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Purpose – This chapter provides an overview of issues related to analysing crash data characterised by excess zero responses and/or long tails and how to overcome these problems. Factors affecting excess zeros and/or long tails are discussed, as well as how they can bias the results when traditional distributions or models are used. Recently introduced multi-parameter distributions and models developed specifically for such datasets are described. The chapter is intended to guide readers on how to properly analyse crash datasets with excess zeros and long or heavy tails.

Methodology – Key references from the literature are summarised and discussed, and two examples detailing how multi-parameter distributions and models compare with the negative binomial distribution and model are presented.

Findings – In the event that the characteristics of the crash dataset cannot be changed or modified, recently introduced multi-parameter distributions and models can be used efficiently to analyse datasets characterised by excess zero responses and/or long tails. They offer a simpler way to interpret the relationship between crashes and explanatory variables, while providing better statistical performance in terms of goodness-of-fit and predictive capabilities.

Research implications – Multi-parameter models are expected to become the next series of traditional distributions and models. The research on these models is still ongoing.

Practical implications – With the advancement of computing power and Bayesian simulation methods, multi-parameter models can now be easily coded and applied to analyse crash datasets characterised by excess zero responses and/or long tails.

Purpose – The purpose of this chapter is to review the methodological and empirical underpinnings of transport network screening, or management, as it relates to improving road safety. As jurisdictions around the world are charged with transport network management in order to reduce externalities associated with road crashes, identifying potential blackspots or hotspots is an important if not critical function and responsibility of transport agencies.

Methodology – Key references from within the literature are summarised and discussed, along with a discussion of the evolution of thinking around hotspot identification and management. The theoretical developments that correspond with the evolution in thinking are provided, sprinkled with examples along the way.

Findings – Hotspot identification methodologies have evolved considerably over the past 30 or so years, correcting for methodological deficiencies along the way. Despite vast and significant advancements, identifying hotspots remains a reactive approach to managing road safety – relying on crashes to accrue in order to mitigate their occurrence. The most fruitful directions for future research will be in the establishment of reliable relationships between surrogate measures of road safety – such as ‘near misses’ – and actual crashes – so that safety can be proactively managed without the need for crashes to accrue.

Research implications – Research in hotspot identification will continue; however, it is likely to shift over time to both closer to ‘real-time’ crash risk detection and considering safety improvements using surrogate measures of road safety – described in Chapter 17.

Practical implications – There are two types of errors made in hotspot detection – identifying a ‘risky’ site as ‘safe’ and identifying a ‘safe’ site as ‘risky’. In the former case no investments will be made to improve safety, while in the latter case ineffective or inefficient safety improvements could be made. To minimise these errors, transport network safety managers should be applying the current state of the practice methods for hotspot detection. Moreover, transport network safety managers should be eager to transition to proactive methods of network safety management to avoid the need for crashes to occur. While in its infancy, the use of surrogate measures of safety holds significant promise for the future.

Purpose – This chapter highlights main thrusts discussed in the book in its entirety.

Methodology – This chapter reviews the content of the book, drawing together the challenges safety analysts and other important road safety stakeholders confront while trying to understand and reduce transport system risks.

Findings – The chapter describes the challenges the profession is confronting. These challenges include the difficulty in analysing crashes and drawing reliable conclusions when crashes are rare, the complexities involved with piecing together and identifying actual causes of crashes, how driver behaviour is a dominant influence on crash risk, how a diverse mix of road users is challenging to manage, that estimating the safety benefits of treatments is fraught with complexity, how surrogate measures of safety – despite the analytical research needed on their linkages with crashes – can be used for proactively improving design and operational decisions, and how real-time data collected on monitored highways, which need the development of solid theoretical underpinnings moving forward – can be used reliably for estimating crash risks and manage safety. The chapter briefly summarises how these challenges may be addressed moving forward.

The chapter also identifies future research opportunities that can be pursued to further improve safe mobility. These opportunities include the use of alternate methodologies for ‘measuring safety’ such as advanced vision recognition techniques, the use of surrogate measures of safety such as time to collision, driverless and connected vehicles, naturalistic driving experiments and data, the reshaping of urban cities, and the rapid growth and motorisation of developing countries.

