Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

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.

On the significance of omitted variables in intersection crash modeling

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causes and contributing factors—rest upon the pursuit of numerous lines of research inquiry. The research community has focused considerable attention on analytical methods development (negative binomial models, 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 logically seek to know which lines of inquiry might provide the most significant improvements in understanding crash causation and/or prediction. It is the contention of this paper that the exclusion of important variables (causal or surrogate measures of causal variables) cause omitted variable bias in model estimation and is an important and neglected line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant opportunities to better understand contributing factors and/or causes of crashes. This study examines the role of important variables (other than Average Annual Daily Traffic (AADT)) that are generally omitted from intersection crash prediction models. In addition to the geometric and traffic regulatory information of intersection, the proposed model includes many spatial factors such as local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools—representing a mix of potential environmental and human factors that are theoretically important, but rarely used. Results suggest that these variables in addition to AADT have significant explanatory power, and their exclusion leads to omitted variable bias. Provided is evidence that variable exclusion overstates the effect of minor road AADT by as much as 40% and major road AADT by 14%.

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

The role of cultural beliefs in contributing to risky road use behaviour in Pakistan

Background Pakistan has the highest population rate of road fatalities in South Asia (25.3 fatalities per 100,000 people: Global Status Report on Road Safety, WHO 2009). Along with road environment and vehicle factors, human factors make a substantial contribution to traffic safety in Pakistan. Beliefs about road crash causation and prevention have been demonstrated to contribute to risky road use behaviour and resistance to preventive measures in a handful of other developing countries, but has not been explored in Pakistan. In particular, fatalism (whether based on religion, other cultural beliefs or experience) has been highlighted as a barrier to achieving changes in attitudes and behaviour. Aims The research reported here aimed (i) to explore perceptions of road crash causation among policy makers, police officers, professional drivers and car drivers in Pakistan; (ii) to identify how cultural and religious beliefs influence road use behaviour in Pakistan; and (iii) to understand how fatalistic beliefs may work as obstacles to road safety interventions. Methods In-depth interviews were conducted by the primary author (mostly in Urdu) in Lahore, Rawalpindi and Islamabad with 12 professional drivers (taxi, bus and truck), 4 car drivers, 6 police officers, 4 policy makers and 2 religious orators. All but two were Muslim, two were female, and they were drawn from a wide range of ages (24 to 60) and educational backgrounds. The interviews were taped and transcribed, then translated into English and analysed for themes related to the aims. Results Fatalism emerged as a pervasive belief utilised to justify risky road use behaviour and to resist messages about preventive measures. There was a strong religious underpinning to the statement of fatalistic beliefs (this reflects popular conceptions of Islam rather than scholarly interpretations), but also an overlap with superstitious beliefs which have longer-standing roots in Pakistani culture. These beliefs were not limited to people of poor educational background or position. A particular issue which was explored in more detail was the way in which these beliefs and their interpretation within Pakistani society contributed to poor police reporting of crashes. Discussion and conclusions The pervasive nature of fatalistic beliefs in Pakistan affects road user behaviour by supporting continued risk taking behaviour on the road, and by interfering with public health messages about behaviours which would reduce the risk of traffic crashes. The widespread influence of these beliefs on the ways that people respond to traffic crashes and the death of family members contribute to low crash reporting rates and to a system which is difficult to change. The promotion of an evidence-based approach to road user behaviour is recommended, along with improved professional education for police and policy makers.

Fatalism, superstition, religion, and culture : road user beliefs and behaviour in Pakistan

