Pedestrian self-reported exposure to distraction by smart phones while walking and crossing the road

Pedestrian crashes account for approximately 14% of road fatalities in Australia. Crossing the road, while a minor part of total walking, presents the highest crash risk because of potential interaction with motor vehicles. Crash risk is elevated by pedestrian illegal use of the road, which may be widespread (e.g. 20% of crossings at signalised intersections at a sample of sites, Brisbane) and enforcement is rare. Effective road crossing requires integration of multiple skills and judgements, any of which can be hindered by distraction. Observational studies suggest that pedestrians are increasingly likely to ‘multitask’, using mobile technology for entertainment and communication, elevating the risk of distraction while crossing. To investigate this, intercept interviews were conducted with a convenience sample of 211 pedestrians aged 18-65 years in Brisbane CBD. Self-reported frequency of using a smart phone for activities at two levels of distraction: cognitive only (voice calls); or cognitive and visual (text messages, internet access) while walking or crossing the road was collected. Results indicated that smart phone use for potentially distracting activities while walking and while crossing the road was high, especially among 18-30 year olds, who were significantly more likely than 31-44yo or 45-65yo to report smart phone use while crossing the road. For 18-30yo and the higher risk activity of crossing the road, 32% texted at high frequency levels and 27% used internet at high frequency levels. Risky levels of distracted crossing appear to be a growing safety issue for 18-30yo, with greater attention to appropriate interventions needed.

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.

Influence of road traffic environment and mobile phone distraction on the speed selection behaviour of young drivers

Travel speed is one of the most critical parameters for road safety; the evidence suggests that increased vehicle speed is associated with higher crash risk and injury severity. Both naturalistic and simulator studies have reported that drivers distracted by a mobile phone select a lower driving speed. Speed decrements have been argued to be a risk compensatory behaviour of distracted drivers. Nonetheless, the extent and circumstances of the speed change among distracted drivers are still not known very well. As such, the primary objective of this study was to investigate patterns of speed variation in relation to contextual factors and distraction. Using the CARRS-Q high-fidelity Advanced Driving Simulator, the speed selection behaviour of 32 drivers aged 18-26 years was examined in two phone conditions: baseline (no phone conversation) and handheld phone operation. The simulator driving route contained five different types of road traffic complexities, including one road section with a horizontal S curve, one horizontal S curve with adjacent traffic, one straight segment of suburban road without traffic, one straight segment of suburban road with traffic interactions, and one road segment in a city environment. Speed deviations from the posted speed limit were analysed using Ward’s Hierarchical Clustering method to identify the effects of road traffic environment and cognitive distraction. The speed deviations along curved road sections formed two different clusters for the two phone conditions, implying that distracted drivers adopt a different strategy for selecting driving speed in a complex driving situation. In particular, distracted drivers selected a lower speed while driving along a horizontal curve. The speed deviation along the city road segment and other straight road segments grouped into a different cluster, and the deviations were not significantly different across phone conditions, suggesting a negligible effect of distraction on speed selection along these road sections. Future research should focus on developing a risk compensation model to explain the relationship between road traffic complexity and distraction.

Roundabout design guidelines and cycling safety

Review conducted as part of a Queensland Department of Transport and Main Roads funded project ‘Roundabout design review’. The project examined: - Design guidelines - Factors that affect safety at roundabouts

Improving health and safety communication of migrant construction workers

Although statistical data in some developed countries indicate that migrant workers are nearly 30% more likely to have work-related injuries than local workers, no equivalent official injury/ incident statistics on the health and safety (H&S) of migrant workers are currently tracked in Australia. With increasing numbers of migrant workers having joined Australia’s extractive industries infrastructure and commercial construction industry, this suggests the need for some investigation. A particular issue is that lack of H&S communication is one of the key factors leading to construction industry accidents/ incidents as it prevents workers from effectively receiving H&S safety training and acquiring H&S information. Migrant workers whose first languages are not English are particularly affected by this problem and ways are needed to improve their situation. The research aims to do this by evaluating the H&S communication problems of migrant workers and identify an effective H&S communication structure. An overview of the challenge being addressed by the research is firstly provided, followed by a description of the research framework, and a report of the initial findings, from which recommendations are provided for improving H&S performance in the construction industry.

