeoff between the percent of glances that are on-road, the distribution of off-road glances, and the total task time for different tasks.     

Investigating the influence of time pressure on overtaking maneuvers and crash risk

The research conducted on overtaking maneuver for evaluating drivers’ safety showed adverse effects of urgency on driving performance and decision making. Therefore, a driving simulator study was designed to examine driving performance of the drivers and its implication on overtaking and crash probabilities under increasing time pressure conditions. Eighty-eight participants data were analyzed in the current study. Three different time pressure conditions: No Time Pressure (NTP), Low Time Pressure (LTP), and High Time Pressure (HTP) were considered for analyzing driving performance of the drivers while executing overtaking maneuvers. The driving performance was assessed using minimum time-to-line crossing and coefficient of variation in speed to dissect the safety margin adopted by the drivers while overtaking the lead vehicle. Further, minimum time-to-line crossing and coefficient of variation in speed were considered as explanatory variables to investigate their influence on overtaking and crash probabilities. Parametric survival analysis and Generalized Linear Mixed Models (GLMM) were used to assess the driving performance, overtaking and crash probabilities. The parametric survival analysis showed that minimum time-to-line crossing reduced by 36.7% and 63.8% in LTP and HTP driving conditions, respectively. The GLMM results revealed that coefficient of variation in speed increased by 3.437% in HTP (no significant effect in LTP) as compared to NTP driving conditions. Further, the GLMM results showed that overtaking and crash probabilities decreased with increment in minimum time-to-line crossing and coefficient of variation in speed values. Additionally, it was observed that male drivers took risky decisions than female drivers. Nevertheless, the comparative analysis revealed that male drivers were less prone to crashes than female drivers. Overall, it can be inferred that the drivers take risky decisions with increment in time pressure to complete the driving task, even at the expense of their own safety which exposed them to high likelihood of crashes.     

The prevalence of cognitive disengagement in automobile crashes

The current study analysed crashes identified in a large-scale naturalistic driving database to assess the prevalence of cognitive disengagement (i.e., purely cognitive distraction and mind wandering/microsleep) or episodes wherein the driver did not look away from the roadway during secondary task completion or wherein another clearly observable contributing crash factor was not present, and the driver's reaction to the crash showed symptoms of cognitive disengagement. The study found that <1% (95% CI [0.45, 1.66]) of higher severity crashes had a potential contributing crash factor of mind wandering/microsleep; ~1.5% (95% CI [0.83, 2.32]) had a potential contributing factor of purely cognitive distraction. The results suggest a relatively low prevalence of cognitive disengagement among automotive crashes compared with visual/manual secondary tasks. However, the current methodology is limited in that it does not account for instances where cognitive disengagement, in combination with other factors, may have led to crashes, potentially leading to conservative estimates.     

Research on parking choice behavior of shared autonomous vehicle services by measuring users’ intention of usage

Shared autonomous vehicles (SAVs) are one of the important development directions of smart and green transportation. However, relevant researches are not sufficient at present. The factors influencing the intention to use SAVs and their parking choice behaviors need to be further analyzed. First, in order to better explain, predict, and improve travelers’ intention to use SAVs, the conceptual framework based on technology acceptance model was developed to establish the relationships between the travelers’ intention to use SAVs, social influence of SAVs, attitude toward behavior of SAVs, perceived risk of SAVs, perceived usefulness of SAVs and perceived ease of these use. Then structural equation model (SEM) was established to analyze the relationship between various variables. The results show that the perceived usefulness, behavior attitude, social influence, perceived ease of use, and perceived risk are the main factors that determine the intention to use SAVs. Through the test of direct effect, indirect effect, and total effect in the model, it is found that perceived usefulness has the largest total impact on intention to use SAVs, with a standardized coefficient of 0.765, followed by behavior attitude (0.732), social influence (0.597), perceived ease of use (0.462) and perceived risk of SAVs (−0.452). In addition, through the study of observed indicator variables ATB2 and BI3, it is found that perceived usefulness, perceived ease of use, social influence, perceived risk, attitude toward behavior, and behavior intention all have an impact on parking behavior. In order to study the specific influencing factors of parking choice behavior, a multinomial logit (MNL) model was established to analyze the relationships between travelers’ parking choice behaviors and the influential factors, which include travelers’ individual characteristics, travel attributes, and parking modes’ attributes by extracting from a questionnaire. The results show that the travel time, travel fees, parking charge, cruising fees, parking time and traffic emission are the main factors that determine travelers’ choices of parking. This paper provides advice for operators of SAVs.     

