Epidemiological study of the impact of Whiplash on subsequent driver safety

This research project involved two studies aimed to determine whether drivers who have experienced a traffic crash resulting in a Whiplash Associated Disorder (WAD) are at an elevated risk of a subsequent traffic crash. Using data and records held by the Queensland Motor Accident Insurance Commission (MAIC) and Queensland Transport Crash Database (QTCD) the first study examined the crash involvement of two samples of drivers subsequent to a crash in which a compensable injury was incurred. One sample was of persons who had suffered a WAD, the second of persons with a soft tissue injury of equivalent severity. Since differentially altered driving exposure following the relevant injury in the two groups could be a potential confound, in the second study such exposure was estimated using survey data obtained from a sample of similarly injured drivers. These studies were supplemented by a brief analysis of qualitative data drawn from open-ended questions in the survey. In addition a comprehensive review of the literature on impaired driving due to similar medical conditions was undertaken and is reported.

Impact and energy absorption of road safety barriers by coupled SPH/FEM

Road safety barriers are used to minimise the severity of road accidents and protect lives and property. There are several types of barrier in use today. This paper reports the initial phase of research carried out to study the impact response of portable water-filled barrier (PWFB) which has the potential to absorb impact energy and hence provide crash mitigation under low to moderate speeds. Current research on the impact and energy absorption capacity of water-filled road safety barriers is limited due to the complexity of fluid-structure interaction under dynamic impact. In this paper, a novel fluid-structure interaction method is developed based on the combination of Smooth Particle Hydrodynamics (SPH) and Finite Element Method (FEM). The sloshing phenomenon of water inside a PWFB is investigated to explore the energy absorption capacity of water under dynamic impact. It was found that water plays an important role in energy absorption. The coupling analysis developed in this paper will provide a platform to further the research in optimising the behaviour of the PWFB. The effect of the amount of water on its energy absorption capacity is investigated and the results have practical applications in the design of PWFBs.

Navigational Safety in Port Waters : Proactive Management of Collision Risk Using Traffic Conflicts

Traditionally navigational safety analyses rely on historical collision data which is often hampered because of low collision counts, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these problems is using navigational traffic conflicts or near-misses as an alternative to the collision data. This book discusses how traffic conflicts can effectively be used in modeling of port water collision risks. Techniques for measuring and predicting collision risks in fairways, intersections, and anchorages are discussed by utilizing advanced statistical models. Risk measurement models, which quantitatively measure collision risks in waterways, are discussed. To predict risks, a hierarchical statistical modeling technique is discussed which identifies the factors influencing the risks. The modeling techniques are illustrated for Singapore port data. Results showed that traffic conflicts are an ethically appealing alternative to collision data for fast, reliable and effective safety assessment, thus possessing great potential for managing collision risks in port waters.

Context-aware rate-adaptive beaconing for efficient and scalable vehicular safety communication

Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.

Integrating driving and traffic simulators to study railway level crossing safety interventions : a methodology

Safety at Railway Level Crossings (RLXs) is an important issue within the Australian transport system. Crashes at RLXs involving road vehicles in Australia are estimated to cost $10 million each year. Such crashes are mainly due to human factors; unintentional errors contribute to 46% of all fatal collisions and are far more common than deliberate violations. This suggests that innovative intervention targeting drivers are particularly promising to improve RLX safety. In recent years there has been a rapid development of a variety of affordable technologies which can be used to increase driver’s risk awareness around crossings. To date, no research has evaluated the potential effects of such technologies at RLXs in terms of safety, traffic and acceptance of the technology. Integrating driving and traffic simulations is a safe and affordable approach for evaluating these effects. This methodology will be implemented in a driving simulator, where we recreated realistic driving scenario with typical road environments and realistic traffic. This paper presents a methodology for evaluating comprehensively potential benefits and negative effects of such interventions: this methodology evaluates driver awareness at RLXs , driver distraction and workload when using the technology . Subjective assessment on perceived usefulness and ease of use of the technology is obtained from standard questionnaires. Driving simulation will provide a model of driving behaviour at RLXs which will be used to estimate the effects of such new technology on a road network featuring RLX for different market penetrations using a traffic simulation. This methodology can assist in evaluating future safety interventions at RLXs.

Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX.

