Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

Concentration and oxidative potential of on-road particle emissions and their relationship with traffic composition : Relevance to exposure assessment

Particles emitted by vehicles are known to cause detrimental health effects, with their size and oxidative potential among the main factors responsible. Therefore, understanding the relationship between traffic composition and both the physical characteristics and oxidative potential of particles is critical. To contribute to the limited knowledge base in this area, we investigated this relationship in a 4.5 km road tunnel in Brisbane, Australia. On-road concentrations of ultrafine particles (<100 nm, UFPs), fine particles (PM2.5), CO, CO2 and particle associated reactive oxygen species (ROS) were measured using vehicle-based mobile sampling. UFPs were measured using a condensation particle counter and PM2.5 with a DustTrak aerosol photometer. A new profluorescent nitroxide probe, BPEAnit, was used to determine ROS levels. Comparative measurements were also performed on an above-ground road to assess the role of emission dilution on the parameters measured. The profile of UFP and PM2.5 concentration with distance through the tunnel was determined, and demonstrated relationships with both road gradient and tunnel ventilation. ROS levels in the tunnel were found to be high compared to an open road with similar traffic characteristics, which was attributed to the substantial difference in estimated emission dilution ratios on the two roadways. Principal component analysis (PCA) revealed that the levels of pollutants and ROS were generally better correlated with total traffic count, rather than the traffic composition (i.e. diesel and gasoline-powered vehicles). A possible reason for the lack of correlation with HDV, which has previously been shown to be strongly associated with UFPs especially, was the low absolute numbers encountered during the sampling. This may have made their contribution to in-tunnel pollution largely indistinguishable from the total vehicle volume. For ROS, the stronger association observed with HDV and gasoline vehicles when combined (total traffic count) compared to when considered individually may signal a role for the interaction of their emissions as a determinant of on-road ROS in this pilot study. If further validated, this should not be overlooked in studies of on- or near-road particle exposure and its potential health effects.

The increased popularity of mopeds and motor scooters : exploring usage patterns and safety outcomes

Increased use of powered two-wheelers (PTWs) often underlies increases in the number of reported crashes, promoting research into PTW safety. PTW riders are overrepresented in crash and injury statistics relative to exposure and, as such, are considered vulnerable road users. PTW use has increased substantially over the last decade in many developed countries. One such country is Australia, where moped and scooter use has increased at a faster rate than motorcycle use in recent years. Increased moped use is particularly evident in the State of Queensland which is one of four Australian jurisdictions where moped riding is permitted for car licence holders and a motorcycle licence is not required. A moped is commonly a small motor scooter and is limited to a maximum design speed of 50 km/h and a maximum engine cylinder capacity of 50 cubic centimetres. Scooters exceeding either of these specifications are classed as motorcycles in all Australian jurisdictions. While an extensive body of knowledge exists on motorcycle safety, some of which is relevant to moped and scooter safety, the latter PTW types have received comparatively little focused research attention. Much of the research on moped safety to date has been conducted in Europe where they have been popular since the mid 20th century, while some studies have also been conducted in the United States. This research is of limited relevance to Australia due to socio-cultural, economic, regulatory and environmental differences. Moreover, while some studies have compared motorcycles to mopeds in terms of safety, no research to date has specifically examined the differences and similarities between mopeds and larger scooters, or between larger scooters and motorcycles. To address the need for a better understanding of moped and scooter use and safety, the current program of research involved three complementary studies designed to achieve the following aims: (1) develop better knowledge and understanding of moped and scooter usage trends and patterns; and (2) determine the factors leading to differences in moped, scooter and motorcycle safety. Study 1 involved six-monthly observations of PTW types in inner city parking areas of Queensland’s capital city, Brisbane, to monitor and quantify the types of PTW in use over a two year period. Study 2 involved an analysis of Queensland PTW crash and registration data, primarily comparing the police-reported crash involvement of mopeds, scooters and motorcycles over a five year period (N = 7,347). Study 3 employed both qualitative and quantitative methods to examine moped and scooter usage in two components: (a) four focus group discussions with Brisbane-based Queensland moped and scooter riders (N = 23); and (b) a state-wide survey of Queensland moped and scooter riders (N = 192). Study 1 found that of the PTW types parked in inner city Brisbane over the study period (N = 2,642), more than one third (36.1%) were mopeds or larger scooters. The number of PTWs observed increased at each six-monthly phase, but there were no significant changes in the proportions of PTW types observed across study phases. There were no significant differences in the proportions or numbers of PTW type observed by season. Study 2 revealed some important differences between mopeds, scooters and motorcycles in terms of safety and usage through analysis of crash and registration data. All Queensland PTW registrations doubled between 2001 and 2009, but there was an almost fifteen-fold increase in moped registrations. Mopeds subsequently increased as a proportion of Queensland registered PTWs from 1.2 percent to 8.8 percent over this nine year period. Moped and scooter crashes increased at a faster rate than motorcycle crashes over the five year study period from July 2003 to June 2008, reflecting their relatively greater increased usage. Crash rates per 10,000 registrations for the study period were only slightly higher for mopeds (133.4) than for motorcycles and scooters combined (124.8), but estimated crash rates per million vehicle kilometres travelled were higher for mopeds (6.3) than motorcycles and scooters (1.7). While the number of crashes increased for each PTW type over the study period, the rate of crashes per 10,000 registrations declined by 40 percent for mopeds compared with 22 percent for motorcycles and scooters combined. Moped and scooter crashes were generally less severe than motorcycle crashes and this was related to the particular crash characteristics of the PTW types rather than to the PTW types themselves. Compared to motorcycle and moped crashes, scooter crashes were less likely to be single vehicle crashes, to involve a speeding or impaired rider, to involve poor road conditions, or to be attributed to rider error. Scooter and moped crashes were more likely than motorcycle crashes to occur on weekdays, in lower speed zones and at intersections. Scooter riders were older on average (39) than moped (32) and motorcycle (35) riders, while moped riders were more likely to be female (36%) than scooter (22%) or motorcycle riders (7%). The licence characteristics of scooter and motorcycle riders were similar, with moped riders more likely to be licensed outside of Queensland and less likely to hold a full or open licence. The PTW type could not be identified in 15 percent of all cases, indicating a need for more complete recording of vehicle details in the registration data. The focus groups in Study 3a and the survey in Study 3b suggested that moped and scooter riders are a heterogeneous population in terms of demographic characteristics, riding experience, and knowledge and attitudes regarding safety and risk. The self-reported crash involvement of Study 3b respondents suggests that most moped and scooter crashes result in no injury or minor injury and are not reported to police. Study 3 provided some explanation for differences observed in Study 2 between mopeds and scooters in terms of crash involvement. On the whole, scooter riders were older, more experienced, more likely to have undertaken rider training and to value rider training programs. Scooter riders were also more likely to use protective clothing and to seek out safety-related information. This research has some important practical implications regarding moped and scooter use and safety. While mopeds and scooters are generally similar in terms of usage, and their usage has increased, scooter riders appear to be safer than moped riders due to some combination of superior skills and safer riding behaviour. It is reasonable to expect that mopeds and scooters will remain popular in Queensland in future and that their usage may further increase, along with that of motorcycles. Future policy and planning should consider potential options for encouraging moped riders to acquire better riding skills and greater safety awareness. While rider training and licensing appears an obvious potential countermeasure, the effectiveness of rider training has not been established and other options should also be strongly considered. Such options might include rider education and safety promotion, while interventions could also target other road users and urban infrastructure. Future research is warranted in regard to moped and scooter safety, particularly where the use of those PTWs has increased substantially from low levels. Research could address areas such as rider training and licensing (including program evaluations), the need for more detailed and reliable data (particularly crash and exposure data), protective clothing use, risks associated with lane splitting and filtering, and tourist use of mopeds. Some of this research would likely be relevant to motorcycle use and safety, as well as that of mopeds and scooters.

