The effectiveness of using a simple ARIA based geographical classification to identify road crash patterns in rural and urban areas of Queensland

Research has noted a ‘pronounced pattern of increase with increasing remoteness' of death rates in road crashes. However, crash characteristics by remoteness are not commonly or consistently reported, with definitions of rural and urban often relying on proxy representations such as prevailing speed limit. The current paper seeks to evaluate the efficacy of the Accessibility / Remoteness Index of Australia (ARIA+) to identifying trends in road crashes. ARIA+ does not rely on road-specific measures and uses distances to populated centres to attribute a score to an area, which can in turn be grouped into 5 classifications of increasing remoteness. The current paper uses applications of these classifications at the broad level of Australian Bureau of Statistics' Statistical Local Areas, thus avoiding precise crash locating or dedicated mapping software. Analyses used Queensland road crash database details for all 31,346 crashes resulting in a fatality or hospitalisation occurring between 1st July, 2001 and 30th June 2006 inclusive. Results showed that this simplified application of ARIA+ aligned with previous definitions such as speed limit, while also providing further delineation. Differences in crash contributing factors were noted with increasing remoteness such as a greater representation of alcohol and ‘excessive speed for circumstances.' Other factors such as the predominance of younger drivers in crashes differed little by remoteness classification. The results are discussed in terms of the utility of remoteness as a graduated rather than binary (rural/urban) construct and the potential for combining ARIA crash data with census and hospital datasets.

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.

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.

Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

Priorities for developing and evaluating data quality characteristics of road crash data in Australia

The National Road Safety Strategy 2011-2020 outlines plans to reduce the burden of road trauma via improvements and interventions relating to safe roads, safe speeds, safe vehicles, and safe people. It also highlights that a key aspect in achieving these goals is the availability of comprehensive data on the issue. The use of data is essential so that more in-depth epidemiologic studies of risk can be conducted as well as to allow effective evaluation of road safety interventions and programs. Before utilising data to evaluate the efficacy of prevention programs it is important for a systematic evaluation of the quality of underlying data sources to be undertaken to ensure any trends which are identified reflect true estimates rather than spurious data effects. However, there has been little scientific work specifically focused on establishing core data quality characteristics pertinent to the road safety field and limited work undertaken to develop methods for evaluating data sources according to these core characteristics. There are a variety of data sources in which traffic-related incidents and resulting injuries are recorded, which are collected for a variety of defined purposes. These include police reports, transport safety databases, emergency department data, hospital morbidity data and mortality data to name a few. However, as these data are collected for specific purposes, each of these data sources suffers from some limitations when seeking to gain a complete picture of the problem. Limitations of current data sources include: delays in data being available, lack of accurate and/or specific location information, and an underreporting of crashes involving particular road user groups such as cyclists. This paper proposes core data quality characteristics that could be used to systematically assess road crash data sources to provide a standardised approach for evaluating data quality in the road safety field. The potential for data linkage to qualitatively and quantitatively improve the quality and comprehensiveness of road crash data is also discussed.

Road crash risk after whiplash associated disorder

The future on-road safety of drivers affected by Whiplash Associated Disorder (WAD), the most common soft-tissue injury suffered in a traffic crash, has not been extensively explored. We obtained an anonymised file of 4280 insurance claimants with WAD and, as controls, 1116 claimants with comparably severe soft-tissue injuries who are considered to be at no increased risk than the general population. Their demographic information, road user type and traffic crash records both prior and subsequent to the traffic incident in which the injury occurred, the index crash, were obtained. Rates of subsequent crash involvement in these two groups were then compared, adjusting for age, sex, road user type and prior crash experience. The risk of a subsequent crash in the WAD group relative to controls was 1.14 (95% confidence interval, 0.87–1.48). To allow for differentially altered driving exposure after index crash we distributed a brief survey asking about changes in driving habits after a traffic crash involving injury via physiotherapy clinics and online through the electronic newsletter of a local motoring organisation. The survey yielded responses from 113 drivers who had experienced WAD in a traffic crash and 53 with other soft tissue injuries. There were no differences on average between the groups in their prior driving levels or their percentage change therein at one, three or six months after injury. There was thus no evidence that drivers with WAD are at any higher safety risk than drivers with other types of relatively minor post-crash soft tissue injury.