Practical implications – By fostering a better understanding of the challenges the profession is facing, and prompting a dialogue on how they can be overcome, will lead to a reduction in the number and severity of crashes of global transport networks, making them more sustainable. The chapter shows how some of these challenges can be tackled.

Originality/value of chapter – This chapter draws from all the chapters of this book that describes various challenges road safety professionals currently face, and directs readers to different parts of the book for more in-depth treatment on how these challenges can be met. The chapter also describes research opportunities where further safety gains can be obtained moving forward.

Purpose – Intersections are hazardous locations and to improve their safety we need to understand the factors contributing to crashes at these locations and provide evidence-based recommendations to reduce them. This chapter provides a summary of the findings on infrastructure-related factors contributing to crashes at urban and rural intersections and some discussions on the implications and potential countermeasures.

Approach – A review of the literature on intersection crashes was performed to identify the infrastructure-related crash-contributing factors. Some discussions on the implications and potential countermeasures are then provided.

Findings – The factors contributing to road crashes are diverse and complex. While the safety effects of a few factors (e.g., exposure and speed) are relatively consistent, many factors have different impacts on crash frequency and severity (e.g., types of intersection) and different impacts on urban and rural intersections (e.g., bus stops).

Research Implications – More studies are needed on developing a stronger theoretical or conceptual foundation on the effects of roadway designs and traffic controls on different dimensions of safety (e.g., exposure, frequency, severity, etc.), types of crashes (e.g., head-on, rear-end, etc.) or road users involved (e.g., drivers, pedestrians, cyclists, etc.).

Practical Implications – Transport engineers need to be aware that some treatments may have different effects on different crash types and road users involved. Even though the overall safety may be improved by the treatments designed, they need to consider and mitigate any unintended consequences to satisfy the Pareto improvement principle and the social equity criterion.

Purpose – This chapter first provides the motivation for writing this book. It then describes the challenges involved with assessing societal safety through the analysis of transport system crashes. It concludes with a summary of the contents of the remainder of the book, identifying how various dimensions of the transport system challenges are addressed.

Methodology/Approach – This chapter discusses important real-world and methodological challenges that practitioners, academics and researchers face in making a more sustainable highway system through a reduction in the number and severity of transport network crashes resulting in fatalities, injuries and property damage.

Findings – The chapter first describes important challenges, such as complexity of the driving task, the challenges of engineering transport systems for humans, unanticipated effects that arise from differences between driver safety and security, the co-mingling of mobility modes of travel, and challenges in evaluating road safety. The chapters are separated into five general themes: driver behaviour, the transportation network, vulnerable road users, methods for understanding and predicting safety performance, and methods for evaluating safety impacts of countermeasures.

Practical Implications – Comprehending the challenges associated with road crashes is a first step in making the roadway system more sustainable. This book provides a broad and understandable description of these challenges and how they can be overcome by academics and practitioners working in transport network safety management.

Originality – This book presents a clear understanding and offers insights about the challenges and potential solutions that can be brought to bear to make a more sustainable and safe transport system, whether it is located in an urban or rural area, and for a wide variety of functional classifications and designs. The topics covered in this book are intended to be useful and applied to tackle transport system management anywhere in the world.

Purpose – Information collected from police crash reports has long been the primary source of data for the analysis of factors that determine the likelihood of a crash (crash frequency) and its resulting severity (measured in terms of the extent of injuries to vehicle occupants). Proper cross-sectional analyses techniques, covered in this chapter, are important for guiding safety policy and countermeasures.

Methodology – This chapter provides an overview of some of the more commonly used cross-sectional statistical and econometric methods, and discusses the nuances and their limitations with regard to how they are applied to typical crash-report data.

Findings – The wide variety of analytic methods available to safety researchers makes the selection of appropriate methods critical. This chapter provides important guidance for safety researchers in their choice of methodological approach.

