Enhancing road safety for young drivers : how Graduate Driver Licensing initiatives can complement "anti-hooning" legislation

Street racing and associated (hooning) behaviours have attracted increasing concern in recent years. While New Zealand and all Australian jurisdictions have introduced “antihooning” legislation and allocated significant police resources to managing the problem, there is limited evidence of the road safety implications of hooning. However, international and Australian data suggests that drivers charged with a hooning offence tend to be young males who are accompanied by one or more peers, and hooning-related crashes tend to occur at night. In this regard, there is considerable evidence that drivers under the age of 25 are over-represented in crash statistics, and are particularly vulnerable soon after obtaining a Provisional licence, when driving at night, and when carrying peer-aged passengers. The similarity between the nature of hooning offenders, offences and crashes, and road safety risks for young drivers in general, suggests that hooning is an issue that may be viewed as part of the broader young driver problem. Many jurisdictions have recently implemented a range of evidence-based strategies to address young driver road safety, and this paper will present Queensland crash and offence data to highlight the potential benefit of Graduated Driver Licensing initiatives, such as night driving restrictions and peer-aged passenger restrictions, to related road safety issues, including hooning. An understanding of potential flow-on effects is important for evaluations of anti-hooning legislation and Graduated Driver Licensing programs, and may have implications for future law enforcement resource allocation and policy development.

Crash Risk Assessment with Cooperative Systems

Crash risk is the statistical probability of a crash. Its assessment can be performed through ex post statistical analysis or in real-time with on-vehicle systems. These systems can be cooperative. Cooperative Vehicle-Infrastructure Systems (CVIS) are a developing research avenue in the automotive industry worldwide. This paper provides a survey of existing CVIS systems and methods to assess crash risk with them. It describes the advantages of cooperative systems versus non-cooperative systems. A sample of cooperative crash risk assessment systems is analysed to extract vulnerabilities according to three criteria: market penetration, over-reliance on GPS and broadcasting issues. It shows that cooperative risk assessment systems are still in their infancy and requires further development to provide their full benefits to road users.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

The on-road difficulties of older drivers and their relationship with self-reported motor vehicle crashes

OBJECTIVES: To quantify the driving difficulties of older adults using a detailed assessment of driving performance and to link this with self-reported retrospective and prospective crashes. DESIGN: Prospective cohort study. SETTING: On-road driving assessment. PARTICIPANTS: Two hundred sixty-seven community-living adults aged 70 to 88 randomly recruited through the electoral roll. MEASUREMENTS: Performance on a standardized measure of driving performance. RESULTS: Lane positioning, approach, and blind spot monitoring were the most common error types, and errors occurred most frequently in situations involving merging and maneuvering. Drivers reporting more retrospective or prospective crashes made significantly more driving errors. Driver instructor interventions during self-navigation (where the instructor had to brake or take control of the steering to avoid an accident) were significantly associated with higher retrospective and prospective crashes; every instructor intervention almost doubled prospective crash risk. CONCLUSION: These findings suggest that on-road driving assessment provides useful information on older driver difficulties, with the self-directed component providing the most valuable information.

