Pedestrian crashes at priority-controlled junctions,roundabouts, and signalized junctions: The UK case study

Objectives: Over half of pedestrians killed and seriously injured in Great Britain in 2015 were involved in crashes at junctions. This study investigates the nature of these crashes.

Methods: A study was conducted into pedestrian casualty crashes at priority controlled junctions, roundabouts and signalised junctions in England between 2005 and 2015 using information from the UK STATS19 accident database, the UK National Travel Survey and the UK National Census. Consideration was given to coding frequencies of contributory factors, exposure (in terms of miles walked or driven) as well as age, gender and the resident deprivation index of the road users involved.

Results and Conclusions: In terms of indicative blame, the coding frequencies of subjectively determined pedestrian actions and behaviour factors which might have contributed to pedestrian casualty crashes were found to be between 1.6 and 2.8 times the frequencies of driver actions and behavioural factors. Substantial social gradients were found in pedestrian casualty rates per miles walked and in the driver involvement rates per mile driven with those from the most deprived quintile having higher rates. In addition, it was found that female pedestrians, aged 60 years and over, had higher pedestrian casualty rates, per billion miles walked, for all three junction types, when compared with males and females under the age of 60 years, apart from male pedestrians aged 16 years and younger at priority controlled junctions.     

Spatial analysis of mortality rate of pedestrian accidents in Iran during 2012–2013

Objectives: Considering the high mortality rate of pedestrians in traffic accidents in Iran, the present study aimed to determine the high-risk and low-risk areas of accidents resulting in pedestrian deaths and the spatial analysis of their mortality rates.

Methods: This cross-sectional study included 4,371 deceased pedestrians reported by the Legal Medicine Organization in Iran from March 2012 to March 2013. For spatial analysis, the collected data were entered into ArcGIS software version 10.2 and a spatial map of the mortality rate was drawn according to the distribution of data in the provinces. Using this software, high-risk and low-risk areas were identified by calculating the spatial autocorrelation of the data. The Moran’s index of road accident patterns was surveyed and high-risk and low-risk points were identified using the local Getis index.

Results: The age-standardized incidence rate was 6.8 per 100,000. After analyzing the data using ArcGIS software, the local Moran’s index showed a cluster pattern with a high mortality rate in 3 provinces of Mazandaran, Gilan, and Qazvin. In identifying high-risk and low-risk points, the local Getis index showed 3 hot spots with a confidence interval of 99% in Qom, Qazvin, and Mazandaran and 5 hot spots with a 95% confidence interval in Markazi, Tehran, Zanjan, Gilan, and Golestan provinces.

Conclusions: According to the cluster pattern of accidents in the 3 provinces and the presence of hot spots in 9 provinces, it is necessary to identify factors that increase the risk of death in the study provinces in order to reduce the mortality rate among pedestrians due to traffic accidents. Therefore, to reduce the pedestrian mortality rate, especially in high-risk provinces, some studies need to be conducted to determine the risk factors in pedestrian mortality.     

Fatally injured drivers in Norway 2005–2015—Trends in substance use and crash characteristics

Objective: Norway introduced a “Vision Zero” strategy in 2001, using multiple approaches, aiming toward a future in which no one will be killed or seriously injured in road traffic crashes (RTCs). Official statistics show that the number of fatally injured road users has declined substantially from 341 deaths in 2000 to 117 in 2015. In-depth crash investigations of all fatal RTCs started in Norway in 2005. The aim of this study was to investigate whether fatal crash characteristics, vehicle safety features, and prevalence of drugs and/or alcohol among fatally injured drivers and riders has changed during 2005–2015, accompanying the reduction in road fatalities.

Methods: Data on all car/van drivers and motorcycle/moped riders fatally injured in RTCs during 2005–2015 were extracted from Norwegian road traffic crash registries and combined with forensic toxicology data.

Results: The proportion of cars and motorcycles with antilock braking systems and cars with electronic stability control, increased significantly during the study period. The prevalence of nonuse of seat belts/helmets and speeding declined among both fatally injured drivers and riders. In addition, the prevalence of alcohol declined, though no significant change in the total prevalence of other substances was noted.

Conclusion: The observed changes toward more safety installations in cars and motorcycles and lower prevalence of driver-related risk factors like alcohol use, speeding, and nonuse of seat belts/helmets among fatally injured drivers/riders may have contributed to the decrease in road traffic deaths.     

