Occupational light vehicle-use: a research driven strategy to improve surveillance and inform policy

Background: Occupational light vehicles (OLV) are light passenger and loadshaped vehicles used for work. The OLV-associated injury burden is as great as that of heavy vehicle users, but has been largely ignored by occupational health and safety (OHS) regulators. Contingent employment growth has accentuated existing gaps in the policy framework between OHS and road-safety. Frequent burden shifting from OHS to road-related health systems undermines the evidence base necessary to inform policy development. Aims: To provide evidence-based recommendations for the collection of OLVuser surveillance data and to underpin OHS procedures and policies for OLVusers. Method: The literature was systematically analyzed to identify OLV-user OHS policy and practice gaps. Strategies to improve and co-ordinate surveillance systems were developed to address the identified limitations. Results: Gaps were identified in OLV-user legislation, data collection, and riskmanagement. These require strategies to improve identification of all OLV-users and to co-ordinate surveillance and OHS practice. Discussion: Contemporary reform of road and OHS, policy, provides a timely opportunity for the implementation of strategic responses to this serious road safety and occupational, public health problem.

Association between attributions of responsibility for motor vehicle crashes, depressive symptoms, and return to work.

Perceptions surrounding the underlying causes of accidents and injuries may be a key mechanism influencing postaccident health and functional outcomes among people injured in road crashes. In particular, attributions of responsibility may influence rates of postcrash depressive symptomatology and return-to-work.

Mini-micro unmanned aerial vehicle intelligence: a threat to land vehicles

Increasing use of commercial off-the-shelf Mini-Micro Unmanned Aerial Vehicle (MAV) systems with enhanced intelligence methodologies can potentially be a threat, if this technology falls into the wrong hands. In this study, we investigate the level of threat imposed on critical infrastructure using different MAV swarm artificial intelligence traits and coordination methodologies. The critical infrastructure in consideration is a moving commercial land vehicle that may be transporting for example an important civil servant or politician. Non-dimensional fitness functions used for measuring MAV mission effectiveness have been established for the case studies considered in this paper. The findings indicated that increased in intelligent and coordination level elevate teams' efficiency, therefore poses a higher degree of threat to targeted land vehicle. Observations from the study have suggested that memory-based cooperative technique provides a consistent efficiency compared to other methods for the mission objectives considered in this paper. © 2014 The authors and IOS Press. All rights reserved.

Nonlinear controller design for vehicle-to-grid systems with output LCL filters

This paper presents a nonlinear controller design for vehicle-to-grid (V2G) systems with LCL output filters. The V2G systems are modeled with LCL output filters in order to eliminate harmonics for improving power qualities and the nonlinear controller is designed based on the feedback linearization. The feasibility of using the appropriate feedback linearization approaches, either partial or exact, is also investigated through the feedback linearizability of V2G systems. In this paper, partial feedback linearization is used to design the controller with a capability of sharing both active and reactive power in V2G systems. The performance of the proposed controller controller is evaluated on a single-phase full-bridge converter-based V2G system with an LCL output filter and compared to that of without any filter. Simulation results clearly demonstrate the harmonic elimination capabilities of the proposed V2G structure with the proposed control scheme.

Characterising vehicle emissions from the burning of biodiesel made from vegetable oil

Biodiesel manufactured from canola oil was blended with diesel and used as fuel in two diesel vehicles. This study aimed to test the emissions of diesel engines using blends of 100%, 80%, 60%, 40% , 20% biodiesel and 100% petroleum diesel, and characterise the particulate matter and gaseous emissions, with particular attention to levels of polycyclic aromatic hydrocarbons (PAHs) which are harmful to humans. A real time dust monitor was also used to monitor the continuous dust emissions during the entire testing cycle. The ECE(Euro 2) drive cycle was used for all emission tests. It was found that the particle concentration was up to 33% less when the engine burnt 100% biodiesel, compared to 100% diesel. Particle emission reduced with increased percentages of biodiesel in the fuel blends. Reductions of NOx, HC and CO were limited to about 10% when biodiesel was burned. Levels of CO2 emissions from the use of biodiesel and diesel were similar. Eighteen EPA priority PAHs were targeted, with only 6 species detected in the gaseous phase from the samples . 9 PAHs were detected in particulate phases at much lower levels than gaseous PAHs. Some marked reductions were observed for less toxic gaseous PAHs such as naphthalene when burning 100% biodiesel, but the particulate PAH emissions, which have more implications to adverse health effects, were virtually unchanged and did not show a statistically significant reduction. These findings are useful to gain an understanding of the emissions and environmental impacts of biodiesel.