An investigation into how work-related road safety can be enhanced

Despite the facts that vehicle incidents continue to be the most common mechanism for Australian compensated fatalities and that employers have statutory obligations to provide safe workplaces, very few organisations are proactively and comprehensively managing their work-related road risks. Unfortunately, limited guidance is provided in the existing literature to assist practitioners in managing work-related road risks. The current research addresses this gap in the literature. To explore how work-related road safety can be enhanced, three studies were conducted. Study one explored the effectiveness of a range of risk management initiatives and whether comprehensive risk management practices were associated with safety outcomes. Study two explored barriers to, and facilitators for, accepting risk management initiatives. Study three explored the influence of organisational factors on road safety outcomes to identify optimal work environments for managing road risks. To maximise the research sample and increase generalisability, the studies were designed to allow data collection to be conducted simultaneously drawing upon the same sample obtained from four Australian organisations. Data was collected via four methods. A structured document review of published articles was conducted to identify what outcomes have been observed in previously investigated work-related road safety initiatives. The documents reviewed collectively assessed the effectiveness of 19 work-related road safety initiatives. Audits of organisational practices and process operating within the four researched organisations were conducted to identify whether organisations with comprehensive work-related road risk management practices and processes have better safety outcomes than organisations with limited risk management practices and processes. Interviews were conducted with a sample of 24 participants, comprising 16 employees and eight managers. The interviews were conducted to identify what barriers and facilitators within organisations are involved in implementing work-related road safety initiatives and whether differences in fleet safety climate, stage of change and safety ownership relate to work-related road safety outcomes. Finally, questionnaires were administered to a sample of 679 participants. The questionnaires were conducted to identify which initiatives are perceived by employees to be effective in managing work-related road risks and whether differences in fleet safety climate, stage of change and safety ownership relate to work-related road safety outcomes. Seven research questions were addressed in the current research project. The key findings with respect to each of the research questions are presented below. Research question one: What outcomes have been observed in previously investigated work-related road safety initiatives? The structured document review indicated that initiatives found to be positively associated with occupational road safety both during and after the intervention period included: a pay rise; driver training; group discussions; enlisting employees as community road safety change agents; safety reminders; and group and individual rewards. Research question two: Which initiatives are perceived by employees to be effective in managing work-related road risks? Questionnaire findings revealed that employees believed occupational road risks could best be managed through making vehicle safety features standard, providing practical driver skills training and through investigating serious vehicle incidents. In comparison, employees believed initiatives including signing a promise card commitment to drive safely, advertising the organisation’s phone number on vehicles and consideration of driving competency in staff selection process would have limited effectiveness in managing occupational road safety. Research question three: Do organisations with comprehensive work-related road risk management practices and processes have better safety outcomes than organisations with limited risk management practices and processes? The audit identified a difference among the organisations in their management of work-related road risks. Comprehensive risk management practices were associated with employees engaging in overall safer driving behaviours, committing less driving errors, and experiencing less fatigue and distraction issues when driving. Given that only four organisations participated in this research, these findings should only be considered as preliminary. Further research should be conducted to explore the relationship between comprehensiveness of risk management practices and road safety outcomes with a larger sample of organisations. Research question four: What barriers and facilitators within organisations are involved in implementing work-related road safety initiatives? The interviews identified that employees perceived six organisational characteristics as potential barriers to implementing work-related road safety initiatives. These included: prioritisation of production over safety; complacency towards work-related road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. In comparison, employees perceived three organisational characteristics as potential facilitators to implementing work-related road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Research question five: Do differences in fleet safety climate relate to work-related road safety outcomes? The interviews and questionnaires identified that organisational climates with high management commitment, support for managing work demands, appropriate safety rules and safety communication were associated with employees who engaged in safer driving behaviours. Regression analyses indicated that as participants’ perceptions of safety climate increased, the corresponding likelihood of them engaging in safer driving behaviours increased. Fleet safety climate was perceived to influence road safety outcomes through several avenues. Some of these included: the allocation of sufficient resources to manage occupational road risks; fostering a supportive environment of mutual responsibility; resolving safety issues openly and fairly; clearly communicating to employees that safety is the top priority; and developing appropriate work-related road safety policies and procedures. Research question six: Do differences in stage of change relate to work-related road safety outcomes? The interviews and questionnaires identified that participants’ perceptions of initiative effectiveness were found to vary with respect to their individual stage of readiness, with stage-matched initiatives being perceived most effective. In regards to safety outcomes, regression analyses identified that as participants’ progress through the stages of change, the corresponding likelihood of them being involved in vehicle crashes decreases. Research question seven: Do differences in safety ownership relate to work-related road safety outcomes? The interviews and questionnaires revealed that management of road risks is often given less attention than other areas of health and safety management in organisations. In regards to safety outcomes, regression analyses identified that perceived authority and perceived shared ownership both emerged as significant independent predictors of self-reported driving behaviours pertaining to fatigue and distractions. The regression models indicated that as participants’ perceptions of the authority of the person managing road risks increases, and perceptions of shared ownership of safety tasks increases, the corresponding likelihood of them engaging in driving while fatigued or multitasking while driving decreases. Based on the findings from the current research, the author makes several recommendations to assist practitioners in developing proactive and comprehensive approaches to managing occupational road risks. The author also suggests several avenues for future research in the area of work-related road safety.

Application of text mining in analysing road crashes for road asset management

Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

Barriers to the acceptance of road safety programmes among rural road users : developing a brief intervention

Motorised countries have more fatal road crashes in rural areas than in urban areas. In Australia, over two thirds of the population live in urban areas, yet approximately 55 percent of the road fatalities occur in rural areas (ABS, 2006; Tziotis, Mabbot, Edmonston, Sheehan & Dwyer, 2005). Road and environmental factors increase the challenges of rural driving, but do not fully account for the disparity. Rural drivers are less compliant with recommendations regarding the “fatal four” behaviours of speeding, drink driving, seatbelt non-use and fatigue, and the reasons for their lower apparent receptivity for road safety messages are not well understood. Countermeasures targeting driver behaviour that have been effective in reducing road crashes in urban areas have been less successful in rural areas (FORS, 1995). However, potential barriers to receptivity for road safety information among rural road users have not been systematically investigated. This thesis aims to develop a road safety countermeasure that addresses three areas that potentially affect receptivity to rural road safety information. The first is psychological barriers of road users’ attitudes, including risk evaluation, optimism bias, locus of control and readiness to change. A second area is the timing and method of intervention delivery, which includes the production of a brief intervention and the feasibility of delivering it at a “teachable moment”. The third area under investigation is the content of the brief intervention. This study describes the process of developing an intervention that includes content to address road safety attitudes and improve safety behaviours of rural road users regarding the “fatal four”. The research commences with a review of the literature on rural road crashes, brief interventions, intervention design and implementation, and potential psychological barriers to receptivity. This literature provides a rationale for the development of a brief intervention for rural road safety with a focus on driver attitudes and behaviour. The research is then divided into four studies. The primary aim of Study One and Study Two is to investigate the receptivity of rural drivers to road safety interventions, with a view to identifying barriers to the efficacy of these strategies.

