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.

The crash involvement of older drivers is associated with their hazard perception latencies

Hazard perception in driving is the one of the few driving-specific skills associated with crash involvement. However, this relationship has only been examined in studies where the majority of individuals were younger than 65. We present the first data revealing an association between hazard perception and self-reported crash involvement in drivers aged 65 and over. In a sample of 271 drivers, we found that individuals whose mean response time to traffic hazards was slower than 6.68 seconds (the ROC-curve derived pass mark for the test) were 2.32 times (95% CI 1.46, 3.22) more likely to have been involved in a self-reported crash within the previous five years than those with faster response times. This likelihood ratio became 2.37 (95% CI 1.49, 3.28) when driving exposure was controlled for. As a comparison, individuals who failed a test of useful field of view were 2.70 (95% CI 1.44, 4.44) times more likely to crash than those who passed. The hazard perception test and the useful field of view measure accounted for separate variance in crash involvement. These findings indicate that hazard perception testing and training could be potentially useful for road safety interventions for this age group.

The short-term effect of air pollution on cardiovascular mortality in Tianjin, China : comparison of time series and case–crossover analyses

Background: Many studies have illustrated that ambient air pollution negatively impacts on health. However, little evidence is available for the effects of air pollution on cardiovascular mortality (CVM) in Tianjin, China. Also, no study has examined which strata length for the time-stratified case–crossover analysis gives estimates that most closely match the estimates from time series analysis. Objectives: The purpose of this study was to estimate the effects of air pollutants on CVM in Tianjin, China, and compare time-stratified case–crossover and time series analyses. Method: A time-stratified case–crossover and generalized additive model (time series) were applied to examine the impact of air pollution on CVM from 2005 to 2007. Four time-stratified case–crossover analyses were used by varying the stratum length (Calendar month, 28, 21 or 14 days). Jackknifing was used to compare the methods. Residual analysis was used to check whether the models fitted well. Results: Both case–crossover and time series analyses show that air pollutants (PM10, SO2 and NO2) were positively associated with CVM. The estimates from the time-stratified case–crossover varied greatly with changing strata length. The estimates from the time series analyses varied slightly with changing degrees of freedom per year for time. The residuals from the time series analyses had less autocorrelation than those from the case–crossover analyses indicating a better fit. Conclusion: Air pollution was associated with an increased risk of CVM in Tianjin, China. Time series analyses performed better than the time-stratified case–crossover analyses in terms of residual checking.

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.

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.

Evaluations of Process Modeling Grammars : Ontological, Qualitative and Quantitative Analyses Using the Example of BPMN

Business processes have emerged as a well-respected variable in the design of successful corporations. However, unlike other key managerial variables, such as products and services, customers and employees, physical or digital assets, the conceptualization and management of business processes are in many respects in their infancy. In this book, Jan Recker investigates the notion of quality of business process modeling grammars. His evaluation is based on an ontological-, qualitative-, and quantitative analysis, applied to BPMN, a widely-used business process modeling grammar. His results reveal the ontological shortcomings of BPMN and how these manifest themselves in actual process modeling practice, as well as how they influence the usage behavior of modeling practitioners. More generally, his book constitutes a landmark for empirical technology assessment, analyzing the way in which design flaws in technology influence usage behavior.

Medication warnings about driving : risk perceptions among French and Australian Communities

Increased crash risk is associated with sedative medications and researchers and health-professionals have called for improvements to medication warnings about driving. The tiered warning system in France since 2005 indicates risk level, uses a color-coded pictogram, and advises the user to seek the advice of a doctor before driving. In Queensland, Australia, the mandatory warning on medications that may cause drowsiness advises the user not to drive or operate machinery if they self-assess that they are affected, and calls attention to possible increased impairment when combined with alcohol. Objectives The reported aims of the study were to establish and compare risk perceptions associated with the Queensland and French warnings among medication users. It was conducted to complement the work of DRUID in reviewing the effectiveness of existing campaigns and practice guidelines. Methods Medication users in France and Queensland were surveyed using warnings about driving from both contexts to compare risk perceptions associated with each label. Both samples were assessed for perceptions of the warning that carried the strongest message of risk. The Queensland study also included perceptions of the likelihood of crash and level of impairment associated with the warning. Results Findings from the French study (N = 75) indicate that when all labels were compared, the majority of respondents perceived the French Level-3 label as the strongest warning about risk concerning driving. Respondents in Queensland had significantly stronger perceptions of potential impairment to driving ability, z = -13.26, p <.000 (n = 325), and potential chance of having a crash, z = -11.87, p < .000 (n = 322), after taking a medication that displayed the strongest French warning, compared with the strongest Queensland warning. Conclusions Evidence suggests that warnings about driving displayed on medications can influence risk perceptions associated with use of medication. Further analyses will determine whether risk perceptions influence compliance with the warnings.

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.

The impact of changes to the graduated driver licensing program in Queensland, Australia on the experiences of learner drivers

Purpose: Graduated driver licensing (GDL) has been introduced in numerous jurisdictions in Australia and internationally in an attempt to ameliorate the significantly greater risk of death and injury for young novice drivers arising from road crashes. The GDL program in Queensland, Australia, was extensively modified in July 2007. This paper reports the driving and licensing experiences of Learner drivers progressing through the current-GDL program, and compares them to the experiences of Learners who progressed through the former-GDL program. ----- ----- Method: Young drivers (n = 1032, 609 females, 423 males) aged 17 to 19 years (M = 17.43, SD = 0.67) were recruited as they progressed from a Learner to a Provisional driver’s licence. They completed a survey exploring their sociodemographic characteristics, driving and licensing experiences as a Learner. Key measures for a subsample (n = 183) of the current-GDL drivers were compared with the former-GDL drivers (n = 149) via t-tests and chi-square analyses. ----- ----- Results: As expected, Learner drivers progressing through the current-GDL program gained significantly more driving practice than those in the former program, which was more likely to be provided by mothers than in the past. Female learners in the current-GDL program reported less difficulty obtaining supervision than those in the former program. The number of attempts needed to pass the practical driving assessment did not change, nor did the amount of professional supervision. The current-GDL Learners held their licence for a significantly longer duration than those in the former program, with the majority reporting that their Logbook entries were accurate on the whole. Compared to those in the former program, a significantly smaller proportion of male current-GDL Learners reported being detected for a driving offence while the females reported significantly lower crash involvement. Most current-GDL drivers reported undertaking their supervised practice at the end of the Learner period. ----- ----- Conclusions: The enhancements to the GDL program in Queensland appear to have achieved many of their intended results. The current-GDL learners participating in the study reported obtaining a significantly greater amount of supervised driving experience compared to former-GDL learners. Encouragingly, the current-GDL Learners did not report any greater difficulty in obtaining supervised driving practice, and there was a decline in the proportion of current-GDL Learners engaging in unsupervised driving. In addition, the majority of Learners do not appear to be attempting to subvert logbook recording requirements, as evidenced by high rates of self-reported logbook accuracy. The results have implications for the development and the evaluation of GDL programs in Australia and around the world.

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.