Road traffic crashes have emerged as a major health problem around the world. Road crash fatalities and injuries have been reduced significantly in developed countries, but they are still an issue in low and middle-income countries. The World Health Organization (WHO, 2009) estimates that the death toll from road crashes in low- and middle-income nations is more than 1 million people per year, or about 90% of the global road toll, even though these countries only account for 48% of the world's vehicles. Furthermore, it is estimated that approximately 265,000 people die every year in road crashes in South Asian countries and Pakistan stands out with 41,494 approximately deaths per year. Pakistan has the highest rate of fatalities per 100,000 population in the region and its road crash fatality rate of 25.3 per 100,000 population is more than three times that of Australia's. High numbers of road crashes not only cause pain and suffering to the population at large, but are also a serious drain on the country's economy, which Pakistan can ill-afford. Most studies identify human factors as the main set of contributing factors to road crashes, well ahead of road environment and vehicle factors. In developing countries especially, attention and resources are required in order to improve things such as vehicle roadworthiness and poor road infrastructure. However, attention to human factors is also critical. Human factors which contribute to crashes include high risk behaviours like speeding and drink driving, and neglect of protective behaviours such as helmet wearing and seat belt wearing. Much research has been devoted to the attitudes, beliefs and perceptions which contribute to these behaviours and omissions, in order to develop interventions aimed at increasing safer road use behaviours and thereby reducing crashes. However, less progress has been made in addressing human factors contributing to crashes in developing countries as compared to the many improvements in road environments and vehicle standards, and this is especially true of fatalistic beliefs and behaviours. This is a significant omission, since in different cultures in developing countries there are strong worldviews in which predestination persists as a central idea, i.e. that one's life (and death) and other events have been mapped out and are predetermined. Fatalism refers to a particular way in which people regard the events that occur in their lives, usually expressed as a belief that an individual does not have personal control over circumstances and that their lives are determined through a divine or powerful external agency (Hazen & Ehiri, 2006). These views are at odds with the dominant themes of modern health promotion movements, and present significant challenges for health advocates who aim to avert road crashes and diminish their consequences. The limited literature on fatalism reveals that it is not a simple concept, with religion, culture, superstition, experience, education and degree of perceived control of one's life all being implicated in accounts of fatalism. One distinction in the literature that seems promising is the distinction between empirical and theological fatalism, although there are areas of uncertainty about how well-defined the distinction between these types of fatalism is. Research into road safety in Pakistan is scarce, as is the case for other South Asian countries. From the review of the literature conducted, it is clear that the descriptions given of the different belief systems in developing countries including Pakistan are not entirely helpful for health promotion purposes and that further research is warranted on the influence of fatalism, superstition and other related beliefs in road safety. Based on the information available, a conceptual framework is developed as a means of structuring and focusing the research and analysis. The framework is focused on the influence of fatalism, superstition, religion and culture on beliefs about crashes and road user behaviour. Accordingly, this research aims to provide an understanding of the operation of fatalism and related beliefs in Pakistan to assist in the development and implementation of effective and culturally appropriate interventions. The research examines the influence of fatalism, superstition, religious and cultural beliefs on risky road use in Pakistan and is guided by three research questions: 1. What are the perceptions of road crash causation in Pakistan, in particular the role of fatalism, superstition, religious and cultural beliefs? 2. How does fatalism, superstition, and religious and cultural beliefs influence road user behaviour in Pakistan? 3. Do fatalism, superstition, and religious and cultural beliefs work as obstacles to road safety interventions in Pakistan? To address these questions, a qualitative research methodology was developed. The research focused on gathering data through individual in-depth interviewing using a semi-structured interview format. A sample of 30 participants was interviewed in Pakistan in the cities of Lahore, Rawalpindi and Islamabad. The participants included policy makers (with responsibility for traffic law), experienced police officers, religious orators, professional drivers (truck, bus and taxi) and general drivers selected through a combination of purposive, criterion and snowball sampling. The transcripts were translated from Urdu and analysed using a thematic analysis approach guided by the conceptual framework. The findings were divided into four areas: attribution of crash causation to fatalism; attribution of road crashes to beliefs about superstition and malicious acts; beliefs about road crash causation linked to popular concepts of religion; and implications for behaviour, safety and enforcement. Fatalism was almost universally evident, and expressed in a number of ways. Fate was used to rationalise fatal crashes using the argument that the people killed were destined to die that day, one way or another. Related to this was the sense of either not being fully in control of the vehicle, or not needing to take safety precautions, because crashes were predestined anyway. A variety of superstitious-based crash attributions and coping methods to deal with road crashes were also found, such as belief in the role of the evil eye in contributing to road crashes and the use of black magic by rivals or enemies as a crash cause. There were also beliefs related to popular conceptions of religion, such as the role of crashes as a test of life or a source of martyrdom. However, superstitions did not appear to be an alternative to religious beliefs. Fate appeared as the 'default attribution' for a crash when all other explanations failed to account for the incident. This pervasive belief was utilised to justify risky road use behaviour and to resist messages about preventive measures. There was a strong religious underpinning to the statement of fatalistic beliefs (this reflects popular conceptions of Islam rather than scholarly interpretations), but also an overlap with superstitious and other culturally and religious-based beliefs which have longer-standing roots in Pakistani culture. A particular issue which is explored in more detail is the way in which these beliefs and their interpretation within Pakistani society contributed to poor police reporting of crashes. The pervasive nature of fatalistic beliefs in Pakistan affects road user behaviour by supporting continued risk taking behaviour on the road, and by interfering with public health messages about behaviours which would reduce the risk of traffic crashes. The widespread influence of these beliefs on the ways that people respond to traffic crashes and the death of family members contribute to low crash reporting rates and to a system which appears difficult to change. Fate also appeared to be a major contributing factor to non-reporting of road crashes. There also appeared to be a relationship between police enforcement and (lack of) awareness of road rules. It also appears likely that beliefs can influence police work, especially in the case of road crash investigation and the development of strategies. It is anticipated that the findings could be used as a blueprint for the design of interventions aimed at influencing broad-spectrum health attitudes and practices among the communities where fatalism is prevalent. The findings have also identified aspects of beliefs that have complex social implications when designing and piloting driver intervention strategies. By understanding attitudes and behaviours related to fatalism, superstition and other related concepts, it should be possible to improve the education of general road users, such that they are less likely to attribute road crashes to chance, fate, or superstition. This study also underscores the understanding of this issue in high echelons of society (e.g., policy makers, senior police officers) as their role is vital in dispelling road users' misconceptions about the risks of road crashes. The promotion of an evidence or scientifically-based approach to road user behaviour and road safety is recommended, along with improved professional education for police and policy makers.