Attention all ‘drivers’: You could be to blame,no matter your behaviour or the level of vehicle automation

Vehicle crashes are one of the leading causes of human deaths worldwide, with crashes predominately attributed to failures of human drivers. Whilst increasing vehicle automation is argued to reduce road crashes via decreased driver involvement, automation also raises concerns around driver blame and stakeholder responsibility. This study examines blame for crash scenarios across four different forms of driver distraction behaviours (phone, sleep, work and driving under the influence), and across four levels of vehicle automation (no automation [manual], partially automated, highly automated, fully automated), using a mixed (qualitative and quantitative) methods approach. Participants (n = 205) were randomised into one of the four levels of vehicle automation and were presented with vignette crash scenarios involving a pedestrian being hit by a vehicle. Results revealed that scenarios varying driver behavior at the time of the crash, had no significant impact on participants’ blame attribution or selected course of action. The qualitative analysis revealed that despite semantic distinction between some driver behaviours, drivers were deemed responsible for the crash. As automation increased, attribution of blame towards the driver decreased, but did not disappear. Blame simultaneously increased towards other stakeholders including the manufacturer and the government, as level of automation increased. These findings mirror that of previous research and further highlight the need for legal frameworks for crashes with automated vehicles, irrespective of driver behaviours.     

Gap acceptance at stop-controlled T-intersections in a simulated rural environment

A high proportion of road crashes occur at intersections: in Victoria, Australia, 15% of fatal crashes and 25% of serious injury crashes occur at T-intersections, with similar proportions occurring at cross intersections. Many of these crashes can be attributed to drivers’ inappropriate gap selection. The current study used a driving simulator to examine the influence of both the driver’s intended manoeuvre and the gap duration on gap acceptance behaviour at stop-controlled T-intersections. Drivers completed 18 gap acceptance trials, with manoeuvre (turning across traffic, merging with traffic) and gap duration (3–11 s) manipulated within-subjects. There was a trend whereby drivers accepted shorter gaps when turning across traffic compared to merging with traffic, which was significant at longer gaps (⩾9 s) but not at shorter, safety–critical gaps (⩽8 s). In addition, accepted lag times varied with manoeuvre. When merging with traffic drivers demonstrated longer accepted lag times, suggesting that turn strategies differ depending on traffic direction and intended manoeuvre. Overall the results suggest that the drivers’ intended manoeuvre influences gap acceptance, although gap duration remains the most influential factor. Implications of these findings for the development and design of intersection decision support systems are discussed.     

Relationships amongst psychological determinants,risk behaviour,and road crashes of young adolescent pedestrians and cyclists: Implications for road safety education programmes

Road safety education (RSE) assumes that psychological determinants predict risk behaviour, and subsequently that risky road behaviour predicts crash involvement. This study examined the validity of this assumption, by analysing these relationships in two age groups of teen cyclists and pedestrians: a younger age group (12 and 13 years old: n = 1372) and an older age group (14–16 years old: n = 938). A questionnaire was administered at school during regular class consisting of items on demographics, on risk behaviour based on the Generic Error Model System (GEMS), on psychological determinants targeted in RSE programmes, and on crash involvement and near crashes. For the younger age group, the results indicated that the risk behaviours ‘errors’, ‘dangerous play’, and ‘lack of protective behaviour’ predicted self-reported crashes; for the older age group only ‘errors’ were found to be predictive of self-reported crashes and near crashes. Path analyses confirmed that risk behaviour could be predicted from the psychological determinants, sharing respectively 44% of the variance in the younger age group and 34% in the older group. In conclusion, these results confirm the RSE assumption that psychological determinants are associated with a higher frequency of risk behaviours and that the latter are again associated with higher crash frequencies. Just as in earlier studies on adolescent risk behaviour, the GEMS based distinction between errors and violations was not confirmed, suggesting that this distinction – derived from studies on adult car drivers – may not apply to young adolescent cyclists and pedestrians.     