Impact of perceptual countermeasures on driving behavior at curves using driving simulator

Objective: The probability of crash occurrence on horizontal curves is 1.5 to 4 times higher than that on tangent sections. A majority of these crashes are associated with human errors. Therefore, human behavior in curves needs to be corrected.

Methodology: In this study, 2 different road marking treatments, optical circles and herringbone patterns, were used to influence driver behavior while entering a curve on a 2-lane rural road section. A driving simulator was used to perform the experiment. The simulated road sections are replicas of 2 real road sections in Flanders.

Results: Both treatments were found to reduce speed before entering the curve. However, speed reduction was more gradual when optical circles were used. A herringbone pattern had more influence on lateral position than optical circles by forcing drivers to maintain a safe distance from opposing traffic in the adjacent lane.

Conclusion: The study concluded that among other low-cost speed reduction methods, optical circles are effective tools to reduce speed and increase drivers’ attention. Moreover, a herringbone pattern can be used to reduce crashes on curves, mainly for head-on crashes where the main problem is inappropriate lateral position.     

Improving pedestrian safety using combined HOG and Haar partial detection in mobile systems

Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.

Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.

Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.

Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian.     

Trauma demography and clinical epidemiology of motorcycle crash–related head injury in a neurosurgery practice in an African developing country

Objective: Though motor vehicle crashes (MVCs) were the main cause of head trauma from road traffic injuries (RTIs), motorcycle crashes (MCCs) are now a major cause of RTI-related head injury (HI) in many developing countries.

Methods: Using a prospective database of HIs from a neurosurgical practice in a sub-Saharan African developing country, a cross-sectional survey was conducted for the trauma demography and clinical epidemiology of this MCC-related HI.

Results: Motorcycle crashes accounted for 57% (473/833) of all RTI-related HIs in this registry. The victims, with a mean age of 33.1 years (SD = 18.3), consisted mainly of males (83.1%), those of low socioeconomic status (>90%), and those aged between 20 and 40 years old (56%). MCCs involved only riders in 114 cases (114/473, 32.1%), of which 69% were motorcycle–motorcycle crashes. The HI was moderate–severe in 50.8%; clinical symptomatology of significant HI included loss of consciousness (92%), anisocoria (35%), Abbreviated Injury Scale head (AIS–head) score > 3 (28%), and CT-Rotterdam score > 3 (30%). Extracranial systemic injury involved the limbs most frequently, with an Injury Severity Score (ISS) >25 in 49%. The fatality rate was 24%.

MCC-related HI among pedestrian victims involved more vulnerable age groups (the young and elderly) but have lower mean ISS compared to motorcycle passengers (mean ISS = 23.5 [11.6] vs. 27.4 [13.0]; 95% confidence interval [CI], 1.27–6.49; P = .004). In addition, compared to a contemporary cohort of MVC-related HIs in our registry, MCC victims were older (mean age 34.8 years [18.0] vs. 30.8 [18.4]; P = .002); had higher proportions of certain extracranial trauma like long bone fractures (71 vs. 29%; P = .02); and suffered fewer surgical brain lesions (25.5 vs. 17.2%; P = .004).

Conclusions: Motorcycle crashes are now a significant threat to the heads, limbs, and lives of vulnerable road users in developing countries.     

Severity of motorcycle crashes in Dar es Salaam,Tanzania

Objective: Motorcycles are a common mode of transportation in low- and middle-income countries. Tanzania, in particular, has experienced an increased use of motorcycles in the last decade. In Dar es Salaam, motorcycles provide door-to-door travel and often operate where more conventional services are uneconomical or physically impossible to maneuver. Although motorcycles play a crucial role in improving mobility in the city, they have several safety issues. This study focuses on identifying factors influencing the severity of motorcycle crashes.

Method: A multinomial logit analysis was conducted to identify factors influencing the severity of motorcycle crashes in Dar es Salaam, Tanzania. The severity categories were fatal, severe injury, minor injury, and property damage only (PDO). The analysis was based on a total of 784 motorcycle crashes that occurred from 2013 to 2016.

Results: The following factors were found to increase the probability of a fatality: Speeding, driving under the influence, head-on impact, presence of horizontal curves, reckless riding, off-peak hours, violations, and riding without a helmet. The results indicate that crashes occurring on weekdays, during peak hours, at intersections, involving a rear-end impact, in daylight, on street roads, and under clear weather conditions decrease the probability of a fatality. However, minor injury and PDO crashes were found to be associated with crashes occurring during peak hours, at intersections, and on street roads, as well as failure to yield right-of-way.