Environmental education - appropriate vehicle for teaching science?

This article we have addresses the issue of an integrated science education curriculum. Following Beane (1995), we suggest an approach that begins with an issue, topic or problem that has an independent existence in real life, and which can serve as a supra.disciplinary organizing principle in providing a framework ror developing a curriculum that presents science content in a contextual fashion alongside other disciplinary content, as dictated by the demands of doing justice to an investigation of the issue, topic or problem. The article illuminates the approach with reference to a case study of a whole-year environmental program. It engages some of the issues raised in recent literature on integrated science curricula, concluding that environmental education might well serve as a useful vehicle for an integrated science education.

Research on seismic signals for vehicle targets and recognition by data fusion

This paper researches seismic signals of typical vehicle targets in order to extract features and to recognize vehicle targets. As a data fusion method, the technique of artificial neural networks combined with genetic algorithm(ANNCGA) is applied for recognition of seismic signals that belong to different kinds of vehicle targets. The technique of ANNCGA and its architecture have been presented. The algorithm had been used for classification and recognition of seismic signals of vehicle targets in the outdoor environment. Through experiments, it can be proven that seismic properties of target acquired are correct, ANNCGA data fusion method is effective to solve the problem of target recognition.

Students' conflicting attitudes towards games as a vehicle for learning mathematics : a methodological dilemma

Mathematics games are widely employed in school classrooms for such reasons as a reward for early finishers or to enhance students' attitude towards mathematics. During a four week period, a total of 222 Grade 5 and 6 (9 to 12 years old) children from Melbourne, Australia, were taught multiplication and division of decimal numbers using calculator games or rich mathematical activities. Likert scale surveys of the children's attitudes towards games as a vehicle for learning mathematics revealed unexpectedly high proportions of negative attitudes at the conclusion of the research. In contrast, student interview data revealed positive associations between games and mathematical learning. This article reports on the methodological dilemma of resultant conflicting attitudinal data related to game- playing. Concerns arising from the divergence in the results are raised in this article. Implications based on the experience of this study may inform educational researchers about future methodological choices involving attitudinal research.

A video-based real-time vehicle detection method by classified background learning

A new two-level real-time vehicle detection method is proposed in order to meet the robustness and efficiency requirements of real world applications. At the high level, pixels of the background image are classified into three categories according to the characteristics of Red, Green, Blue (RGB) curves. The robustness of the classification is further enhanced by using
line detection and pattern connectivity. At the lower level, an exponential forgetting algorithm with adaptive parameters for different categories is utilised to calculate the background and reduce the distortion by the small motion of video cameras. Scene tests show that the proposed method is more robust and faster than previous methods, which is very suitable for real-time vehicle detection in outdoor environments, especially concerning locations where the level of illumination changes frequently and speed detection is important.

A flow control methodology for the rapid generation of vehicle traffic models

This paper presents a conveyor-based methodology to model complex vehicle flows common to factory and distribution warehouse facilities. The AGV and human path modelling techniques available in many commercial discrete event simulation packages require extensive knowledge and time to implement even the simplest flow control rules for multiple vehicle interaction. Although discrete event simulation is accepted as an effective tool to model vehicle delivery movements, human paths and delivery schedules for modern assembly lines, the time to generate accurate models is a significant limitation of existing simulation-based optimisation methodologies. The flow control method has been successfully implemented using two commercial simulation packages. It provides a realistic visual representation, as well as accurate statistical results, and reduces the model development process cost.

Risky driving habits and motor vehicle driver injury

Risky driving is an important cause of motor vehicle injury, but there is a lack of good epidemiological data in this field, particularly data comparing risky driving in younger drivers to those of other age groups. We examined the relationship between risky driving habits, prior traffic convictions and motor vehicle injury using cross-sectional data amongst 21,893 individuals in New Zealand, including 8029 who were aged 16–24 years. Those who reported frequently racing a motor vehicle for excitement or driving at 20 km/h or more over the speed limit, and those who had received traffic convictions over the past 12 months, were between two and four times more likely to have been injured while driving over the same time period. Driving unlicensed was a risk factor for older but not younger drivers, and driving at 20 km/h or more above the speed limits was a stronger risk factor for younger (<25 years) than older drivers. These results confirm the need for interventions targeting risky driving and suggest that different strategies may be required for different high-risk groups.