A comparison of the psychological, social, and legal factors contributing to speeding and drink driving behaviour

Within Australia, motor vehicle injury is the leading cause of hospital admissions and fatalities. Road crash data reveals that among the factors contributing to crashes in Queensland, speed and alcohol continue to be overrepresented. While alcohol is the number one contributing factor to fatal crashes, speeding also contributes to a high proportion of crashes. Research indicates that risky driving is an important contributor to road crashes. However, it has been debated whether all risky driving behaviours are similar enough to be explained by the same combination of factors. Further, road safety authorities have traditionally relied upon deterrence based countermeasures to reduce the incidence of illegal driving behaviours such as speeding and drink driving. However, more recent research has focussed on social factors to explain illegal driving behaviours. The purpose of this research was to examine and compare the psychological, legal, and social factors contributing to two illegal driving behaviours: exceeding the posted speed limit and driving when over the legal blood alcohol concentration (BAC) for the drivers licence type. Complementary theoretical perspectives were chosen to comprehensively examine these two behaviours including Akers’ social learning theory, Stafford and Warr’s expanded deterrence theory, and personality perspectives encompassing alcohol misuse, sensation seeking, and Type-A behaviour pattern. The program of research consisted of two phases: a preliminary pilot study, and the main quantitative phase. The preliminary pilot study was undertaken to inform the development of the quantitative study and to ensure the clarity of the theoretical constructs operationalised in this research. Semi-structured interviews were conducted with 11 Queensland drivers recruited from Queensland Transport Licensing Centres and Queensland University of Technology (QUT). These interviews demonstrated that the majority of participants had engaged in at least one of the behaviours, or knew of someone who had. It was also found among these drivers that the social environment in which both behaviours operated, including family and friends, and the social rewards and punishments associated with the behaviours, are important in their decision making. The main quantitative phase of the research involved a cross-sectional survey of 547 Queensland licensed drivers. The aim of this study was to determine the relationship between speeding and drink driving and whether there were any similarities or differences in the factors that contribute to a driver’s decision to engage in one or the other. A comparison of the participants self-reported speeding and self-reported drink driving behaviour demonstrated that there was a weak positive association between these two behaviours. Further, participants reported engaging in more frequent speeding at both low (i.e., up to 10 kilometres per hour) and high (i.e., 10 kilometres per hour or more) levels, than engaging in drink driving behaviour. It was noted that those who indicated they drove when they may be over the legal limit for their licence type, more frequently exceeded the posted speed limit by 10 kilometres per hour or more than those who complied with the regulatory limits for drink driving. A series of regression analyses were conducted to investigate the factors that predict self-reported speeding, self-reported drink driving, and the preparedness to engage in both behaviours. In relation to self-reported speeding (n = 465), it was found that among the sociodemographic and person-related factors, younger drivers and those who score high on measures of sensation seeking were more likely to report exceeding the posted speed limit. In addition, among the legal and psychosocial factors it was observed that direct exposure to punishment (i.e., being detected by police), direct punishment avoidance (i.e., engaging in an illegal driving behaviour and not being detected by police), personal definitions (i.e., personal orientation or attitudes toward the behaviour), both the normative and behavioural dimensions of differential association (i.e., refers to both the orientation or attitude of their friends and family, as well as the behaviour of these individuals), and anticipated punishments were significant predictors of self-reported speeding. It was interesting to note that associating with significant others who held unfavourable definitions towards speeding (the normative dimension of differential association) and anticipating punishments from others were both significant predictors of a reduction in self-reported speeding. In relation to self-reported drink driving (n = 462), a logistic regression analysis indicated that there were a number of significant predictors which increased the likelihood of whether participants had driven in the last six months when they thought they may have been over the legal alcohol limit. These included: experiences of direct punishment avoidance; having a family member convicted of drink driving; higher levels of Type-A behaviour pattern; greater alcohol misuse (as measured by the AUDIT); and the normative dimension of differential association (i.e., associating with others who held favourable attitudes to drink driving). A final logistic regression analysis examined the predictors of whether the participants reported engaging in both drink driving and speeding versus those who reported engaging in only speeding (the more common of the two behaviours) (n = 465). It was found that experiences of punishment avoidance for speeding decreased the likelihood of engaging in both speeding and drink driving; whereas in the case of drink driving, direct punishment avoidance increased the likelihood of engaging in both behaviours. It was also noted that holding favourable personal definitions toward speeding and drink driving, as well as higher levels of on Type-A behaviour pattern, and greater alcohol misuse significantly increased the likelihood of engaging in both speeding and drink driving. This research has demonstrated that the compliance with the regulatory limits was much higher for drink driving than it was for speeding. It is acknowledged that while speed limits are a fundamental component of speed management practices in Australia, the countermeasures applied to both speeding and drink driving do not appear to elicit the same level of compliance across the driving population. Further, the findings suggest that while the principles underpinning the current regime of deterrence based countermeasures are sound, current enforcement practices are insufficient to force compliance among the driving population, particularly in the case of speeding. Future research should further examine the degree of overlap between speeding and drink driving behaviour and whether punishment avoidance experiences for a specific illegal driving behaviour serve to undermine the deterrent effect of countermeasures aimed at reducing the incidence of another illegal driving behaviour. Furthermore, future work should seek to understand the factors which predict engaging in speeding and drink driving behaviours at the same time. Speeding has shown itself to be a pervasive and persistent behaviour, hence it would be useful to examine why road safety authorities have been successful in convincing the majority of drivers of the dangers of drink driving, but not those associated with speeding. In conclusion, the challenge for road safety practitioners will be to convince drivers that speeding and drink driving are equally risky behaviours, with the ultimate goal to reduce the prevalence of both behaviours.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Hotspot Identification: A Full Bayesian Hierarchical Modeling Approach