Conclusions: Several countermeasures are recommended based on the study findings. The recommended countermeasures focus on the holistic safety improvement strategies constituting the three Es of highway safety, namely, engineering, education, and enforcement.     

Effect of the zero-tolerance drinking and driving law on mortality due to road traffic accidents according to the type of victim,sex, and age in Rio de Janeiro,Brazil: An interrupted time series study

Objective: The objective of this study was to estimate the effect of the Brazilian zero-tolerance drinking and driving law on mortality rates due to road traffic accidents according to the type of victim, sex, and age.

Methods: An interrupted time series design was used to compare yearly mortality rates due to road traffic accidents in Rio de Janeiro, Brazil, before and after the zero-tolerance drinking and driving law came into effect on June 19, 2008. Yearly mortality rates were compared according to the type of victim: pedestrian, cyclist, motorcyclist, and vehicle occupant. We used the Prais-Winsten procedure of autoregression in the analysis of time series; the outcome of this analysis was the annual percentage change in the rates. Overall and stratified analyses were conducted to investigate whether the zero-tolerance drinking and driving law may have had a distributional effect on mortality rates due to road traffic accidents depending on sex and age group; a significance level of P < .01 was accepted.

Results: From 1999 to 2016, there were 15,629 deaths due to road traffic accidents in Rio de Janeiro. The effect of the zero-tolerance drinking and driving law on overall mortality rates due to road traffic accidents in Rio de Janeiro was not statistically significant. However, among cyclists and motorcyclists aged ≥60 years and among pedestrians of both sexes and aged ≥20 years, the effect of the zero-tolerance drinking and driving law was to decrease mortality due to road traffic accidents at a yearly rate.

Conclusion: There is evidence of reduced mortality rates due to road traffic accidents among cyclists and motorcyclists aged ≥60 years and among pedestrians of both sexes aged ≥20 years in the second major Brazilian capital 9 years after the zero-tolerance drinking and driving law was adopted.     

Epidemiology of alcohol and drug screening among pedestrian fatalities in the United States, 2014–2016

Objective: U.S. pedestrian fatalities increased by 25% between 2010 and 2015. Risk factors include distractions, the built environment, urbanization, economic variables, and weather conditions. Of interest is the role of alcohol and drugs in premature death among pedestrians. This study sought to explore the prevalence of substance use screenings among pedestrian fatalities in the United States between 2014 and 2016.

Methods: Data were collected from the Fatality Analysis Reporting System provided by the NHTSA. Pedestrian crash variables included demographics as well as information regarding alcohol or drug testing status. Frequency and cross-tabulation tables were constructed to assess the prevalence of screening by person, place, and time. Log-linear analyses were completed to explore age, race, and sex differences. A 3-year examination period was used to control for yearly fluctuations and to incorporate an increasing trend in cases.

Results: Pedestrian fatalities accounted for 84% of all deaths among vulnerable road users during the examination period. Those most at risk were white males between the ages of 45 and 64. Over all states, 74.7% of fatalities were tested for alcohol and 67.1% were tested for drugs; further, 66.5% of cases were tested for both alcohol and drugs and 24.8% were tested for neither substance. Cases screened for both alcohol and drugs ranged from 2.9% in North Carolina to 95.7% in Nevada and those testing for neither substance ranged from a high of 68.9% in Indiana to a low of 1.1% in Maryland. Log-linear regression revealed significant differences in alcohol screening by age and race but not by sex. Differences in drug screening were not identified for any demographic variable. Fatalities tested for alcohol were significantly more likely to be tested for drugs; only 8.2% were screened solely for alcohol and 0.05% were screened for drugs alone.

Conclusions: Preventive strategies become more important as pedestrian crashes and fatalities increase. Risk reduction in the form of policy change, alterations to the built environment, or interdisciplinary approaches to injury prevention is dependent upon best evidence supported in part by more deliberate and consistent screening.     

Identifying the crash characteristics on freeway segments based on different ramp influence areas

Objective: This study aimed to explore the relationship between crash types and different freeway segments and identify the factors contributing to crashes on different freeway segments. Unlike most of the previous studies on freeway segments, this study separately investigates basic freeway segments, single ramp influence segments, and multiple ramp influence segments.

Methods: Nonlinear canonical correlation analysis (NLCCA) and proportionality test were used to identify the relationship between crash types and different freeway segments. The data sets for the different freeway segments accumulated for this study consist of 9,867 crash samples with complete information on all 22 chosen variables. A multinomial logit model (MNL) was used to estimate the influence of crash factors on different freeway segments.