Implications – Understanding the importance of proper model specification, unobserved heterogeneity, endogeneity and other factors covered in this chapter is extremely important in analysing safety data and must be given full consideration before any results are finalised.

Purpose – This chapter gives an overview of methods for defining and analysing crash severity.

Methodology – Commonly used methods for defining crash severity are surveyed and reviewed. Factors commonly found to be associated with crash severity are discussed. Approaches for formulating and estimating models for predicting crash severity are presented and critiqued. Two examples of crash severity modelling exercises are presented and findings are discussed. Suggestions are offered for future research in crash severity modelling.

Findings – Crash severity is usually defined according to the outcomes for the persons involved. The definition of severity levels used by law enforcement or crash investigation professionals is less detailed and consistent than what is used by medical professionals. Defining crash severity by vehicle damage can be more consistent, as vehicle response to crash forces is more consistent than that of humans. Factors associated with crash severity fall into three categories – human, vehicle/equipment and environmental/road – and can apply before, during or after the crash event. Crash severity can be modelled using ordered, nominal or several different types of mixed models designed to overcome limitations of the ordered and nominal approaches. Two mixed modelling examples demonstrate better prediction accuracy than ordered or nominal modelling.

Research Implications – Linkage of crash, roadway and healthcare data sets could create a more accurate picture of crash severity. Emerging statistical analysis methods could address remaining limitations of the current best methods for crash severity modelling.

Practical Implications – Medical definitions of injury severity require observation by trained medical professionals and access to private medical records, limiting their use in routine crash data collection. Crash severity is more sensitive to human and vehicle factors than environmental or road factors. Unfortunately, human and vehicle factor data are generally not available for aggregate forecasting.

Purpose – The focus of this chapter is on state-of-the-art methodology for observational before–after evaluations. The purpose of such evaluations is to acquire information on the safety effects of site-specific treatments that could be used by road agencies for future interventions that may have an impact on safety.

Methodology – Information, illustrated by a detailed example, is presented mainly on what is still regarded as the gold standard – the Empirical Bayes (EB) method. The methodology accounts for observed changes in crash frequencies that may be due to regression-to-the-mean, changes in traffic volume and time trends. Two related approaches – a comparison group method and the Full Bayes approach, which have been legitimately used for evaluations under special circumstances – are discussed in brief.

Findings – The EB before–after methodology remains the gold standard but must be applied properly.

Research implications – Some issues, for example, the selection of reference groups, still require further research.

Practical implications – Key issues in the application of the before–after evaluation methods in general are also discussed.

Purpose – This chapter aims to advise the public as well as municipal, state and national agencies about how pedestrian safety can be improved through changes in our built environment. Higher safety can lead to more walking and thereby a more sustainable society.

Methodology – The chapter is based on a review of literature, including a review of published papers and field studies by the author himself.

Findings – To reach ‘acceptable’ safety levels, all arterials and collector roads – at least segments with more than 50 pedestrians a day – should have sidewalks. The sidewalks should be separated from the roadway by a curb if speeds are low and by a barrier or wide separation strip in high-speed areas; that is, where speeds are higher than 50 km/h. Local roads also need sidewalks unless traffic volumes and speeds are very low. The major safety issue for pedestrians is, however, where they cross streets. Elderly pedestrians and pedestrians in a great hurry or under the influence of intoxicants in particular need streets to be narrow and have low speeds for them to be able to cross safely. Marking crosswalks or even signalising them will have only marginal safety effects at best. Posting them for low speed is also not enough unless we have photo speed-enforcement ensuring that everyone drives slowly. Rather, using narrow cross-sections or speed cushions at the approaches ensuring that 90-percentile speeds are no more than 30 km/h at crossing points is key to safety. In between crossing points a speed of 50 km/h is acceptable with pedestrians on adjacent sidewalks.

Social implications – We as a society need to encourage walking as a mode of transportation since walking promotes better health and a cleaner environment; that is, a more sustainable society. However, it has to be safe to walk or people will prefer to drive to their destinations. Also, distances between destination points have to be kept reasonably short and the environment, where people walk needs to be interesting and aesthetically somewhat pleasing to encourage walking.