Differences in the performance of safety performance functions estimated for total crash count and for crash count by crash type

In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as safety performance functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach for applying intersection SPFs is to assume that crash types occur in fixed proportions (e.g., rear-end crashes make up 20% of crashes, angle crashes 35%, and so forth) and then apply these fixed proportions to crash totals to estimate crash frequencies by type. As demonstrated in this paper, such a practice makes questionable assumptions and results in considerable error in estimating crash proportions. Through the use of rudimentary SPFs based solely on the annual average daily traffic (AADT) of major and minor roads, the homogeneity-in-proportions assumption is shown not to hold across AADT, because crash proportions vary as a function of both major and minor road AADT. For example, with minor road AADT of 400 vehicles per day, the proportion of intersecting-direction crashes decreases from about 50% with 2,000 major road AADT to about 15% with 82,000 AADT. Same-direction crashes increase from about 15% to 55% for the same comparison. The homogeneity-in-proportions assumption should be abandoned, and crash type models should be used to predict crash frequency by crash type. SPFs that use additional geometric variables would only exacerbate the problem quantified here. Comparison of models for different crash types using additional geometric variables remains the subject of future research.

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.

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.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

Effect of clear zone widths on run-off-road crash outcomes

Current guidelines on clear zone selection and roadside hazard management adopt the US approach based on the likelihood of roadside encroachment by drivers. This approach is based on the available research conducted in the 1960s and 70s. Over time, questions have been raised regarding the robustness and applicability of this research in Australasia in 2010 and in the Safe System context. This paper presents a review of the fundamental research relating to selection of clear zones. Results of extensive rural highway statistical data modelling suggest that a significant proportion of run-off-road to the left casualty crashes occurs in clear zones exceeding 13 m. They also show that the risk of run-off-road to the left casualty crashes was 21% lower where clear zones exceeded 8 m when compared with clear zones in the 4 – 8 m range. The paper discusses a possible approach to selection of clear zones based on managing crash outcomes, rather than on the likelihood of roadside encroachment which is the basis for the current practice. It is expected that this approach would encourage selection of clear zones wider than 8 m when the combination of other road features suggests higher than average casualty crash risk.

Crash risk estimation and assessment tool

Currently in Australia, there are no decision support tools for traffic and transport engineers to assess the crash risk potential of proposed road projects at design level. A selection of equivalent tools already exists for traffic performance assessment, e.g. aaSIDRA or VISSIM. The Urban Crash Risk Assessment Tool (UCRAT) was developed for VicRoads by ARRB Group to promote methodical identification of future crash risks arising from proposed road infrastructure, where safety cannot be evaluated based on past crash history. The tool will assist practitioners with key design decisions to arrive at the safest and the most cost -optimal design options. This paper details the development and application of UCRAT software. This professional tool may be used to calculate an expected mean number of casualty crashes for an intersection, a road link or defined road network consisting of a number of such elements. The mean number of crashes provides a measure of risk associated with the proposed functional design and allows evaluation of alternative options. The tool is based on historical data for existing road infrastructure in metropolitan Melbourne and takes into account the influence of key design features, traffic volumes, road function and the speed environment. Crash prediction modelling and risk assessment approaches were combined to develop its unique algorithms. The tool has application in such projects as road access proposals associated with land use developments, public transport integration projects and new road corridor upgrade proposals.

V2V/V2I augmented maps : state-of-the-art and contribution to real-time crash risk assessment

A number of advanced driver assistance systems (ADAS) are currently being released on the market, providing safety functions to the drivers such as collision avoidance, adaptive cruise control or enhanced night-vision. These systems however are inherently limited by their sensory range: they cannot gather information from outside this range, also called their “perceptive horizon”. Cooperative systems are a developing research avenue that aims at providing extended safety and comfort functionalities by introducing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications to the road actors. This paper presents the problematic of cooperative systems, their advantages and contributions to road safety and exposes some limitations related to market penetration, sensors accuracy and communications scalability. It explains the issues of how to implement extended perception, a central contribution of cooperative systems. The initial steps of an evaluation of data fusion architectures for extended perception are exposed.

Discrimination or Differential Involvement? A Review of the Research Exploring the Impact of Indigenous Status on Sentencing

Existing court data suggest that adult Indigenous offenders are more likely than non-Indigenous defendants to be sentenced to prison but once imprisoned generally receive shorter terms. Using findings from international and Australian multivariate statistical analyses, this paper reviews the three key hypotheses advanced as plausible explanations for these differences: 1) differential involvement, 2) negative discrimination, 3) positive discrimination. Overall, prior research shows strong support for the differential involvement thesis, some support for positive discrimination and little foundation for negative discrimination in the sentencing of Indigenous defendants. Where discrimination is found, we argue that this may be explained by the lack of a more complete set of control variables in researchers’ multivariate models.