This study proposes a full Bayes (FB) hierarchical modeling approach in traffic crash hotspot identification. The FB approach is able to account for all uncertainties associated with crash risk and various risk factors by estimating a posterior distribution of the site safety on which various ranking criteria could be based. Moreover, by use of hierarchical model specification, FB approach is able to flexibly take into account various heterogeneities of crash occurrence due to spatiotemporal effects on traffic safety. Using Singapore intersection crash data(1997-2006), an empirical evaluate was conducted to compare the proposed FB approach to the state-of-the-art approaches. Results show that the Bayesian hierarchical models with accommodation for site specific effect and serial correlation have better goodness-of-fit than non hierarchical models. Furthermore, all model-based approaches perform significantly better in safety ranking than the naive approach using raw crash count. The FB hierarchical models were found to significantly outperform the standard EB approach in correctly identifying hotspots.

Not all older adults have insight into their driving abilities : evidence from an on-road assessment and implications for policy

Purpose To compare self-reported driving ability with objective measures of on-road driving performance in a large cohort of older drivers. Methods 270 community-living adults aged 70 – 88 years recruited via the electoral roll completed a standardized assessment of on-road driving performance and questionnaires determining perceptions of their own driving ability, confidence and driving difficulties. Retrospective self-reported crash data over the previous five years were recorded. Results Participants reported difficulty with only selected driving situations, including driving into the sun, in unfamiliar areas, in wet conditions, and at night or dusk. The majority of participants rated their own driving as good to excellent. Of the 47 (17%) of drivers who were rated as potentially unsafe to drive, 66% rated their own driving as good to excellent. Drivers who made critical errors, where the driving instructor had to take control of the vehicle, had no lower self-rating of driving ability then the rest of the group. The discrepancy in self-perceptions of driving and participants’ safety rating on the on-road assessment was significantly associated with self-reported retrospective crash rates, where those drivers who displayed greater overconfidence in their own driving were significantly more likely to report a crash. Conclusions This study demonstrates that older drivers with the greatest mismatch between actual and self-rated driving ability pose the greatest risk to road safety. Therefore licensing authorities should not assume that when older individuals’ driving abilities begin to decline they will necessarily be aware of these changes and adopt appropriate compensatory driving behaviours; rather, it is essential that evidence-based assessments are adopted.