Socio-economic and driving experience factors affecting drivers’ perceptions of traffic crash risk

Drivers are estimated to contribute an overwhelming proportion to the burden of traffic crashes, as factors that increase crash risk are frequently due to unsafe driving behaviours. The relationship between risk perceptions and people’s risky driving behaviours is still not well understood. This paper aims to further analyse the potential effect of risky driving behaviours on drivers’ perceptions of crash risk and differences in perceptions among drivers.Crash risk perceptions in an inter-city, two-way road context of 492 drivers were measured by using a Stated Preference (SP) ranking survey. Rank-ordered logit models were used to evaluate the impact on risk perception of five unsafe driving behaviours and to identify differences in drivers’ risk perceptions. The five unsafe driving behaviours considered in the analysis were respectively related to whether or not the driver follows the speed limits, the rules of passing another car and the safe distance, whether or not the driver is distracted, and whether or not she/he is driving under optimal personal conditions.All risky driving behaviours showed a significant potential effect (p < 0.001) on crash risk perceptions, and model’s results allowed to differentiate more important from less important unsafe driving behaviours based on their weight on perceived crash risk. Additionally, this paper further analyses the potential differences in risk perception of these traffic violations between drivers of different characteristics, such as driving experience, household size, income and gender.The SP technique could be applied to further analyse differences in perceptions of risky driving behaviours among drivers. Future research should consider the potential effect of driving skill on perceptions of risky driving behaviours.     

Approaching intersections: Gaze behavior of drivers depending on traffic,intersection type,driving maneuver,and secondary task involvement

Urban intersections are hotspots for crashes because they provide a location for several traffic streams and types of road users to cross. A main cause of crashes is the misinformation of drivers as they fail to sense relevant visual information. We aimed to analyze the gaze behavior of car drivers in a variety of intersection scenarios, bringing together the partial findings of previous research, and examine the interdependencies of the contributing factors to provide a database for driver modeling. In a driving simulator study with 59 participants, we varied intersection scenarios regarding drivers’ right of way (yield sign, green traffic light), intersection type (T junction, X intersection), surrounding traffic (none, irrelevant, relevant), and intended driving maneuver (left turn, right turn, going straight). A total of 25 intersection scenarios were presented in a within-subjects design to a control group and a group with a cognitive load task (counting back in numbers of two). Fixations were coded regarding defined areas of interest in the field of view and separated according to three segments of the intersection approach: 75–50 m, 50–25 m, and 25–0 m before entering the intersection. The results show that the effect of surrounding traffic, secondary task engagement, and the intended driving maneuver changed dramatically depending on the right of way of the driver. Surrounding traffic primarily affected gaze behavior in scenarios of ceding the right of way close to the intersection entry. The cognitive load task increased fixations on the road center especially in situations where the driver had the right of way, but less in situations of ceding the right of way. Interactions with the type of intersection were only apparent for different driving maneuvers. This study provides a detailed and comprehensive picture of drivers’ attentional processes when approaching intersections which is relevant for understanding and modeling of driver behavior in urban traffic.     

