Size-resolved particle distribution and gaseous concentrations by real-world road tunnel measurement

Measurements of aerosol particle number size distributions (15-700 nm), CO and NOx were performed in a bus tunnel, Australia. Daily mean particle size distributions of mixed diesel/CNG (Compressed Natural Gas) buses traffic flow were determined in 4 consecutive measurement days. EFs (Emission Factors) of Particle size distribution of diesel buses and CNG buses were obtained by MLR (Multiple Linear Regression) methods, particle distributions of diesel buses and CNG buses were observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow were decomposed by two log-normal fitting curves for each 30 minutes interval mean scans, all the mix fleet PSD emission can be well fitted by the summation of two log-normal distribution curves, and these were composed of nuclei mode curve and accumulation curve, which were affirmed as the CNG buses and diesel buses PN emission curves respectively. Finally, particle size distributions of diesel buses and CNG buses were quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters were 74.5～87.5nm, geometric standard deviations were 1.89～1.98. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters were 21～24 nm, geometric standard deviations were 1.27～1.31.

Systems-based approach to investigate unsafe pedestrian behaviour at level crossings

Crashes at level crossings are a major issue worldwide. In Australia, as well as in other countries, the number of crashes with vehicles has declined in the past years, while the number of crashes involving pedestrians seems to have remained unchanged. A systematic review of research related to pedestrian behaviour highlighted a number of important scientific gaps in current knowledge. The complexity of such intersections imposes particular constraints to the understanding of pedestrians’ crossing behaviour. A new systems-based framework, called Pedestrian Unsafe Level Crossing framework (PULC) was developed. The PULC organises contributing factors to crossing behaviour on different system levels as per the hierarchical classification of Jens Rasmussen’s Framework for Risk Management. In addition, the framework adapts James Reason’s classification to distinguish between different types of unsafe behaviour. The framework was developed as a tool for collection of generalizable data that could be used to predict current or future system failures or to identify aspects of the system that require further safety improvement. To give it an initial support, the PULC was applied to the analysis of qualitative data from focus groups discussions. A total number of 12 pedestrians who regularly crossed the same level crossing were asked about their daily experience and their observations of others’ behaviour which allowed the extraction and classification of factors associated with errors and violations. Two case studies using Rasmussen’s AcciMap technique are presented as an example of potential application of the framework. A discussion on the identified multiple risk contributing factors and their interactions is provided, in light of the benefits of applying a systems approach to the understanding of the origins of individual’s behaviour. Potential actions towards safety improvement are discussed.

Adaptive nature of coordinated road traffic injury prevention responses in some OECD countries

This study examines the context of coordinated responses, triggers for coordinated responses, and preference for or choice of coordinating strategies in road traffic injury prevention at a local level in some OECD countries. This aim is achieved through a mixed-methodology. In this respect, 22 semi-structured interviews were conducted with road traffic injury prevention experts from five OECD countries. In addition, 31 professional road traffic injury prevention stakeholders from seven OECD nations completed a self-administered, online survey. It found that there was resource limitation and inter-dependence across actors within the context of road traffic injury prevention at a local level. Furthermore, this study unveiled the realization of resource-dependency as a trigger for coordinated responses at a local level. Moreover, the present examination has revealed two coordinating strategies favored by experts in road traffic injury prevention – i.e. self-organizing community groups, which are deemed to have a platform to deliver programs within communities, and the funding of community groups to forge partnerships. However, the present study did not appear to endorse other strategies such as the formalization of coordinated responses or a legal mandate to coordinate responses. In essence, this study appears to suggest a need to manage coordinated responses from an adaptive perspective with interactions across road traffic injury prevention programs being forged on a mutual understanding of inter-dependency arising out of resource scarcity. In fact, the role of legislation and top-down national models in local level management of coordinated responses is likely to be one of identifying opportunities to interact with self-organized community groups and fund partnership-based road traffic injury prevention events.