Analysis of traffic injury severity in a mega city of a developing country

Despite a considerable amount of research on traffic injury severities, relatively little is known about the factors influencing traffic injury severity in developing countries, and in particular in Bangladesh. Road traffic crashes are a common headline in daily newspapers of Bangladesh. It has also recorded one of the highest road fatality rates in the world. This research identifies significant factors contributing to traffic injury severity in Dhaka – a mega city and capital of Bangladesh. Road traffic crash data of 5 years from 2007 to 2011 were collected from the Dhaka Metropolitan Police (DMP), which included about 2714 traffic crashes. The severity level of these crashes was documented in a 4-point ordinal scale: no injury (property damage), minor injury, severe injury, and death. An ordered Probit regression model has been estimated to identify factors contributing to injury severities. Results show that night time influence is associated with a higher level injury severity as is for individuals involved in single vehicle crashes. Crashes on highway sections within the city are found to be more injurious than crashes along the arterial and feeder roads. There is a lower likelihood of injury severity, however, if the road sections are monitored and enforced by the traffic police. The likelihood of injuries is lower on two-way traffic arrangements than one-way, and at four-legged intersections and roundabouts compare to road segments. The findings are compared with those from developed countries and the implications of this research are discussed in terms of policy settings for developing countries.

Older drivers' crashes in Queensland, Australia

Background: The growing proportion of older adults in Australia is predicted to comprise 23% of the population by 2030. Accordingly, an increasing number of older drivers and fatal crashes of these drivers could also be expected. While the cognitive and physiological limitations of ageing and their road safety implications have been widely documented, research has generally considered older drivers as a homogeneous group. Knowledge of age-related crash trends within the older driver group itself is currently limited. Objective: The aim of this research was to identify age-related differences in serious road crashes of older drivers. This was achieved by comparing crash characteristics between older and younger drivers and between sub-groups of older drivers. Particular attention was paid to serious crashes (crashes resulting in hospitalisation and fatalities) as they place the greatest burden on the Australian health system. Method: Using Queensland Crash data, a total of 191,709 crashes of all-aged drivers (17–80+) over a 9-year period were analysed. Crash patterns of drivers’ aged 17–24, 25–39, 40–49, 50–59, 60–69, 70–79 and 80+ were compared in terms of crash severity (e.g., fatal), at fault levels, traffic control measures (e.g., stop signs) and road features (e.g., intersections). Crashes of older driver sub-groups (60–69, 70–79, 80+) were also compared to those of middle-aged drivers (40–49 and 50–59 combined, who were identified as the safest driving cohort) with respect to crash-related traffic control features and other factors (e.g., speed). Confounding factors including speed and crash nature (e.g., sideswipe) were controlled for. Results and discussion: Results indicated that patterns of serious crashes, as a function of crash severity, at-fault levels, road conditions and traffic control measures, differed significantly between age groups. As a group, older drivers (60+) represented the greatest proportion of crashes resulting in fatalities and hospitalisation, as well as those involving uncontrolled intersections and failure to give way. The opposite was found for middle-aged drivers, although they had the highest proportion of alcohol and speed-related crashes when compared to older drivers. Among all older drivers, those aged 60–69 were least likely to be involved in or the cause of crashes, but most likely to crash at interchanges and as a result of driving while fatigued or after consuming alcohol. Drivers aged 70–79 represented a mid-range level of crash involvement and culpability, and were most likely to crash at stop and give way signs. Drivers aged 80 years and beyond were most likely to be seriously injured or killed in, and at-fault for, crashes, and had the greatest number of crashes at both conventional and circular intersections. Overall, our findings highlight the heterogeneity of older drivers’ crash patterns and suggest that age-related differences must be considered in measures designed to improve older driver safety.