Data mining the relationship between road crash and skid resistance

Road asset managers are seeking analysis of the whole road network to supplement statistical analyses of small subsets of homogeneous roadway. This study outlines the use of data mining capable of analyzing the wide range of situations found on the network, with a focus on the role of skid resistance in the cause of crashes. Results from the analyses show that on non-crash-prone roads with low crash rates, skid resistance contributes only in a minor way, whereas on high-crash roadways, skid resistance often contributes significantly in the calculation of the crash rate. The results provide evidence supporting a causal relationship between skid resistance and crashes and highlight the importance of the role of skid resistance in decision making in road asset management.

Estimating the under-reporting of road crash injuries to police using multiple linked data collections

The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries.

How serious are they? The use of data linkage to explore different definitions of serious road crash injuries

Over recent years, the focus in road safety has shifted towards a greater understanding of road crash serious injuries in addition to fatalities. Police reported crash data are often the primary source of crash information; however, the definition of serious injury within these data is not consistent across jurisdictions and may not be accurately operationalised. This study examined the linkage of police-reported road crash data with hospital data to explore the potential for linked data to enhance the quantification of serious injury. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. Nine different estimates of serious road crash injury were produced. Results showed that there was a large amount of variation in the estimates of the number and profile of serious road crash injuries depending on the definition or measure used. The results also showed that as the definition of serious injury becomes more precise the vulnerable road users become more prominent. These results have major implications in terms of how serious injuries are identified for reporting purposes. Depending on the definitions used, the calculation of cost and understanding of the impact of serious injuries would vary greatly. This study has shown how data linkage can be used to investigate issues of data quality. It has also demonstrated the potential improvements to the understanding of the road safety problem, particularly serious injury, by conducting data linkage.