Self-reported circumstances and consequences of driving while sleepy

Driver surveys are indispensable sources of information when estimating the role of sleepiness in crash causation. The purpose of the study was to (1) identify the prevalence of driving while sleepy among Finnish drivers, (2) determine the circumstances of such instances, and (3) identify risk factors and risk groups. Survey data were collected from a representative sample of active Finnish drivers (N = 1121). One-fifth of the drivers (19.5%) reported having fallen asleep at the wheel during their driving career, with 15.9% reporting having been close to falling asleep or having difficulty staying awake when driving during the previous twelve months. Epworth Sleepiness Scale scores were found to be associated with both types of sleepiness-related driving instances, while sleep quality was associated only with the latter. Compared to women, men more often reported falling asleep at the wheel; the differences were somewhat smaller with respect to fighting sleep while driving during the previous twelve months. The reported discrepancy in sleepiness-related instances (high prevalence of fighting sleep while driving during the previous twelve months and lower proportion of actually falling asleep) identifies young men (⩽25 years) as one of the main target groups for safety campaigns. Approximately three-quarters of drivers who had fallen asleep while driving reported taking action against falling asleep before it actually happened. Furthermore, almost all drivers who had fallen asleep while driving offered at least one logical reason that could have contributed to their falling asleep. These data indicate some degree of awareness about driving while sleepy and of the potential pre-trip factors that could lead to sleepiness while driving, and supports the notion that falling asleep at the wheel does not come as a (complete) surprise to the driver.

Real-World Performance of Longitudinal Barriers Struck by Large Trucks

Outside of relatively limited crash testing with large trucks, very little is known regarding the performance of traffic barriers subjected to real-world large truck impacts. The purpose of this study was to investigate real-world large truck impacts into traffic barriers to determine barrier crash involvement rates, the impact performance of barriers not specifically designed to redirect large trucks, and the real-world performance of large-truck-specific barriers. Data sources included the Fatality Analysis Reporting System (2000-2009), the General Estimates System (2000-2009) and 155 in-depth large truck-to-barrier crashes from the Large Truck Crash Causation Study. Large truck impacts with a longitudinal barrier were found to comprise 3 percent of all police-reported longitudinal barrier impacts and roughly the same proportion of barrier fatalities. Based on a logistic regression model predicting barrier penetration, large truck barrier penetration risk was found to increase by a factor of 6 for impacts with barriers designed primarily for passenger vehicles. Although large-truck-specific barriers were found to perform better than non-heavy vehicle specific barriers, the penetration rate of these barriers were found to be 17 percent. This penetration rate is especially a concern because the higher test level barriers are designed to protect other road users, not the occupants of the large truck. Surprisingly, barriers not specifically designed for large truck impacts were found to prevent large truck penetration approximately half of the time. This suggests that adding costlier higher test level barriers may not always be warranted, especially on roadways with lower truck volumes.