A simulated annealing algorithm for energy efficient virtual machine placement

Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Fatalism and its implications for risky road use and receptiveness to safety messages : a qualitative investigation in Pakistan

Given the increasing vehicle numbers and expanding road construction in developing countries, the importance of safe road user behaviour is critical. Road traffic crashes (RTC) are a significant problem in Pakistan, however the factors that contribute to RTC in Pakistan are not well-researched. Fatalistic beliefs are a potential barrier to the enhancement of road safety, especially participation in health-promoting and injury prevention behaviours, and also contribute to risk-taking. Fatalistic beliefs relating to road safety have been found in some developing countries, although again research is scarce and indicates that the nature and extent of fatalism differs in each country. Qualitative research was undertaken with a range of drivers, religious orators, police and policy makers to explore associations between fatalism, risky road use and associated issues. Findings indicate that fatalistic beliefs are pervasive in Pakistan, are strongly linked with religion, present a likely barrier to road safety messages and contribute to risky road use. Fatalism appears to be a default attribution of RTC and the intensity of belief in fate surpasses the kinds of fatalism noted in the limited existing literature. These findings have importance to developing road safety countermeasures in countries where fatalistic beliefs are strong.

Perceptions of clinical safety climate of the multicultural nursing workforce in Saudi Arabia : a cross-sectional survey

Purpose The purpose of this study is to explore the safety climate perceptions of the multicultural nursing workforce, and to investigate the influence of diversity of the multicultural nursing workforce on clinical safety in a large tertiary hospital in Saudi Arabia. Background Working in a multicultural environment is challenging. Each culture has its own unique characteristics and dimensions that shape the language, lifestyle, beliefs, values, customs, traditions, and patterns of behaviour, which expatriate nurses must come to terms with. However, cultural diversity in the health care environment can potentially affect the quality of care and patient safety. Method A mixed-method case study (survey, interview and document analysis) was employed. A primary study phase entailed the administration of the Safety Climate Survey (SCS). A population sampling strategy was used and 319 nurses participated, yielding a 76.8% response rate. Descriptive and inferential statistics (Kruskal–Wallis test) were used to analyse survey data. Results The data revealed the nurses’ perceptions of the clinical safety climate in this multicultural environment was unsafe, with a mean score of 3.9 out of 5. No significant difference was found between the age groups, years of nursing experience and their perceptions of the safety climate in this context. A significant difference was observed between the national background categories of nurses and perceptions of safety climate. Conclusion Cultural diversity within the nursing workforce could have a significant influence on perceptions of clinical safety. These findings have the potential to inform policy and practice related to cultural diversity in Saudi Arabia.

Evaluation of the GHR car following model for traffic safety studies

Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

The benefits of tree-based models for stock selection

The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making...

A hybrid approach to combining CART and logistic regression for stock ranking

The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...

Multiuser virtual safety training system for tower crane dismantlement

Tower crane dismantling is one of the most dangerous activities in the construction industry. Tower crane erection and dismantlement causes 10–12% of the fatalities of all crane accidents. The nature of the task is such that off-the-job training is not practicable, and the knowledge and expertise needed has to be gained on the job. However, virtual trainers such as Microsoft Flight Simulator for airplane pilots and mission rehearsal exercise (MRE) for army personnel have been developed and are known to provide a highly successful means of overcoming the risks involved in such on-the-job learning and clearly have potential in construction situations. This paper describes the newly developed multiuser virtual safety training system (MVSTS) aimed at providing a similar learning environment for those involved in tower crane dismantlement. The proposed training system is developed by modifying an existing game engine. Within the close-to-reality virtual environment, trainees can participate in a virtual dismantling process. During the process, they learn the correct dismantling procedure and working location and to cooperate with other trainees by virtually dismantling the crane. The system allows the trainees to experience the complete procedure in a risk-free environment. A case study is provided to demonstrate how the system works and its practical application. The proposed system was evaluated by interviews with 30 construction experts with different backgrounds, divided into three groups according to their experience and trained by the traditional and virtual methods, respectively. The results indicate that the trainees of the proposed system generally learned better than those using the traditional method. The ratings also indicate that the system generally has great potential as a training platform.

Positive impacts of environmental characteristics on health and wellbeing in health-care facilities : a review

Well-designed indoor environments can support people’s health and welfare. In this literature review, we identify the environmental features that affect human health and wellbeing. Environmental characteristics found to influence health outcomes and/or wellbeing included: environmental safety; indoor air quality (e.g. odour and temperature); sound and noise; premises and interior design (e.g. construction materials, viewing nature and experiencing nature, windows versus no windows, light, colours, unit layout and placement of the furniture, the type of room, possibilities to control environmental elements, environmental complexity and sensory simulations, cleanliness, ergonomics and accessibility, ‛‛wayfinding’’); art, and music, among others. Indoor environments that incorporate healing elements can, for instance, reduce anxiety, lower blood pressure, lessen pain and shorten hospital stays.