A data mining driven crash risk profiling method for road asset management

This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

Rural and remote road safety study : final report

• Introduction: Concern and action for rural road safety is relatively new in Australia in comparison to the field of traffic safety as a whole. In 2003, a program of research was begun by the Centre for Accident Research and Road Safety - Queensland (CARRS-Q) and the Rural Health Research Unit (RHRU) at James Cook University to investigate factors contributing to serious rural road crashes in the North Queensland region. This project was funded by the Premier’s Department, Main Roads Department, Queensland Transport, QFleet, Queensland Rail, Queensland Ambulance Service, Department of Natural Resources and Queensland Police Service. Additional funding was provided by NRMA Insurance for a PhD scholarship. In-kind support was provided through the four hospitals used for data collection, namely Cairns Base Hospital, The Townsville Hospital, Mount Isa Hospital and Atherton Hospital.----- The primary aim of the project was to: Identify human factors related to the occurrence of serious traffic incidents in rural and remote areas of Australia, and to the trauma suffered by persons as a result of these incidents, using a sample drawn from a rural and remote area in North Queensland.----- The data and analyses presented in this report are the core findings from two broad studies: a general examination of fatalities and casualties from rural and remote crashes for the period 1 March 2004 until 30 June 2007, and a further linked case-comparison study of hospitalised patients compared with a sample of non-crash-involved drivers.----- • Method: The study was undertaken in rural North Queensland, as defined by the Australian Bureau of Statistics (ABS) statistical divisions of North Queensland, Far North Queensland and North-West Queensland. Urban areas surrounding Townsville, Thuringowa and Cairns were not included. The study methodology was centred on serious crashes, as defined by a resulting hospitalisation for 24 hours or more and/or a fatality. Crashes meeting this criteria within the North Queensland region between 1 March 2004 and 30 June 2007 were identified through hospital records and interviewed where possible. Additional data was sourced from coroner’s reports, the Queensland Transport road crash database, the Queensland Ambulance Service and the study hospitals in the region.----- This report is divided into chapters corresponding to analyses conducted on the collected crash and casualty data.----- Chapter 3 presents an overview of all crashes and casualties identified during the study period. Details are presented in regard to the demographics and road user types of casualties; the locations, times, types, and circumstances of crashes; along with the contributing circumstances of crashes.----- Chapter 4 presents the results of summary statistics for all casualties for which an interview was able to be conducted. Statistics are presented separately for drivers and riders, passengers, pedestrians and cyclists. Details are also presented separately for drivers and riders crashing in off-road and on-road settings. Results from questionnaire data are presented in relation to demographics; the experience of the crash in narrative form; vehicle characteristics and maintenance; trip characteristics (e.g. purpose and length of journey; periods of fatigue and monotony; distractions from driving task); driving history; alcohol and drug use; medical history; driving attitudes, intentions and behaviour; attitudes to enforcement; and experience of road safety advertising.----- Chapter 5 compares the above-listed questionnaire results between on-road crash-involved casualties and interviews conducted in the region with non-crash-involved persons. Direct comparisons as well as age and sex adjusted comparisons are presented.----- Chapter 6 presents information on those casualties who were admitted to one of the study hospitals during the study period. Brief information is given regarding the demographic characteristics of these casualties. Emergency services’ data is used to highlight the characteristics of patient retrieval and transport to and between hospitals. The major injuries resulting from the crashes are presented for each region of the body and analysed by vehicle type, occupant type, seatbelt status, helmet status, alcohol involvement and nature of crash. Estimates are provided of the costs associated with in-hospital treatment and retrieval.----- Chapter 7 describes the characteristics of the fatal casualties and the nature and circumstances of the crashes. Demographics, road user types, licence status, crash type and contributing factors for crashes are presented. Coronial data is provided in regard to contributing circumstances (including alcohol, drugs and medical conditions), cause of death, resulting injuries, and restraint and helmet use.----- Chapter 8 presents the results of a comparison between casualties’ crash descriptions and police-attributed crash circumstances. The relative frequency of contributing circumstances are compared both broadly within the categories of behavioural, environmental, vehicle related, medical and other groupings and specifically for circumstances within these groups.----- Chapter 9 reports on the associated research projects which have been undertaken on specific topics related to rural road safety.----- Finally, Chapter 10 reports on the conclusions and recommendations made from the program of research.---- • Major Recommendations : From the findings of these analyses, a number of major recommendations were made: + Male drivers and riders - Male drivers and riders should continue to be the focus of interventions, given their very high representation among rural and remote road crash fatalities and serious injuries.----- - The group of males aged between 30 and 50 years comprised the largest number of casualties and must also be targeted for change if there is to be a meaningful improvement in rural and remote road safety.----- + Motorcyclists - Single vehicle motorcycle crashes constitute over 80% of serious, on-road rural motorcycle crashes and need particular attention in development of policy and infrastructure.----- - The motorcycle safety consultation process currently being undertaken by Queensland Transport (via the "Motorbike Safety in Queensland - Consultation Paper") is strongly endorsed. As part of this process, particular attention needs to be given to initiatives designed to reduce rural and single vehicle motorcycle crashes.----- - The safety of off-road riders is a serious problem that falls outside the direct responsibility of either Transport or Health departments. Responsibility for this issue needs to be attributed to develop appropriate policy, regulations and countermeasures.----- + Road safety for Indigenous people - Continued resourcing and expansion of The Queensland Aboriginal Peoples and Torres Strait Islander Peoples Driver Licensing Program to meet the needs of remote and Indigenous communities with significantly lower licence ownership levels.----- - Increased attention needs to focus on the contribution of geographic disadvantage (remoteness) factors to remote and Indigenous road trauma.----- + Road environment - Speed is the ‘final common pathway’ in determining the severity of rural and remote crashes and rural speed limits should be reduced to 90km/hr for sealed off-highway roads and 80km/hr for all unsealed roads as recommended in the Austroads review and in line with the current Tasmanian government trial.----- - The Department of Main Roads should monitor rural crash clusters and where appropriate work with local authorities to conduct relevant audits and take mitigating action. - The international experts at the workshop reviewed the data and identified the need to focus particular attention on road design management for dangerous curves. They also indicated the need to maximise the use of audio-tactile linemarking (audible lines) and rumble strips to alert drivers to dangerous conditions and behaviours.----- + Trauma costs - In accordance with Queensland Health priorities, recognition should be given to the substantial financial costs associated with acute management of trauma resulting from serious rural and remote crashes.----- - Efforts should be made to develop a comprehensive, regionally specific costing formula for road trauma that incorporates the pre-hospital, hospital and post-hospital phases of care. This would inform health resource allocation and facilitate the evaluation of interventions.----- - The commitment of funds to the development of preventive strategies to reduce rural and remote crashes should take into account the potential cost savings associated with trauma.----- - A dedicated study of the rehabilitation needs and associated personal and healthcare costs arising from rural and remote road crashes should be undertaken.----- + Emergency services - While the study has demonstrated considerable efficiency in the response and retrieval systems of rural and remote North Queensland, relevant Intelligent Transport Systems technologies (such as vehicle alarm systems) to improve crash notification should be both developed and evaluated.----- + Enforcement - Alcohol and speed enforcement programs should target the period between 2 and 6pm because of the high numbers of crashes in the afternoon period throughout the rural region.----- + Drink driving - Courtesy buses should be advocated and schemes such as the Skipper project promoted as local drink driving countermeasures in line with the very high levels of community support for these measures identified in the hospital study.------ - Programs should be developed to target the high levels of alcohol consumption identified in rural and remote areas and related involvement in crashes.----- - Referrals to drink driving rehabilitation programs should be mandated for recidivist offenders.----- + Data requirements - Rural and remote road crashes should receive the same quality of attention as urban crashes. As such, it is strongly recommended that increased resources be committed to enable dedicated Forensic Crash Units to investigate rural and remote fatal and serious injury crashes.----- - Transport department records of rural and remote crashes should record the crash location using the national ARIA area classifications used by health departments as a means to better identifying rural crashes.----- - Rural and remote crashes tend to be unnoticed except in relatively infrequent rural reviews. They should receive the same level of attention and this could be achieved if fatalities and fatal crashes were coded by the ARIA classification system and included in regular crash reporting.----- - Health, Transport and Police agencies should collect a common, minimal set of data relating to road crashes and injuries, including presentations to small rural and remote health facilities.----- + Media and community education programmes - Interventions seeking to highlight the human contribution to crashes should be prioritised. Driver distraction, alcohol and inappropriate speed for the road conditions are key examples of such behaviours.----- - Promotion of basic safety behaviours such as the use of seatbelts and helmets should be given a renewed focus.----- - Knowledge, attitude and behavioural factors that have been identified for the hospital Brief Intervention Trial should be considered in developing safety campaigns for rural and remote people. For example challenging the myth of the dangerous ‘other’ or ‘non-local’ driver.----- - Special educational initiatives on the issues involved in rural and remote driving should be undertaken. For example the material used by Main Roads, the Australian Defence Force and local initiatives.