Multi-Hypotheses Tracking using the Dempster–Shafer Theory, application to ambiguous road context

This paper presents a Multi-Hypotheses Tracking (MHT) approach that allows solving ambiguities that arise with previous methods of associating targets and tracks within a highly volatile vehicular environment. The previous approach based on the Dempster–Shafer Theory assumes that associations between tracks and targets are unique; this was shown to allow the formation of ghost tracks when there was too much ambiguity or conflict for the system to take a meaningful decision. The MHT algorithm described in this paper removes this uniqueness condition, allowing the system to include ambiguity and even to prevent making any decision if available data are poor. We provide a general introduction to the Dempster–Shafer Theory and present the previously used approach. Then, we explain our MHT mechanism and provide evidence of its increased performance in reducing the amount of ghost tracks and false positive processed by the tracking system.

Truckies and workplace health promotion: Targeting a hard-to-reach group

- Introduction Research identifies truck drivers as being at high risk of chronic disease. For most truck drivers their workplace is their vehicle. Truck drivers’ health is impacted by the limitations of this unique working environment, including reduced opportunities for physical activity and the intake of healthy foods. Workplaces are widely recognised as effective platforms for health promotion. However, the effectiveness of traditional and contemporary health promotion interventions in truck drivers’ novel workplace is unknown. - Methods This project worked with six transport industry workplaces in Queensland, Australia over a two-year period. Researchers used Participatory Action Research (PAR) processes to engage truck drivers and workplace managers in the implementation and evaluation of six workplace health promotion interventions. These interventions were designed to support truck drivers to increase their physical activity and access to healthy foods at work. They included traditional health promotion interventions such as a free fruit initiative, a ten thousand steps challenge, personal health messages and workplace posters, and a contemporary social media intervention. Participants were engaged via focus groups, interviews and mixed-methods surveys. - Results The project achieved positive changes in truck drivers’ health knowledge and health behaviours, particularly related to nutrition. There were positive changes in truck drivers’ self-reported health rating, body mass index (BMI) and readiness to make health-related lifestyle changes. There were also positive changes in truck drivers reporting their workplace as a key source of health information. These changes were underpinned by a positive shift in the culture of participating workplaces. Truck drivers’ perceptions of their workplace valuing, encouraging, modelling and facilitating healthy nutrition and physical activity behaviours improved. PAR processes enabled researchers to develop relationships with workplace managers, contextualise interventions and deliver rigorous outcomes. Despite the novelty of truck drivers’ mobile workplace, traditional health promotion interventions were more effective than contemporary ones. - Conclusion In this workplace health promotion project targeting a ‘hard-to-reach’ group of truck drivers, a combination of well-designed traditional workplace interventions and the PAR process resulted in positive health outcomes.

Design and Development of an In-Vehicle Human Machine Interface to Improve Fuel Efficiency & Safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behaviour change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, this research seeks to use human factors related theories and practices to inform the design and evaluation of an in-vehicle Human Machine Interface (HMI) providing real-time driver feedback with the aim of improving both fuel efficiency and safety.

Traffic safety at road–rail level crossings using a driving simulator and traffic simulation

Several intelligent transportation systems (ITS) were used with an advanced driving simulator to assess its influence on driving behavior. Three types of ITS interventions were tested: video in vehicle, audio in vehicle, and on-road flashing marker. The results from the driving simulator were inputs for a developed model that used traffic microsimulation (VISSIM 5.4) to assess the safety interventions. Using a driving simulator, 58 participants were required to drive through active and passive crossings with and without an ITS device and in the presence or absence of an approaching train. The effect of changes in driver speed and compliance rate was greater at passive crossings than at active crossings. The slight difference in speed of drivers approaching ITS devices indicated that ITS helped drivers encounter crossings in a safer way. Since the traffic simulation was not able to replicate a dynamic speed change or a probability of stopping that varied depending on ITS safety devices, some modifications were made to the traffic simulation. The results showed that exposure to ITS devices at active crossings did not influence drivers’ behavior significantly according to the traffic performance indicator, such as delay time, number of stops, speed, and stopped delay. However, the results of traffic simulation for passive crossings, where low traffic volumes and low train headway normally occur, showed that ITS devices improved overall traffic performance.