The Heavy Vehicle Study : a case-control study investigating risk factors for crash in long distance heavy vehicle drivers in Australia

Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.

Keeping in constant touch : the predictors of young Australians’ mobile phone involvement

Little is known about the psychological underpinnings of young people’s mobile phone behaviour. In the present research, 292 young Australians, aged 16–24 years, completed an online survey assessing the effects of self-identity, in-group norm, the need to belong, and self-esteem on their frequency of mobile phone use and mobile phone involvement, conceptualised as people’s degree of cognitive and behavioural association with their mobile phone. Structural equation modelling revealed that age (younger) and self-identity significantly predicted the frequency of mobile phone use. In contrast, age (younger), gender (female), self-identity and in-group norm predicted young people’s mobile phone involvement. Neither self-esteem nor the need to belong significantly predicted mobile phone behaviour. The present study contributes to our understanding of this phenomenon and provides an indication of the characteristics of young people who may become highly involved with their mobile phone.

Should we be concerned about alcohol in bicycle crashes?

This paper sets out to examine from published literature and crash data analyses whether alcohol in bicycle crashes is an issue about which we should be concerned. It discusses factors that have the potential to increase the number of bicycle crashes in which alcohol is involved (such growth in the size and diversity of the cyclist population, and balance and coordination demands) and factors which may reduce the importance of alcohol in bicycle crashes (such as time of data factors and child riders). It also examines data availability issues that contribute to difficulties in determining the true magnitude of the issue. Methods: This paper reviews previous research and reports analyses of data from Queensland, Australia, that examine the role of alcohol in Police-reported road crashes. In Queensland it is an offence to ride a bicycle or drive a motor vehicle with a BAC exceeding 0.05% (or lower for novice and professional drivers). Results: In the five years 2003-2007, alcohol was reported as involved in 165 bicycle crashes (4%). The bicycle rider was coded as “under the influence” or “over the prescribed BAC limit” in 15 were single unit crashes (12%). In multi-vehicle bicycle crashes, alcohol involvement was reported for 16 cyclists (0.4%) and 110 operators of other vehicles (3%). Additional analyses including characteristics of the cyclist crashes involving alcohol and the importance of missing data will be discussed in the paper. Conclusion: The increase in participation in cycling and the vulnerability of cyclists to injuries support the need to examine the role of alcohol in bicycle crashes. Current data suggest that alcohol on the part of the vehicle driver is a larger concern than alcohol on the part of the cyclist, but improvements in data collection are needed before more precise conclusions can be drawn.

Involvement of Exo1b in DNA damage-induced apoptosis

Apoptosis is essential for the maintenance of inherited genomic integrity. During DNA damage-induced apoptosis, mechanisms of cell survival, such as DNA repair are inactivated to allow cell death to proceed. Here, we describe a role for the mammalian DNA repair enzyme Exonuclease 1 (Exo1) in DNA damage-induced apoptosis. Depletion of Exo1 in human fibroblasts, or mouse embryonic fibroblasts led to a delay in DNA damage-induced apoptosis. Furthermore, we show that Exo1 acts upstream of caspase-3, DNA fragmentation and cytochrome c release. In addition, induction of apoptosis with DNA-damaging agents led to cleavage of both isoforms of Exo1. The cleavage of Exo1 was mapped to Asp514, and shown to be mediated by caspase-3. Expression of a caspase-3 cleavage site mutant form of Exo1, Asp514Ala, prevented formation of the previously observed fragment without any affect on the onset of apoptosis. We conclude that Exo1 has a role in the timely induction of apoptosis and that it is subsequently cleaved and degraded during apoptosis, potentially inhibiting DNA damage repair.

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.

Risky driving or risky drivers? Exploring driving and crash histories of illegal street racing offenders

Illegal street racing has received increased attention in recent years from road safety professionals and the media as jurisdictions in Australia, Canada, and the United States have implemented laws to address the problem, which primarily involves young male drivers. Although some evidence suggests that the prevalence of illegal street racing is increasing, obtaining accurate estimates of the crash risk of this behavior is difficult because of limitations in official data sources. Although crash risk can be explored by examining the proportion of incidents of street racing that result in crashes, or the proportion of all crashes that involve street racing, this paper reports on the findings of a study that explored the riskiness of involved drivers. The driving histories of 183 male drivers with an illegal street racing conviction in Queensland, Australia, were compared with a random sample of 183 male Queensland drivers with the same age distribution. The offender group was found to have significantly more traffic infringements, license sanctions, and crashes than the comparison group. Drivers in the offender group were more likely than the comparison group to have committed infringements related to street racing, such as speeding, "hooning," and offenses related to vehicle defects or illegal modifications. Insufficient statistical capacity prevented full exploration of group differences in the type and nature of earlier crashes. It was concluded, however, that street racing offenders generally can be considered risky drivers who warrant attention and whose risky behavior cannot be explained by their youth alone.

Road crash proneness prediction using data mining

Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.