Assessing wet crashes for the skid resistance management of road assets

Australia, road crash trauma costs the nation A$15 billion annually whilst the US estimates an economic impact of around US$ 230 billion on its network. Worldwide economic cost of road crashes is estimated to be around US$ 518 billion each year. Road accidents occur due to a number of factors including driver behaviour, geometric alignment, vehicle characteristics, environmental impacts, and the type and condition of the road surfacing. Skid resistance is considered one of the most important road surface characteristics because it has a direct effect on traffic safety. In 2005, Austroads (the Association of Australian and New Zealand Road Transport and Traffic Authorities) published a guideline for the management of skid resistance and Queensland Department of Main Roads (QDMR) developed a skid resistance management plan (SRMP). The current QDMR strategy is based on rationale analytical methodology supported by field inspection with related asset management decision tools. The Austroads’s guideline and QDMR's skid resistance management plan have prompted QDMR to review its skid resistance management practice. As a result, a joint research project involving QDMR, Queensland University of Technology (QUT) and the Corporative Research Centre for Integrated Engineering Asset Management (CRC CIEAM) was formed. The research project aims at investigating whether there is significant relationship between road crashes and skid resistance on Queensland’s road networks. If there is, the current skid resistance management practice of QDMR will be reviewed and appropriate skid resistance investigatory levels will be recommended. This paper presents analysis results in assessing the relationship between wet crashes and skid resistance on Queensland roads. Attributes considered in the analysis include surface types, annual average daily traffic (AADT), speed and seal age.