Results: The results show that weaving and diverge overlap influence segments (WD) are more likely to have injury or fatal crashes; diverge and diverge overlap influence segments (DD) are more likely to have property damage–only (PDO) crashes; merge and merge overlap influence segments (MM) are more likely to have sideswipe crashes; and WD have non-sideswipe crashes; WD and weaving overlap influence segments (MW) are more likely to have rear end crashes; and MM segments are less likely to have hit object crashes. The contributing factors are identified by MNL and the results show that different traffic variables, environmental variables, vehicle variables, driver variables, and geometric variables significantly affected the likelihood of crashes on different freeway segments.

Conclusions: Investigation of crash types and factors contributing to crashes on different freeway segments is based on multiple ramp influence segments, which can promote a better understanding of the safety performance of various freeway segments.     

A semi-automated tool for identifying agricultural roadway crashes in crash narratives

Objective: Crash reports contain precoded structured data fields and a crash narrative that can be a source of rich information not included in the structured data. The narrative can be useful for identifying vulnerable roadway users, such as agricultural workers. However, using the narratives often requires manual reviews that are time consuming and costly. The objective of this research was to develop a simple and relatively inexpensive, semi-automated tool for screening crash narratives and expediting the process of identifying crashes with specific characteristics, such as agricultural crashes.

Methods: Crash records for Louisiana from 2010 to 2015 were obtained from the Louisiana Department of Transportation (LaDOTD). Records with narratives were extracted and stratified by vehicle type. The majority of analyses focused on a vehicle type of farm equipment (Type T). Two keyword lists, an inclusion list and an exclusion list, were created based on the published literature, subject-matter experts, and findings from a pilot project. Next, a semi-automated tool was developed in Microsoft Excel to identify agricultural crashes. Lastly, the tool’s performance was assessed using a gold standard set of agricultural narratives identified through manual review.

Results: The tool reduced the search space (e.g., number of narratives that need manual review) for narratives requiring manual review from 6.7 to 59.4% depending on the research question. Sensitivity was high, with 96.1% of agricultural crash narratives being correctly classified. Of the gold standard agricultural narratives, 58.3% included an equipment keyword and 72.8% included a farm equipment brand.

Conclusion: This article provides information on how crash narratives can supplement structured crash data. It also provides an easy-to-implement method to facilitate incorporating narratives into safety research along with keyword lists for identifying agricultural crashes.     

A novel driver hazard perception sensitivity model based on drivers’ characteristics: A simulator study

Objective: Considering the high annual number of fatal driving accidents in Iran, any approach for reducing the number or severity of driving accidents is a positive step toward decreasing accident-related losses. Accidents can often be avoided by a timely reaction of the driver. One of the steps before reacting to a hazard is perception. Some driver characteristics may affect road hazard perception. In this research, it was assumed that various driver characteristics, including demographic characteristics and cognitive characteristics, have an impact on driver perception.

Methods: The driving simulator used in this research provides various scenarios; for example, passing a pedestrian or animal across the road or placing fixed objects in a 2-lane separated rural road for 2 groups of experienced and inexperienced drivers under day and night lighting conditions. The go/no-go test was carried out in order to assess drivers’ attention to driving tasks and inhibitory control. A structural equation model (SEM) was used to estimate the relation between driver characteristics and sensitivity to road hazard perception. A new hazard perception index was proposed based on the time intervals in the hazard vulnerability.

Results: The results show that the most effective variables in the analysis of sensitivity to hazard perception are driving experience (in kilometers) during the last 3 years and road lighting conditions. Moreover, hazard perception sensitivity was improved by better inhibitory control, selective attention, and decision making, more carefulness, the average amount of daily sleep, and marital status.

Conclusion: The results of this research may be useful in educating and advertising programs. It also could enhance sensitivity to perception of hazards such as pedestrians, animals, and fixed obstacles among young and novice drivers.     

A clustering approach to integrate traffic safety in road maintenance prioritization

Objectives: We combine data on roads and crash characteristics to identify patterns in road traffic crashes with regard to road characteristics. We illustrate how combined analysis of data regarding road maintenance, maintenance costs, road characteristics, crash characteristics, and geographical location can enrich road maintenance prioritization from a traffic safety perspective.

Methods: The study is based on traffic crash data merged with road maintenance data and annual average daily traffic (AADT) collected in Denmark. We analyzed 3,964 crashes that occurred from 2010 to 2015. A latent class clustering (LCC) technique was used to identify crash clusters with different road and crash characteristics. The distribution of crash severity and estimated road maintenance costs for each cluster was found and cluster differences were compared using the chi-square test. Finally, a map matching procedure was used to identify the geographical distribution of the crashes in each cluster.

