Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

Screening to identify large truck potential blackspots : methodological issues and concerns

1. Overview of hotspot identification (HSID)methods 2. Challenges with HSID 3. Bringing crash severity into the ‘mix’ 4. Case Study: Truck Involved Crashes in Arizona 5. Conclusions • Heavy duty trucks have different performance envelopes than passenger cars and have more difficulty weaving, accelerating, and braking • Passenger vehicles have extremely limited sight distance around trucks • Lane and shoulder widths affect truck crash risk more than passenger cars • Using PDOEs to model truck crashes results in a different set of locations to examine for possible engineering and behavioral problems • PDOE models point to higher societal cost locations, whereas frequency models point to higher crash frequency locations • PDOE models are less sensitive to unreported crashes • PDOE models are a great complement to existing practice

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.

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.

Large-scale interlaboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

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.

The Australian naturalistic driving study: From beginnings to launch

The Australian Naturalistic Driving Study (ANDS), a ground-breaking study of Australian driver behaviour and performance, was officially launched on April 21st, 2015 at UNSW. The ANDS project will provide a realistic perspective on the causes of vehicle crashes and near miss crash events, along with the roles speeding, distraction and other factors have on such events. A total of 360 volunteer drivers across NSW and Victoria - 180 in NSW and 180 in Victoria - will be monitored by a Data Acquisition System (DAS) recording continuously for 4 months their driving behaviour using a suite of cameras and sensors. Participants’ driving behaviour (e.g. gaze), the behaviour of their vehicle (e.g. speed, lane position) and the behaviour of other road users with whom they interact in normal and safety-critical situations will be recorded. Planning of the ANDS commenced over two years ago in June 2013 when the Multi-Institutional Agreement for a grant supporting the equipment purchase and assembly phase was signed by parties involved in this large scale $4 million study (5 university accident research centres, 3 government regulators, 2 third party insurers and 2 industry partners). The program’s second development phase commenced a year later in June 2014 after a second grant was awarded. This paper presents an insider's view into that two year process leading up to the launch, and outlines issues that arose in the set-up phase of the study and how these were addressed. This information will be useful to other organisations considering setting up an NDS.

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.

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.