Identifying relationship between skid resistance, road characteristics and crashes using probability-based risk approach

Road accidents are of great concerns for road and transport departments around world, which cause tremendous loss and dangers for public. Reducing accident rates and crash severity are imperative goals that governments, road and transport authorities, and researchers are aimed to achieve. In Australia, road crash trauma costs the nation A$ 15 billion annually. Five people are killed, and 550 are injured every day. Each fatality costs the taxpayer A$1.7 million. Serious injury cases can cost the taxpayer many times the cost of a fatality. Crashes are in general uncontrolled events and are dependent on a number of interrelated factors such as driver behaviour, traffic conditions, travel speed, road geometry and condition, and vehicle characteristics (e.g. tyre type pressure and condition, and suspension type and condition). Skid resistance is considered one of the most important surface characteristics as it has a direct impact on traffic safety. Attempts have been made worldwide to study the relationship between skid resistance and road crashes. Most of these studies used the statistical regression and correlation methods in analysing the relationships between skid resistance and road crashes. The outcomes from these studies provided mix results and not conclusive. The objective of this paper is to present a probability-based method of an ongoing study in identifying the relationship between skid resistance and road crashes. Historical skid resistance and crash data of a road network located in the tropical east coast of Queensland were analysed using the probability-based method. Analysis methodology and results of the relationships between skid resistance, road characteristics and crashes are presented.

Using data mining on road asset management data in analysing road crashes

Road safety is a major concern worldwide. Road safety will improve as road conditions and their effects on crashes are continually investigated. This paper proposes to use the capability of data mining to include the greater set of road variables for all available crashes with skid resistance values across the Queensland state main road network in order to understand the relationships among crash, traffic and road variables. This paper presents a data mining based methodology for the road asset management data to find out the various road properties that contribute unduly to crashes. The models demonstrate high levels of accuracy in predicting crashes in roads when various road properties are included. This paper presents the findings of these models to show the relationships among skid resistance, crashes, crash characteristics and other road characteristics such as seal type, seal age, road type, texture depth, lane count, pavement width, rutting, speed limit, traffic rates intersections, traffic signage and road design and so on.

Road safety issues for older road users : CARRS-Q Monograph 1

[Selection of papers from the Older Road User Safety Symposium, 26 November 2000, Brisbane, Australia.]----- This publication is a selection of papers on older road user safety which were presented at the Older Road User Safety Symposium on Sunday 26 November 2000 at the Sheraton Brisbane Hotel, Queensland, Australia. The Symposium was held on the day before Australia’s annual Road Safety Research, Policing and Education Conference, which provided an opportunity to garner both presenters and participants from the wider road safety community in Australia. Road safety is a large and diverse area of scholarship and practice, and many disciplines are drawn on in the processes of understanding and addressing road safety problems. The safety of older road users is no different. As this selection shows, work on older road user safety can be informed by demography, research on the mental and physical effects of ageing, social research on older people as road users, evaluation of educational and behavioural interventions, road crash analysis, engineering research and practice, and reviews of policy approaches within Australia and elsewhere. It is possible to summarise these into four constellations, which are reflected in the papers selected for this publication: social impacts and responses; physical and cognitive capability; specific road use performance; and environment/ecology. Though three years have passed since the Symposium, the issues raised in these papers remain current.