Investigating the reasons behind the intention to report cycling crashes to the police and hospitals in Denmark

This study explores the factors underlying the reporting intentions of cycling crashes by looking at barriers to reporting from other contexts and eliciting them via a survey and a structural equation model (SEM). The barriers consist of the attitude that crash reporting is useless, the preference to allocate time to other activities, the concerns about family distress and social image, the distrust in the police, and the medical consultation aversion. The survey elicited the reasons as well as socio-economic characteristics, cycling habits and last crash experience of cyclists, and yielded 1512 complete responses that were used for SEM estimation. The empirical analysis revealed that: (i) distrust in the police and medical consultation aversion are related to the reporting intentions both directly and indirectly through the attitude that crash reporting is useless and the preferences to allocate time to other activities; (ii) medical consultation aversion has a higher weight than the distrust in the police in demotivating cycling crash reporting intentions; (iii) the reasons are all strongly related to cyclists’ characteristics and last cycling crash characteristics; and (iv) information provision regarding the societal benefits of crash reporting is important for increasing the reporting rate.     

Influence of pedestrian-to-vehicle technology on drivers’ response and safety benefits considering pre-crash conditions

Pedestrian-to-vehicle (P2V) technology may offer a promising approach to reducing pedestrian crashes. However, its influences on both driver response and safety benefits have been little studied in previous research, particularly in regard to the variation of influences between different pre-crash scenarios. To investigate these influences, this study designed three pre-crash scenarios based on pedestrian crash contributing factors identified from crash reports, and collected 44 drivers’ driving simulator experiments’ data. The results clarified how using P2V technology to warn drivers of an impending collision improves safety by causing a series of changes for both brake operation and braking profile. These series of changes were further demonstrated to vary between scenarios. The study showed that P2V technology may be particularly useful in scenarios in which a pedestrian’s crossing intention is unclear; specifically, in this type of scenario, the P2V warning had changed the braking process from a panic brake of “slow reaction-hard brake” to a comfortable brake of “quick reaction-gentle brake.” In addition, the P2V warning may be less effective in “low-risk” level scenarios where a driver is confident that he/she can handle the situation through a more conservative evasive action and don’t need to react strongly to a warning. Moreover, depending on the pre-crash scenario, the P2V warning may be mostly beneficial for drivers who had a crash/citation in the past five years and working-aged drivers.     

Predictors of driving outcomes in advancing age

This study aimed to develop predictive models for real-life driving outcomes in older drivers. Demographics, driving history, on-road driving errors, and performance on visual, motor, and neuropsychological test scores at baseline were assessed in 100 older drivers (ages 65-89 years [72.7]). These variables were used to predict time to driving cessation, first moving violation, or crash. Using Cox proportional hazards regression models, significant individual predictors for driving cessation were greater age and poorer scores on Near Visual Acuity, Contrast Sensitivity, Useful Field of View, Judgment of Line Orientation, Trail Making Test-Part A, Benton Visual Retention Test, Grooved Pegboard, and a composite index of overall cognitive ability. Greater weekly mileage, higher education, and "serious" on-road errors predicted moving violations. Poorer scores from Trail Making Test-Part B or Trail Making Test (B-A) and serious on-road errors predicted crashes. Multivariate models using "off-road" predictors revealed (a) age and Contrast Sensitivity as best predictors for driving cessation; (b) education, weekly mileage, and Auditory Verbal Learning Task-Recall for moving violations; and (c) education, number of crashes over the past year, Auditory Verbal Learning Task-Recall, and Trail Making Test (B-A) for crashes. Diminished visual, motor, and cognitive abilities in older drivers can be easily and noninvasively monitored with standardized off-road tests, and performances on these measures predict involvement in motor vehicle crashes and driving cessation, even in the absence of a neurological disorder. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

Roles of personal and environmental factors in the red light running propensity of pedestrian: Case study at the urban crosswalks

Pedestrian is vulnerable to mortality and severe injury in road crashes. Red light running violation of pedestrians is one of the leading causes to the crashes at signalized intersections, at which the crash involvement rates of pedestrians are high. Therefore, it is important to identify the factors that affect the propensity of red light running of pedestrian. In this study, effects of both personal factors (pedestrians’ demographics and behavior) and environmental factors (presence and behavior of other pedestrians, signal time, and traffic condition) on the individual decision of red light running violation are examined, using the video observation surveys at the signalized crossings that are prone to pedestrian-vehicle crashes and have moderate pedestrian and vehicular traffic volumes in the urban area. Crossing behaviors of 6320 pedestrians are captured. Results of a random parameter logit model indicate that pedestrian gender, age, number of lanes, presence of a companion, number of pedestrians around, presence of other violators in the same cycle, time to green, red time, traffic volume, and percentage of heavy vehicles all affect the propensity of red light running violation of pedestrians. Also, there are significant interaction effects by pedestrian’s gender and age, presence of other violators, with a companion, and traffic volume on the propensity. Findings are indicative to the development of effective engineering, enforcement and educational initiatives combating the red light running violation behavior of pedestrians. Therefore, pedestrian safety level at the signalized intersections can be enhanced.     