Illegal street racing and associated (hooning) behaviours

In an Australian context, the term hooning refers to risky driving behaviours such as illegal street racing and speed trials, as well as behaviours that involve unnecessary noise and smoke, which include burn outs, donuts, fish tails, drifting and other skids. Hooning receives considerable negative media attention in Australia, and since the 1990s all Australian jurisdictions have implemented vehicle impoundment programs to deal with the problem. However, there is limited objective evidence of the road safety risk associated with hooning behaviours. Attempts to estimate the risk associated with hooning are limited by official data collection and storage practices, and the willingness of drivers to admit to their illegal behaviour in the event of a crash. International evidence suggests that illegal street racing is associated with only a small proportion of fatal crashes; however, hooning in an Australian context encompasses a broader group of driving behaviours than illegal street racing alone, and it is possible that the road safety risks will differ with these behaviours. There is evidence from North American jurisdictions that vehicle impoundment programs are effective for managing drink driving offenders, and drivers who continue to drive while disqualified or suspended both during and post-impoundment. However, these programs used impoundment periods of 30 – 180 days (depending on the number of previous offences). In Queensland the penalty for a first hooning offence is 48 hours, while the vehicle can be impounded for up to 3 months for a second offence, or permanently for a third or subsequent offence within three years. Thus, it remains unclear whether similar effects will be seen for hooning offenders in Australia, as no evaluations of vehicle impoundment programs for hooning have been published. To address these research needs, this program of research consisted of three complementary studies designed to: (1) investigate the road safety implications of hooning behaviours in terms of the risks associated with the specific behaviours, and the drivers who engage in these behaviours; and (2) assess the effectiveness of current approaches to dealing with the problem; in order to (3) inform policy and practice in the area of hooning behaviour. Study 1 involved qualitative (N = 22) and quantitative (N = 290) research with drivers who admitted engaging in hooning behaviours on Queensland roads. Study 2 involved a systematic profile of a large sample of drivers (N = 834) detected and punished for a hooning offence in Queensland, and a comparison of their driving and crash histories with a randomly sampled group of Queensland drivers with the same gender and age distribution. Study 3 examined the post-impoundment driving behaviour of hooning offenders (N = 610) to examine the effects of vehicle impoundment on driving behaviour. The theoretical framework used to guide the research incorporated expanded deterrence theory, social learning theory, and driver thrill-seeking perspectives. This framework was used to explore factors contributing to hooning behaviours, and interpret the results of the aspects of the research designed to explore the effectiveness of vehicle impoundment as a countermeasure for hooning. Variables from each of the perspectives were related to hooning measures, highlighting the complexity of the behaviour. This research found that the road safety risk of hooning behaviours appears low, as only a small proportion of the hooning offences in Study 2 resulted in a crash. However, Study 1 found that hooning-related crashes are less likely to be reported than general crashes, particularly when they do not involve an injury, and that higher frequencies of hooning behaviours are associated with hooning-related crash involvement. Further, approximately one fifth of drivers in Study 1 reported being involved in a hooning-related crash in the previous three years, which is comparable to general crash involvement among the general population of drivers in Queensland. Given that hooning-related crashes represented only a sub-set of crash involvement for this sample, this suggests that there are risks associated with hooning behaviour that are not apparent in official data sources. Further, the main evidence of risk associated with the behaviour appears to relate to the hooning driver, as Study 2 found that these drivers are likely to engage in other risky driving behaviours (particularly speeding and driving vehicles with defects or illegal modifications), and have significantly more traffic infringements, licence sanctions and crashes than drivers of a similar (i.e., young) age. Self-report data from the Study 1 samples indicated that Queensland’s vehicle impoundment and forfeiture laws are perceived as severe, and that many drivers have reduced their hooning behaviour to avoid detection. However, it appears that it is more common for drivers to have simply changed the location of their hooning behaviour to avoid detection. When the post-impoundment driving behaviour of the sample of hooning offenders was compared to their pre-impoundment behaviour to examine the effectiveness of vehicle impoundment in Study 3, it was found that there was a small but significant reduction in hooning offences, and also for other traffic infringements generally. As Study 3 was observational, it was not possible to control for extraneous variables, and is, therefore, possible that some of this reduction was due to other factors, such as a reduction in driving exposure, the effects of changes to Queensland’s Graduated Driver Licensing scheme that were implemented during the study period and affected many drivers in the offender sample due to their age, or the extension of vehicle impoundment to other types of offences in Queensland during the post-impoundment period. However, there was a protective effect observed, in that hooning offenders did not show the increase in traffic infringements in the post period that occurred within the comparison sample. This suggests that there may be some effect of vehicle impoundment on the driving behaviour of hooning offenders, and that this effect is not limited to their hooning driving behaviour. To be more confident in these results, it is necessary to measure driving exposure during the post periods to control for issues such as offenders being denied access to vehicles. While it was not the primary aim of this program of research to compare the utility of different theoretical perspectives, the findings of the research have a number of theoretical implications. For example, it was found that only some of the deterrence variables were related to hooning behaviours, and sometimes in the opposite direction to predictions. Further, social learning theory variables had stronger associations with hooning. These results suggest that a purely legal approach to understanding hooning behaviours, and designing and implementing countermeasures designed to reduce these behaviours, are unlikely to be successful. This research also had implications for policy and practice, and a number of recommendations were made throughout the thesis to improve the quality of relevant data collection practices. Some of these changes have already occurred since the expansion of the application of vehicle impoundment programs to other offences in Queensland. It was also recommended that the operational and resource costs of these laws should be compared to the road safety benefits in ongoing evaluations of effectiveness to ensure that finite traffic policing resources are allocated in a way that produces maximum road safety benefits. However, as the evidence of risk associated with the hooning driver is more compelling than that associated with hooning behaviour, it was argued that the hooning driver may represent the better target for intervention. Suggestions for future research include ongoing evaluations of the effectiveness of vehicle impoundment programs for hooning and other high-risk driving behaviours, and the exploration of additional potential targets for intervention to reduce hooning behaviour. As the body of knowledge regarding the factors contributing to hooning increases, along with the identification of potential barriers to the effectiveness of current countermeasures, recommendations for changes in policy and practice for hooning behaviours can be made.