The influence of fatalistic beliefs on risky road use behavior in developing countries

There is little discussion of fatalism in the road safety literature, and limited research. However, fatalism is a potential barrier to participation in health-promoting behaviours, particularly among the populations of developing countries and to some extent in developed countries. Many people still believe in divine discretion and magical powers as causes of road crashes in different parts of the world. Fatalistic beliefs and beliefs in mystical powers and superstition appear to influence perceptions of crash risk and consequently lead people to take risks and neglect safety measures. Fatalistic beliefs may cause individuals to be resigned to risks because they cannot do anything to reduce these risks.

Road safety messages tailored for young adults : Using the Internet and encouraging protective passenger behaviour

Young drivers are at higher risk of crashes than other drivers when carrying passengers. Graduated Driver Licensing has demonstrated effectiveness in reducing fatalities however there is considerable potential for additional strategies to complement the approach. A survey with 276 young adults (aged 17-25 years, 64% females) was conducted to examine the potential and importance of strategies that are delivered via the Internet and potential strategies for passengers. Strategies delivered via the Internet represent opportunity for widespread dissemination and greater reach to young people at times convenient to them. The current study found some significant differences between males and females with regard to ways the Internet is used to obtain road safety information and the components valued in trusted road safety sites. There were also significant differences between males and females on the kinds of strategies used as passengers to promote driver safety and the context in which it occurred, with females tending to take more proactive strategies than males. In sum, young people see value in Internet delivery for passenger safety information (80% agreed/ strongly agreed) and more than 90% thought it was important to intervene while a passenger of a risky driver. Thus tailoring Internet road safety strategies to young people may differ for males and females however there is considerable potential for a passenger focus in strategies aimed at reducing young driver crashes.

Development of accident modification factors on intersection crash maneuvers

In order to estimate the safety impact of roadway interventions engineers need to collect, analyze, and interpret the results of carefully implemented data collection efforts. The intent of these studies is to develop Accident Modification Factors (AMF's), which are used to predict the safety impact of various road safety features at other locations or in upon future enhancements. Models are typically estimated to estimate AMF's for total crashes, but can and should be estimated for crash outcomes as well. This paper first describes data collected with the intent estimate AMF's for rural intersections in the state of Georgia within the United Sates. Modeling results of crash prediction models for the crash outcomes: angle, head-on, rear-end, sideswipe (same direction and opposite direction) and pedestrian-involved crashes are then presented and discussed. The analysis reveals that factors such as the Annual Average Daily Traffic (AADT), the presence of turning lanes, and the number of driveways have a positive association with each type of crash, while the median width and the presence of lighting are negatively associated with crashes. The model covariates are related to crash outcome in different ways, suggesting that crash outcomes are associated with different pre-crash conditions.

Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.

The significance of endogeneity problems in crash models: An examination of left-turn lanes in intersection crash models

Crash prediction models are used for a variety of purposes including forecasting the expected future performance of various transportation system segments with similar traits. The influence of intersection features on safety have been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes compared to other segments in the transportation system. The effects of left-turn lanes at intersections in particular have seen mixed results in the literature. Some researchers have found that left-turn lanes are beneficial to safety while others have reported detrimental effects on safety. This inconsistency is not surprising given that the installation of left-turn lanes is often endogenous, that is, influenced by crash counts and/or traffic volumes. Endogeneity creates problems in econometric and statistical models and is likely to account for the inconsistencies reported in the literature. This paper reports on a limited-information maximum likelihood (LIML) estimation approach to compensate for endogeneity between left-turn lane presence and angle crashes. The effects of endogeneity are mitigated using the approach, revealing the unbiased effect of left-turn lanes on crash frequency for a dataset of Georgia intersections. The research shows that without accounting for endogeneity, left-turn lanes ‘appear’ to contribute to crashes; however, when endogeneity is accounted for in the model, left-turn lanes reduce angle crash frequencies as expected by engineering judgment. Other endogenous variables may lurk in crash models as well, suggesting that the method may be used to correct simultaneity problems with other variables and in other transportation modeling contexts.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Incorporating weather into regionwide safety planning prediction models

Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.