Under-reporting of road crashes in Pakistan and the role of fate

Objective: Comprehensive, accurate information about road crashes and related trauma is a prerequisite for identification and control of risk factors as well as for identifying faults within the broader road safety system. Quality data and appropriate crash investigation are critical in reducing the road toll that is rapidly growing in much of the developing world, including Pakistan. This qualitative research explored the involvement of social and cultural factors (in particular, fatalism) in risky road use in Pakistan. The findings highlight a significant issue, previously unreported in the road safety literature, namely, the link between fatalistic beliefs and inaccurate reporting of road crashes. Method: Thirty interviews (one-to one) were conducted by the first author with police officers, drivers, policy makers and religious orators in three Pakistani cities. Findings: Evidence emerged of a strong link between fatalism and the under-reporting of road crashes. In many cases, crashes and related road trauma appear to go unreported because a crash is considered to be one’s fate and, therefore, beyond personal control. Fate was also implicated in the practice of reconciliation between parties after a crash without police involvement and the seeking and granting of pardon for a road death. Conclusions: These issues represent additional factors that can contribute to under-reporting of crashes and associated trauma. Together, they highlight complications involved in establishing the true cost of road trauma in a country such as Pakistan and the difficulties faced when attempting to promote scientifically-based road safety information to counteract faith-based beliefs.

Random Breath Testing in Australia: Is there an Optimum Level of Intensity?

Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.

Driver perceptions of the benefits of reducing their driving speed on safety, emissions, and stress and road rage

The existing literature shows driving speed significantly affects levels of safety, emissions, and stress in driving. In addition, drivers who feel tense when driving have been found to drive more slowly than others. These findings were mostly obtained from crash data analyses or field studies, and less is known regarding driver perceptions of the extent to which reducing their driving speed would improve road safety, reduce their car’s emissions, and reduce stress and road rage. This paper uses ordered probit regression models to analyse responses from 3538 Queensland drivers who completed an online RACQ survey. Drivers most strongly agreed that reducing their driving speed would improve road safety, less strongly agreed that reducing their driving speed would reduce their car’s emissions and least strongly agreed that reducing their driving speed would reduce stress and road rage. Younger drivers less strongly agreed that these benefits would occur than older drivers. Drivers of automatic cars and those who are bicycle commuters agreed more to these benefits than other drivers. Female drivers agreed more strongly than males on improving safety and reducing stress and road rage. Type of fuel used, engine size, driving experience, and distance driven per week were also found to be associated with driver perceptions, although these were not found to be significant in all of the regression models. The findings from this study may help in developing targeted training or educational measures to improve drivers’ willingness to reduce their driving speed.

Characteristics of police-reported road traffic crashes in Ethiopia over a six year period

Ethiopia has one of Africa’s fastest growing non-oil producing economies and an increasing level of motorisation (AfDB, OECD, UNDP, & UNECA, 2012). This rapidly increasing mobility has created some unique road safety concerns; however there is scant published information and related commentary (United Nations Economic Commission for Africa, 2009). The objective of this paper is to quantify police-reported traffic crashes in Ethiopia and characterise the existing state of road safety. Six years (July 2005 - June 2011) of police-reported crash data were analysed, consisting of 12,140 fatal and 29,454 injury crashes on the country’s road network. The 12,140 fatal crashes involved 1,070 drivers, 5,702 passengers, and 7,770 pedestrians, totalling 14,542 fatalities, an average of 1.2 road user fatalities per crash. An important and glaring trend that emerges is that more than half of the fatalities in Ethiopia involve pedestrians. The majority of the crashes occur during daytime hours, involve males, and involve persons in the 18-50 age group—Ethiopia’s active workforce. Crashes frequently occur in mid blocks or roadways. The predominant collision between motor vehicles and pedestrians was a rollover on a road tangent section. Failing to observe the priority of pedestrians and speeding were the major causes of crashes attributed by police. Trucks and minibus taxis were involved in the majority of crashes, while automobiles (small vehicles) were less involved in crashes relative to other vehicle types, partially because small vehicles tend to be driven fewer kilometres per annum. These data illustrate and justify a high priority to identify and implement effective programs, policies, and countermeasures focused on reducing pedestrian crashes.