Results: Results showed that based on road maintenance levels there was no difference in the distribution of crash severity. The LCC technique revealed 11 crash clusters. Five clusters were characterized by crashes on roads with a poor maintenance level (levels 4 and 3). Only a few of these crashes included a vulnerable road user (VRU) but many occurred on roads without barriers. Four clusters included a large share of crashes on acceptably maintained roads (level 2). For these clusters only small variations in road characteristics were found, whereas the differences in crash characteristics were more dominant. The last 2 clusters included crashes that mainly occurred on new roads with no need for maintenance (level 1). Injury severity, estimated maintenance costs, and geographical location were found to be differently distributed for most of the clusters.

Conclusions: We find that focusing solely on road maintenance and crash severity does not provide clear guidance of how to prioritize between road maintenance efforts from a traffic safety perspective. However, when combined with geographical location and crash characteristics, a more nuanced picture appears that allows consideration of different target groups and perspectives.     

A multinomial logit analysis of factors associated with severity of motorcycle crashes in Ghana

Objective: The objective of this study was to explore the factors affecting motorcycle crash severity in Ghana.

Methods: A retrospective analysis of motorcycle crash data between 2011 and 2015 was conducted using a motorcycle crash data set extracted from the National Road Traffic Crash Database at the Building and Road Research Institute (BRRI) in Ghana. Injury severity was classified into 4 categories: Fatal, hospitalized, injured, and damage only. A multinomial logit modeling framework was used to identify the possible determinants of motorcycle crash severity.

Results: During the study period, a total of 8,516 motorcycle crashes were recorded, of which 22.9% were classified as fatal, 42.1% were classified as hospitalized injuries, 29.4% were classified as slight injuries, and 5.6% were classified as damage-only crashes. The estimation results indicate that the following factors increase the probability of fatal injuries: At a junction; weekend; signage; poor road shoulder; village settlement; tarred and good road surface; and collision between motorcycle and heavy goods vehicle (HGV). Motorcycle crashes occurring during the daytime and on the weekend increases the probability of hospitalized injury. The results also suggest that motorcycle crashes occurring during the daytime, in curves or inclined portions of roads, or in unclear weather conditions decrease the probability of fatal injury.

Conclusions: This study provides further empirical evidence to support motorcycle crash modeling research, which is lacking in developing countries. The ability to understand the various factors that influence motorcycle crash severity is a step forward in providing an appropriate basis upon which informed motorcycle crash policies can be developed. Particular attention should be given to the provision of road signage at junctions and speed humps and controlling traffic during the weekend. In addition, road maintenance should be carried out periodically to address motorcycle safety in Ghana.     

Suicide by crashing into a heavy vehicle: Focus on professional drivers using in-depth crash data

Objective: Road traffic suicides typically involve a passenger car driver crashing his or her vehicle into a heavy vehicle, because death is almost certain due to the large mass difference between these vehicles. For the same reason, heavy-vehicle drivers typically suffer minor injuries, if any, and have thus received little attention in the research literature. In this study, we focused on heavy-vehicle drivers who were involved as the second party in road suicides in Finland.

Methods: We analyzed 138 road suicides (2011–2016) involving a passenger car crashing into a heavy vehicle. We used in-depth road crash investigation data from the Finnish Crash Data Institute.

Results: The results showed that all but 2 crashes were head-on collisions. Almost 30% of truck drivers were injured, but only a few suffered serious injuries. More than a quarter reported sick leave following their crash. Injury insurance compensation to heavy-vehicle drivers was just above €9,000 on average. Material damage to heavy vehicles was significant, with average insurance compensation paid being €70,500. Three out of 4 truck drivers reported that drivers committing suicide acted abruptly and left them little opportunity for preventive action.

Conclusions: Suicides by crashing into heavy vehicles can have an impact on drivers’ well-being; however, it is difficult to see how heavy-vehicle drivers could avoid a suicide attempt involving their vehicle.     

Reliability and validity of the Multidimensional Driving Style Inventory in Chinese drivers

Objective: The Multidimensional Driving Style Inventory (MDSI) has been widely used in assessing the associations between driving styles and traffic violations and accidents in different cultural contexts. Due to the lack of a valid instrument to assess driving style, studies concerning driving style and its influence factors are limited in China. Thus, this study aimed to adapt and validate a Chinese version of the MDSI.