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

A probability-based approach for assessing the relationship between crash accidents and pavement properties

Skid resistance is a condition parameter characterising the contribution that a road makes to the friction between a road surface and a vehicle tyre. Studies of traffic crash histories around the world have consistently found that a disproportionate number of crashes occur where the road surface has a low level of surface friction and/or surface texture, particularly when the road surface is wet. Various research results have been published over many years and have tried to quantify the influence of skid resistance on accident occurrence and to characterise a correlation between skid resistance and accident frequency. Most of the research studies used simple statistical correlation methods in analysing skid resistance and crash data.----- ------ Preliminary findings of a systematic and extensive literature search conclude that there is rarely a single causation factor in a crash. Findings from research projects do affirm various levels of correlation between skid resistance and accident occurrence. Studies indicate that the level of skid resistance at critical places such as intersections, curves, roundabouts, ramps and approaches to pedestrian crossings needs to be well maintained.----- ----- Management of risk is an integral aspect of the Queensland Department of Main Roads (QDMR) strategy for managing its infrastructure assets. The risk-based approach has been used in many areas of infrastructure engineering. However, very limited information is reported on using risk-based approach to mitigate crash rates related to road surface. Low skid resistance and surface texture may increase the risk of traffic crashes.----- ----- The objectives of this paper are to explore current issues of skid resistance in relation to crashes, to provide a framework of probability-based approach to be adopted by QDMR in assessing the relationship between crash accidents and pavement properties, and to explain why the probability-based approach is a suitable tool for QDMR in order to reduce accident rates due to skid resistance.

Stock Markets and Household Wealth: Can a Stock Market Crash Cause a Recession in The U.S. Economy?

Stock market wealth effects on the level of consumption in the United States economy have been constantly debated; there is evidence for arguments for and against its prominence and its symmetry. This paper seeks to investigate the strength of its negative effect by creating models to analyze unexpected shocks to the Standard and Poor's 500 index. First, a transmission mechanism between the stock market and GDP is established through the use of second-order vector autoregressive models. Following which, theory from the life cycle model and adaptations of previous researchers' models are used to create a structural model. This paper finds that stock market wealth effects are small, but important to consider, especially if markets are overpriced; this claim is corroborated by evidence from simulation of 'alternative scenarios' and the historical experiences of 1987 and 2001.

Examining the Alliance-Outcome Relationship: Reverse Causation, Third Variables, and Treatment Phase Artifacts

Psychotherapy research reveals consistent associations between therapeutic alliance and treatment outcomes in the youth and adult literatures. Despite these consistent findings, prospective associations are not sufficient to support the claim that the alliance is a change mechanism in psychotherapy. The current study examined the direction of effect of the alliance- outcome relationship, the contribution of early symptom change in treatment to the development of therapeutic alliance, and the potential for pretreatment interpersonal functioning characteristics to be third variables that account for the association between alliance and outcome. Participants were adolescents with depression and a history of interpersonal trauma that presented to a community mental health center for treatment. Findings demonstrated that a more positive therapeutic alliance predicted greater subsequent symptom improvement, even after removing symptom change occurring before the measurement of alliance. Results also suggested that early change only slightly contributed to alliance development. Finally, though pretreatment interpersonal functioning was related to the first session alliance, these pretreatment client characteristics were not related to later alliance or symptom change. Overall, results provided some support for therapeutic alliance as a mechanism of change in psychotherapy. Methodological and clinical issues are discussed.

Expert systems for crash data collection.

Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

Crash protection systems for handicapped school and transit bus occupants. Volume I: executive summary. Interim report.

National Highway Traffic Safety Administration, Washington, D.C.