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.

Large eddy simulation of smoke flow in a real road tunnel fire using FDS

Numerical study is carried out using large eddy simulation to study the heat and toxic gases released from fires in real road tunnels. Due to disasters about tunnel fires in previous decade, it attracts increasing attention of researchers to create safe and reliable ventilation designs. In this research, a real tunnel with 10 MW fire (which approximately equals to the heat output speed of a burning bus) at the middle of tunnel is simulated using FDS (Fire Dynamic Simulator) for different ventilation velocities. Carbone monoxide concentration and temperature vertical profiles are shown for various locations to explore the flow field. It is found that, with the increase of the longitudinal ventilation velocity, the vertical profile gradients of CO concentration and smoke temperature were shown to be both reduced. However, a relatively large longitudinal ventilation velocity leads to a high similarity between the vertical profile of CO volume concentration and that of temperature rise.

Visibility-related characteristics of crashes involving bicyclists and motor vehicles – Responses from an online questionnaire study

Bicyclists are among the most vulnerable of road users, with high fatal crash rates. Although visibility aids have been widely advocated to help prevent bicycle-vehicle conflicts, to date no study has investigated, among crash-involved cyclists, the kind of visibility aids they were using at the time of the crash. This study undertook a detailed investigation of visibility factors involved in bicyclist-motor-vehicle crashes. We surveyed 184 bicyclists (predominantly from Australia via internet cycling forums) who had been involved in motor vehicle collisions regarding the perceived cause of the collision, ambient weather and general visibility, as well as the clothing and bicycle lights used by the bicyclist. Over a third of the crashes occurred in low light levels (dawn, dusk or night-time), which is disproportionate given that only a small proportion of bicyclists typically ride at these times. Importantly, 19% of these bicyclists reported not using bicycle lights at the time of the crash, and only 34% were wearing reflective clothing. Only two participants (of 184) nominated bicyclist visibility as the cause of the crash: 61% attributed the crash to driver inattention. These findings demonstrate that crash-involved bicyclists tend to under-rate and under-utilise visibility aids as a means of improving their safety.

Prevalence of risk factors for undiagnosed obstructive sleep apnoea is high in truck drivers on UK roads

Objectives To determine the prevalence of symptoms and risk factors of obstructive sleep apnoea (OSA) in truck drivers at a UK large truck stop. Methods Over a 5 day period, truck drivers completed a short questionnaire at a major UK ‘truck stop’. The questionnaire asked about OSA rist factors and symptoms, and included the Epworth Sleepiness Scale (ESS). Additionally, measurements of height, weight and collar size were taken. 148 truck drivers participated and within this random group the risk factors of OSA that were looked for were:men age over 40 y, obesity, parge neck circumference, smoking, high ESS and bed partner reporting snoring with witnessed apnoeas. Results Our sample were all men, with 82% aged over 40 y. 47% were obese (compared with 23% for UK men in general) and average neck circumference was 42 cm (compared with 38 cm for UK men in general – Martin et al 1997). 31% smoked (vs 21% for general population), and ESS averaged 2.1 points higher than expected for a healthy population (Johns et al 1997). Snoring was quite evident at 57% (compared wth 40% for men in general) and witnessed apnoeas were almost double (7%) compared with 3.8% given by Ohayon et al (1997) generally for men. Conclusion 8 key symptoms and risk factors of OSA have been found to be prevalent in a sample of truck drivers on UK roads, and to greater extent that for estimates in the general male population. Bed partners of truck drivers reporting witnessed apnoeas strongly suggests this group has a high potential for undiagnosed OSA. OSA sufferers are known to be at high risk of causing road traffi c accidents. This, together with the large size of trucks, then the potential for serious road crashes is great. Truck drivers, especially those who are obese, ought to be a high priority population for OSA screening.