Injury severity of pedestrian crashes in Singapore

Singapore is a highly urbanized city-state country where walking is an important mode of travel. Pedestrians form about 25% of road fatalities every year, making them one of the most vulnerable road user groups in Singapore. Engineering measures like provision of overhead pedestrian crossings and raised zebra crossings tend to address pedestrian safety in general, but there may be occasions where pedestrians are particularly vulnerable so that targeted interventions are more appropriate. The objective of this study is to identify factors and situations that affect the injury severity of pedestrians involved in traffic crashes. Six years of crash data from 2003 to 2008 containing around four thousands pedestrian crashes at roadway segments were analyzed. Injury severity of pedestrians—recorded as slight injury, major injury and fatal—were modeled as a function of roadway characteristics, traffic features, environmental factors and pedestrian demographics by an ordered probit model. Results suggest that the injury severity of pedestrians involved in crashes during night time is higher indicating that pedestrian visibility during night is a key issue in pedestrian safety. The likelihood of fatal or serious injuries is higher for crashes on roads with high speed limit, center and median lane of multi-lane roads, school zones, roads with two-way divided traffic type, and when pedestrians cross the roads. Elderly pedestrians appear to be involved in fatal and serious injury crashes more when they attempt to cross the road without using nearby crossing facilities. Specific countermeasures are recommended based on the findings of this study.

Identifying and characterising crashes of returning riders - a new approach

Surveys have identified that many older motorcyclists are returning riders but it is difficult to draw conclusions about their crash risk because of discrepancies in definitions and the inability to identify returning riders in official crash databases. Analyses of NSW crash data were undertaken in which returning riders were defined as aged 25 and over, holding a full licence 10 years prior to the crash, and not the registered operator of one or more motorcycles during the 5-10 years prior to the crash. Based on this definition, there were 472 riders in casualty crashes in 2005-09 who were returning riders (5.5% of riders aged 25 and over in casualty crashes) and the characteristics of their crashes were similar to those involving continuing riders. In contrast, crashes of new riders were more likely to have characteristics suggestive of relatively more riding in urban areas, probably for transport rather than recreation. More work is recommended to assess the validity of the definition to allow a better understanding of the effects of long periods away from riding on riding skills and crash risk.

How accurate is the identification of serious traffic injuries by Police? The concordance between Police and hospital reported traffic injuries

Police reported crash data are the primary source of crash information in most jurisdictions. However, the definition of serious injury within police-reported data is not consistent across jurisdictions and may not be accurate. With the Australian National Road Safety Strategy targeting the reduction of serious injuries, there is a greater need to assess the accuracy of the methods used to identify these injuries. A possible source of more accurate information relating to injury severity is hospital data. While other studies have compared police and hospital data to highlight the under-reporting in police-reported data, little attention has been given to the accuracy of the methods used by police to identify serious injuries. The current study aimed to assess how accurate the identification of serious injuries is in police-reported crash data, by comparing the profiles of transport-related injuries in the Queensland Road Crash Database with an aligned sample of data from the Queensland Hospital Admitted Patients Data Collection. Results showed that, while a similar number of traffic injuries were recorded in both data sets, the profile of these injuries was different based on gender, age, location, and road user. The results suggest that the ‘hospitalisation’ severity category used by police may not reflect true hospitalisations in all cases. Further, it highlights the wide variety of severity levels within hospitalised cases that are not captured by the current police-reported definitions. While a data linkage study is required to confirm these results, they highlight that a reliance on police-reported serious traffic injury data alone could result in inaccurate estimates of the impact and cost of crashes and lead to a misallocation of valuable resources.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Analysis of traffic injury severity in Dhaka, Bangladesh

This research identifies roadway, traffic, and environmental factors that influence the injury severity of road traffic crashes in Dhaka. Dhaka provides a rather unusual driving risk environment to study, since virtually anyone can obtain a drivers’ license and very little traffic enforcement and fines are given when drivers violate traffic rules. To examine this city with presumed heightened crash severity risk, police reported crash data from 2007 to 2011 containing about 2714 road traffic crashes were collected. The injury severity of traffic crashes—recorded as either fatal, serious injury, or property damage only—were modeled using an ordered Probit model. Significant factors increasing the probability of fatal injuries include crashes along highways (65%), absence of a road divider (80%), crashes during night time (54%), and vehicle-pedestrian collisions (367%); whereas two-way traffic configuration (21%), and traffic police controlled schemes (41%) decrease the probability of fatalities. Both similarities and differences of the findings between crash risk in Dhaka and developed countries are discussed in policy relevant terms.