Methods: Seven hundred and sixty drivers aged from 19 to 60 years old were asked to complete the MDSI and a personality scale (trait anger, sensation seeking, altruism, and normlessness). Exploratory factory analysis (EFA) and confirmatory factor analysis (CFA) were used to obtain the factorial structure of the MDSI. The external validity of the MDSI was then evaluated by examining the associations between driving styles and personality traits, demographic variables, and traffic violations and crashes.

Results: EFA revealed a 6-factor structure of the MDSI (i.e., risky, anxious, angry, distress reduction, careful, and dissociative driving styles). CFA confirmed that the model fit of the MDSI was acceptable. The MDSI factors were moderately or weakly correlated with trait anger, sensation seeking, altruism, and normlessness. Significant gender and age differences in driving styles were found. Moreover, drivers who had traffic violations or crashes in the past year scored higher on risky and angry driving styles and lower on careful driving style than those who had not have traffic violations or crashes.

Conclusions: The Chinese version of the MDSI proved to be a reliable, valid, and highly useful instrument. It could be used to assess Chinese drivers who are at risk due to their maladaptive driving styles.     

Driving anger among motor vehicle drivers in China: A cross-sectional survey

Objective: Driving anger is a common emotion while driving and has been associated with traffic crashes. This study aimed to investigate situations that increase driving anger among Chinese drivers.

Methods: A cross-sectional study was conducted among 3,101 drivers in southern China. The translated version of the 33-item Driving Anger Scale (DAS) was used to measure driving anger. Data were collected by face-to-face interviews between June 2016 and September 2016.

Results: Confirmatory factor analysis showed that the fit of the original 6-factor model (discourtesy, traffic obstacles, hostile gestures, slow driving, illegal driving, and police presence) was satisfactory, after removing 2 items and allowing 5 error pairs to covary. The model showed satisfactory fit: goodness of fit index (GFI) = 0.90, incremental fit index (IFI) = 0.90, root mean square error of approximation (RMSEA) = 0.06, 90% confidence interval (CI) = 0.061–0.064. Driving anger among Chinese drivers was lower than that in some Western countries. Compared to older and experienced drivers, younger and new drivers were more likely to report driving anger. There was no difference in total reported driving anger between males and females. Additionally, the higher the driver’s anger level was, the more likely he or she was to have had a traffic crash.

Conclusion: Driving anger is a common emotion among Chinese drivers and has a strong correlation with aggressive driving behavior and traffic crashes.     

Driving while impaired by alcohol: An analysis of drink-drivers involved in UK collisions

Objective: Drink-driving represents a critical issue on international organizations’ agendas as one of the key behavioral risk factors in road traffic safety, alongside speed and nonuse of motorcycle helmets, seat belts, and child restraints. Changing road user behaviors regarding these 5 factors is a critical component in reducing road traffic injuries and casualties. The objective of this study is the identification of drivers who are more likely to contribute to crashes in the UK while impaired by alcohol to design targeted drink drive compliance campaigns.

Method: To profile drivers with the factor “impaired by alcohol” assigned in collisions, an extensive data set is used, including all reported injury collisions between 2011 and 2015 in the UK (police records), merged with the Experian Mosaic Database. A multilevel mixed-effects logistic regression is conducted, utilizing the hierarchical nature of the data (drivers within Mosaic types).

Results: Using multilevel mixed-effects logistic regression analysis, the finding is that some driver profiles are more likely to contribute to crashes and are assigned the contributory factor “impaired by alcohol.” Drink-related crashes are more common in some circumstances or for some crash-involved driver groups than others. For instance, alcohol-related crashes are more likely to occur on single carriageways and among males and 25- to 35-year-olds. Drink-drive-related crashes are found to be strongly associated with dark lighting conditions and, more specifically, with late night hours (the interval between 3:00 a.m. and 4:00 a.m. accounts for a third of the drink-drive-related collisions). Using the Experian Mosaic Database which divides the UK population into 66 types based on demographic, lifestyle, and behavior characteristics, the finding is that, among crash-involved drivers, some Mosaic types are significantly more likely (e.g., pocket pensions, dependent greys, streetwise singles) and others are significantly less likely (e.g., crowded kaleidoscope, cultural comfort, penthouse chic) to contribute to a drink-related crash.

Conclusions: The outcome is a more nuanced understanding of drivers contributing to drink-related crashes in the UK. The study concludes by discussing the implications for governments and other interested bodies for better targeting and delivery of public education campaigns and interventions.