Young and unaffected by road policing strategies: Using deterrence theory to explain provisional drivers' (non)compliance

Newly licenced drivers are disproportionately represented in traffic injuries and crash statistics. Despite the implementation of countermeasures designed to improve safety, such as graduated driver licencing (GDL) schemes, many young drivers do not comply with road rules. This study used a reconceptualised deterrence theory framework to investigate young drivers’ perceptions of the enforcement of road rules in general and those more specifically related to GDL. A total of 236 drivers aged 17–24 completed a questionnaire assessing their perceptions of various deterrence mechanisms (personal and vicarious) and their compliance with both GDL-specific and general road rules. Hierarchical multiple regressions conducted to explore noncompliant behaviour revealed that, contrary to theoretical expectations, neither personal nor vicarious punishment experiences affected compliance in the expected direction. Instead, the most influential factors contributing to noncompliance were licence type (P2) and, counterintuitively, having previously been exposed to enforcement. Parental enforcement was also significant in the prediction of transient rule violations, but not fixed rule violations or overall noncompliance. Findings are discussed in light of several possibilities, including an increase in violations due to more time spent on the road, an ‘emboldening effect’ noted in prior studies and possible conceptual constraints regarding the deterrence variables examined in this study.

Zombies on the road: A holistic design approach to balancing gamification and safe driving

This paper explores novel driving experiences that make use of gamification and augmented reality in the car. We discuss our design considerations, which are grounded in road safety psychology and video game design theory. We aim to address the tension between safe driving practices and player engagement. Specifically, we propose a holistic, iterative thinking process inspired by game design cognition and share our insights generated through the application of this process. We present preliminary game concepts that blend digital components with physical elements from the driving environment. We further highlight how this design process helped us to iteratively evolve these concepts towards being safer while maintaining fun. These insights and game design cognition itself will be useful to the AutomotiveUI community investigating similar novel driving experiences.

Road safety and pavement management: A case study of Tanzania

The implementation of pavement management seems to ignore road safety, with its focus being mainly on infrastructure condition. Safety management as part of pavement management should consider various means of reducing the frequency of vehicle crashes by allocating corrective measures to mitigate accident exposure, as well as reduce accident severity and likelihood. However, it is common that lack of accident records and crash contributing factors impedes incorporating safety into pavement management. This paper presents a case study for the initial development of pavement management systems considering data limitations for 3000 km of Tanzania’s national roads. A performance based optimization utilizes indices for safety and surface condition to allocate corrective measures. A modified Pareto analysis capable of accounting for annual performance and of balancing resources to achieve good surface condition and low levels of safety was applied. Tradeoff analysis for the case study found the need to assign 30% relevance to condition and 70% to road safety. Safety and condition deficiencies were corrected within 5 years with the majority of improvements dedicated to surface treatments and some geometric corrections. Large investments for correcting geometric issues were observed in years two and three if more money was made available.

Reproducible and label-free biosensor for the selective extraction and rapid detection of proteins in biological fluids

Erythropoietin (EPO), a glycoprotein hormone of ∼34 kDa, is an important hematopoietic growth factor, mainly produced in the kidney and controls the number of red blood cells circulating in the blood stream. Sensitive and rapid recombinant human EPO (rHuEPO) detection tools that improve on the current laborious EPO detection techniques are in high demand for both clinical and sports industry. A sensitive aptamer-functionalized biosensor (aptasensor) has been developed by controlled growth of gold nanostructures (AuNS) over a gold substrate (pAu/AuNS). The aptasensor selectively binds to rHuEPO and, therefore, was used to extract and detect the drug from horse plasma by surface enhanced Raman spectroscopy (SERS). Due to the nanogap separation between the nanostructures, the high population and distribution of hot spots on the pAu/AuNS substrate surface, strong signal enhancement was acquired. By using wide area illumination (WAI) setting for the Raman detection, a low RSD of 4.92% over 150 SERS measurements was achieved. The significant reproducibility of the new biosensor addresses the serious problem of SERS signal inconsistency that hampers the use of the technique in the field. The WAI setting is compatible with handheld Raman devices. Therefore, the new aptasensor can be used for the selective extraction of rHuEPO from biological fluids and subsequently screened with handheld Raman spectrometer for SERS based in-field protein detection.