THE DRINKING DRIVER, A guide to the five part series ONE FOR THE ROAD

THE DRINKING DRIVER is a guide for listeners to the Adult Education radio series ONE FOR THE ROAD, a five-part series on drink-driving and Australia’s road toll. ONE FOR THE ROAD was produced by Lee Parker and Julie Levi, with assistance from the Federal Office of Road Safety in Canberra. The five programs, presented by Lee Parker were first broadcast on ABC Radio National in January 1989, and repeated on Radio National and Regional Stations across Australia in April/May 1989. THE DRINKING DRIVER was written by Mark King, Senior Project Officer with the Road Safety Division of the South Australian Department of Transport.

A novel approach to assessing road-curve crash severity

Curves are a common feature of road infrastructure; however crashes on road curves are associated with increased risk of injury and fatality to vehicle occupants. Countermeasures require the identification of contributing factors. However, current approaches to identifying contributors use traditional statistical methods and have not used self-reported narrative claim to identify factors related to the driver, vehicle and environment in a systemic way. Text mining of 3434 road-curve crash claim records filed between 1 January 2003 and 31 December 2005 at a major insurer in Queensland, Australia, was undertaken to identify risk levels and contributing factors. Rough set analysis was used on insurance claim narratives to identify significant contributing factors to crashes and their associated severity. New contributing factors unique to curve crashes were identified (e.g., tree, phone, over-steer) in addition to those previously identified via traditional statistical analysis of Police and licensing authority records. Text mining is a novel methodology to improve knowledge related to risk and contributing factors to road-curve crash severity. Future road-curve crash countermeasures should more fully consider the interrelationships between environment, the road, the driver and the vehicle, and education campaigns in particular could highlight the increased risk of crash on road-curves.

Learning from insurance data: Injuries to other road users in motorcyclist at-fault crashes

In multi-vehicle motorcycle crashes, the motorcycle rider is less likely to be at-fault but more commonly severely injured than the other road user. Therefore, not surprisingly, crashes in which motorcycle riders are at-fault and particularly the injuries to the other road users in these crashes have received little research attention. This paper aims to address this gap in the literature by investigating the factors influencing the severity of injury to other road users in motorcyclist-at-fault crashes. Five years of data from Queensland, Australia, were obtained from a database of claims against the compulsory third party (CTP) injury insurance of the at-fault motorcyclists. Analysis of the data using an ordered probit model shows higher injury severity for crashes involving young (under 25) and older (60+) at-fault motorcyclists. Among the not at-fault road users, the young, old, and males were found to be more severely injured than others. Injuries to vehicle occupants were less severe than those to pillions. Crashes that occurred between vehicles traveling in opposite directions resulted in more severe injuries than those involving vehicles traveling in the same direction. While most existing studies have analyzed police reported crash data, this study used CTP insurance data. Comparison of results indicates the potential of using CTP insurance data as an alternative to police reported crash data for gaining a better understanding of risk factors for motorcycle crashes and injury severity.

Building local capacity to reduce road traffic injury in rapidly motorising countries

Road safety is a significant public health issue - 1.24m killed each year, 20-50m injured, 91% in rapidly motorising low/mid income countries Decade of Action for Road Safety 2011-2020: - National and local actions: “strengthening the management infrastructure and capacity for technical implementation of road safety activities at the national, regional and global levels” - Capacity as a constraint on a country’s action - Emphasis on knowledge/training – understand principles, promote training and education etc

Drink driving among indigenous people in Far North Queensland and Northern New South Wales: A summary of qualitative findings

In response to the threat that drink drivers pose to themselves and others, drink driving programs form an important part of a suite of countermeasures used in Australia and internationally. Unlike New Zealand/Aotearoa, United States and Canada that have programs catering for their First Peoples, all Australian programs are designed for the general driver population. The aim of this study was to identify the factors that contribute to Indigenous drink driving in order to inform appropriate recommendations related to developing a community-based program for Indigenous communities. Broader drivers licensing policy recommendations are also discussed. A sample of 73 Indigenous people from Queensland and in New South Wales with one or more drink driving convictions completed a semi-structured interview regarding their drink driving behaviour. Participants were asked to disclose information regarding their drink driving history, and alcohol and drug use. If participants self-reported no longer drink driving, they were probed about what factors had assisted them to avoid further offending. Key themes which emerged to maintain drink driving include motivations to drink and drive, and belief in the ability to manage the associated risks. Factors that appeared to support others from avoiding further offending include re-connecting with culture and family support. A range of recommendations regarding delivery and content of a program for regional and remote communities as well as other policy implications are discussed.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.