Granule mining and its application for network traffic characterization

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

Sustainable Road Management in Texas : network-level flexible pavement structural condition analysis using data mining techniques

The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.

Workflow patterns put into context

In his paper “Approaches to Modeling Business Processes. A Critical Analysis of BPMN, Workflow Patterns and YAWL”, Egon Börger criticizes the work of the Workflow Patterns Initiative in a rather provocative manner. Although the workflow patterns and YAWL are well established and frequently used, Börger seems to misunderstand the goals and contributions of the Workflow Patterns Initiative. Therefore, we put the workflow patterns and YAWL in their historic context. Moreover, we address some of the criticism of Börger by pointing out the real purpose of the workflow patterns and their relationship to formal languages (Petri nets) and real-life WFM/BPM systems.

A safety adapted car following model for traffic safety studies

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. 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 them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.

Exploring perceived legitimacy of traffic law enforcement

The purpose of traffic law enforcement is to encourage compliant driver behaviour. That is, the threat of an undesirable sanction encourages drivers to comply with traffic laws. However, not all traffic law violations are considered equal. For example, while drink driving is generally seen as socially unacceptable, behaviours such as speeding are arguably less so, and speed enforcement is often portrayed in the popular media as a means of “revenue raising”. The perceived legitimacy of traffic law enforcement has received limited research attention to date. Perceived legitimacy of traffic law enforcement may influence (or be influenced by) attitudes toward illegal driving behaviours, and both of these factors are likely to influence on-road driving behaviour. This study aimed to explore attitudes toward a number of illegal driving behaviours and traffic law enforcement approaches that typically target these behaviours using self-reported data from a large sample of drivers. The results of this research can be used to inform further research in this area, as well as the content of public education and advertising campaigns designed to influence attitudes toward illegal driving behaviours and perceived legitimacy of traffic law enforcement.

Novel methods and the maximum likelihood estimation technique for estimating traffic critical gap

Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.

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.

A new approach for trip generation estimation for use in traffic impact assessments

Findings from an online survey conducted by Queensland University of Technology (QUT) shows that Australia is suffering from a lack of data reflecting trip generation for use in Traffic Impact Assessments (TIAs). Current independent variables for trip generation estimation are not able to create robust outcomes as well. It is also challenging to account for the impact of the new development on public and active transport as well as the effect of trip chaining behaviour in Australian TIA studies. With this background in mind, research is being implemented by QUT to find a new approach developing a combined model of trip generation and mode choice with consideration of trip chaining effects. It is expected that the model will provide transferable outcomes as it is developed based on socio-demographic parameters. Child Care Centres within the Brisbane area have been nominated for model development. At the time, the project is in the data collection phase. Findings from the pilot survey associated with capturing trip chaining and mode choice information reveal that applying questionnaire is able to capture required information in an acceptable level. The result also reveals that several centres within an area should be surveyed in order to provide sufficient data for trip chaining and modal split analysis.

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.

Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

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.