Increasing motorist compliance and caution at stop signs.

This study evaluated strategies to improve motorist compliance and caution at three stop‐sign‐controlled intersections with a history of motor vehicle crashes. The primary intervention was a light‐emitting diode (LED) sign that featured animated eyes scanning left and right to prompt drivers to look left and right for approaching traffic. Data were scored from videotape on the percentage of drivers coming to a complete stop and the percentage of drivers looking right before entering the intersection. Observational data were collected on the percentage of right‐angle conflicts (defined as braking suddenly or swerving from the path to avoid an intersection crash). The introduction of the LED sign according to a multiple baseline across the three intersections was associated with an increase in the percentage of vehicles coming to a complete stop at all three intersections and a small increase in the percentage of drivers looking right before entering the intersections. Conflicts between vehicles on the major and minor road were also reduced following the introduction of the animated eyes prompt.     

Reducing young drivers’ crash risk: Are we there yet? An ecological systems-based review of the last decade of research

The involvement of young novice drivers in road crashes and violations has remained a significant transport and public health issue worldwide. Despite extensive evidence that multiple individual, social, and environmental factors contribute to risk while driving, crashes among young novice drivers have decreased only marginally. There is a need to define clear indicators of risk as well as develop effective interventions.The current study reviews the literature on young novice drivers, including empirical studies, systematic reviews, and crash reports published over the past ten years to provide a synthesis of risk and protective factors across multiple domains, from individual characteristics, to social influences, to behavioural and social interventions, to the car and road environment. Adopting an ecological systems perspective, we discuss links between these domains to clarify the strongest indicators of risk for young novice drivers as compared to experienced drivers, and we collate the available evidence on social and environmental factors that can improve young drivers’ behaviour so to reduce the rate of their road crashes.Among the factors discussed, the incomplete maturation of cognitive skills crucial to safe driving (visual scanning, hazard anticipation, handling of in-vehicle distractions) and the higher susceptibility to social influences (especially peers and parents) emerged as the strongest determinants of discrepancies in performance between young novice and experienced drivers. Growing awareness of the complex array of factors intervening synergistically in young drivers’ risk, as well as technological advancements have led to the design of interventions with some level of effectiveness, however, further research and more robust programmes adopting ecological and holistic approaches are needed to fully address the young driver problem.     

Cultural foundations of safety culture: A comparison of traffic safety culture in China,Japan and the United States

Understanding how to assess the influence of culture on traffic safety is important for improving traffic safety globally. Traffic safety culture is embedded in the larger context of country’s cultural norms and values, producing different safety outcomes even when other factors are similar. The current work examines how culture influences traffic safety outcomes in three of the largest automobile countries in the world, but which have very different cultural values and which also have very different traffic safety outcomes: China, Japan and the United States. China has an emerging driver population and cultural values that result in aberrant driving behaviors and “scrambling” to gain the right of way, producing a high number of crashes. Japan has an established driver culture, but an emphasis on reducing risk, which results in a lower rate of crashes. The United States, with the most established “car culture”, has an historical and cultural view of the car as a representation of freedom, leading to choices that result in higher crash rates than many countries around the world. The current work explores these cultural underpinnings for traffic safety culture in each country by establishing the historical basis for a traffic culture, examining road, vehicle engineering and legal standards, and reviewing available crash data and data on safety attitudes. These countries are compared across the different dimensions to establish unique cultural influences on traffic safety.