Emerging issues for road construction and maintenance – A futuristic view

In the coming decades the design, construction and maintenance of roads will face a range of new issues and as such will require a number of new approaches. In particular, road authorities will be required to consider and respond to a range of issues related to climate change, and associated extreme weather events, such as the extensive flooding in January 2011 in Queensland, Australia Figure 1). Coupled with diminishing access to road construction supplies (such as aggregate), water scarcity, and the potential for increases in oil and electricity prices, this range of challenges bear little resemblance to those previously faced. In Australia, state and federal authorities face further pressures given the variety of needs resulting from the country's geographical and population diversity, expansive road networks, road freight requirements and relatively small population base.

Reducing environmental pressures of road building

Although road construction and use provides significant economic and social benefits its environmental impact is of growing concern. Roads are one of the greatest greenhouse gas contributors both directly through fossil energy consumed in mining, transporting, earthworks, and paving work, along with in-direct emissions from road use by vehicles. This discussion paper will outline opportunities within the Australian context for reducing environmental pressure in road building and consider the future environmental impacts of road projects.

Active learning: A step towards automating medical concept extraction

Objective This paper presents an automatic active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort, and (2) the robustness of incremental active learning framework across different selection criteria and datasets is determined. Materials and methods The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional Random Fields as the supervised method, and least confidence and information density as two selection criteria for active learning framework were used. The effect of incremental learning vs. standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. Two clinical datasets were used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Results The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared to the Random sampling baseline, the saving is at least doubled. Discussion Incremental active learning guarantees robustness across all selection criteria and datasets. The reduction of annotation effort is always above random sampling and longest sequence baselines. Conclusion Incremental active learning is a promising approach for building effective and robust medical concept extraction models, while significantly reducing the burden of manual annotation.

External knowledge and query strategies in active learning: A study in clinical information extraction

This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required. The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

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.

Addressing the road trauma burden in China: Exploring attitudes, behaviours, risk perceptions and cultural uniqueness

As China continues to motorise rapidly, solutions are needed to reduce the burden of road trauma that is spread inequitably across the community. Little is currently known about how new drivers are trained to deal with on-road challenges, and little is also known about the perceptions, behaviours and attitudes of road users in China. This paper reports on a pilot study conducted in a driver retraining facility in one Chinese city where people who have had their licence suspended for accrual of 12 demerit points in a one year period must attend compulsory retraining in order to regain their licence. A sample of 239 suspended drivers responded to an anonymous questionnaire that sought information about preferred driving speeds and perceptions of safe driving speeds across two speed zones. Responses indicated that speeds higher than the posted limits were commonly reported, and that there was incongruence between preferred and safe speeds, such that a greater proportion of drivers reported preferred speeds that were substantially faster than what were reported as safe speeds. Participants with more driving experience reported significantly fewer crashes than newly licensed drivers (less than 2 years licensed) but no differences were found in offences when compared across groups with different levels of driving experience. Perceptions of risky behaviours were assessed by asking participants to describe what they considered to be the most dangerous on-road behaviours. Speeding and drink driving were the most commonly reported by far, followed by issues such as fatigue, ignoring traffic rules, not obeying traffic rules, phone use while driving, and non-use of seatbelts, which attracted an extremely low response which seems consistent with previously reported low belt wearing rates, unfavourable attitudes towards seatbelt use, and low levels of enforcement. Finally, observations about culturally specific considerations are made from previous research conducted by the authors and others. Specifically, issues of saving face and the importance and pervasiveness of social networks and social influence are discussed with particular regard to how any future countermeasures need to be informed by a thorough understanding of Chinese customs and culture.