Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

Proactive management of collision risks in port waters using navigational traffic conflicts

Navigational collisions are one of the major safety concerns in many seaports. To address this safety concern, a comprehensive and structured method of collision risk management is necessary. Traditionally management of port water collision risks has been relied on historical collision data. However, this collision-data-based approach is hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of samples for a sound statistical analysis, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these shortcomings is the navigational traffic conflict technique that uses traffic conflicts as an alternative to the collision data. This paper proposes a collision risk management method by utilizing the principles of this technique. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which, consequently, has great potential for managing collision risks in a fast, reliable and efficient manner.

PARP inhibition induces BAX/BAK-independent synthetic lethality of BRCA1-deficient non-small cell lung cancer

Evasion of apoptosis contributes to both tumourigenesis and drug resistance in non-small cell lung carcinoma (NSCLC). The pro-apoptotic BCL-2 family proteins BAX and BAK are critical regulators of mitochondrial apoptosis. New strategies for targeting NSCLC in a mitochondria-independent manner should bypass this common mechanism of apoptosis block. BRCA1 mutation frequency in lung cancer is low; however, decreased BRCA1 mRNA and protein expression levels have been reported in a significant proportion of lung adenocarcinomas. BRCA1 mutation/deficiency confers a defect in homologous recombination DNA repair that has been exploited by synthetic lethality through inhibition of PARP (PARPi) in breast and ovarian cells; however, it is not known whether this same synthetic lethal mechanism exists in NSCLC cells. Additionally, it is unknown whether the mitochondrial apoptotic pathway is required for BRCA1/PARPi-mediated synthetic lethality. Here we demonstrate that silencing of BRCA1 expression by RNA interference sensitizes NSCLC cells to PARP inhibition. Importantly, this sensitivity was not attenuated in cells harbouring mitochondrial apoptosis block induced by co-depletion of BAX and BAK. Furthermore, we demonstrate that BRCA1 inhibition cannot override platinum resistance, which is often mediated by loss of mitochondrial apoptosis signalling, but can still sensitize to PARP inhibition. Finally we demonstrate the existence of a BRCA1-deficient subgroup (11–19%) of NSCLC patients by analysing BRCA1 protein levels using immunohistochemistry in two independent primary NSCLC cohorts. Taken together, the existence of BRCA1-immunodeficient NSCLC suggests that this molecular subgroup could be effectively targeted by PARP inhibitors in the clinic and that PARP inhibitors could be used for the treatment of BRCA1-immunodeficient, platinum-resistant tumours.

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.

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.

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.

Relating vehicle generated pollutants to urban stormwater quality

Rapid urbanisation and resulting continuous increase in traffic has been recognised as key factors in the contribution of increased pollutant loads to urban stormwater and in turn to receiving waters. Urbanisation primarily increases anthropogenic activities and the percentage of impervious surfaces in urban areas. These processes are collectively responsible for urban stormwater pollution. In this regard, urban traffic and land use related activities have been recognised as the primary pollutant sources. This is primarily due to the generation of a range of key pollutants such as solids, heavy metals and PAHs. Appropriate treatment system design is the most viable approach to mitigate stormwater pollution. However, limited understanding of the pollutant process and transport pathways constrains effective treatment design. This highlights necessity for the detailed understanding of traffic and other land use related pollutants processes and pathways in relation to urban stormwater pollution. This study has created new knowledge in relation to pollutant processes and transport pathways encompassing atmospheric pollutants, atmospheric deposition and build-up on ground surfaces of traffic generated key pollutants. The research study was primarily based on in-depth experimental investigations. This thesis describes the extensive knowledge created relating to the processes of atmospheric pollutant build-up, atmospheric deposition and road surface build-up and establishing their relationships as a chain of processes. The analysis of atmospheric deposition revealed that both traffic and land use related sources contribute total suspended particulate matter (TSP) to the atmosphere. Traffic sources become dominant during weekdays whereas land use related sources become dominant during weekends due to the reduction in traffic sources. The analysis further concluded that atmospheric TSP, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) concentrations are highly influenced by total average daily heavy duty traffic, traffic congestion and the fraction of commercial and industrial land uses. A set of mathematical equation were developed to predict TSP, PAHs and HMs concentrations in the atmosphere based on the influential traffic and land use related parameters. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1.4 ìm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1.4 ìm) travel much longer distances from the source and deposit mainly with the wet deposition. Pollutants in wet deposition are less sensitive to the source characteristics compared to dry deposition. Atmospheric deposition of HMs is not directly influenced by land use but rather by proximity to high emission sources such as highways. Therefore, it is important to consider atmospheric deposition as a key pollutant source to urban stormwater in the vicinity of these types of sources. Build-up was analysed for five different particle size fractions, namely, <1 ìm, 1-75 ìm, 75-150 ìm, 150-300 ìm and >300 ìm for solids, PAHs and HMs. The outcomes of the study indicated that PAHs and HMs in the <75 ìm size fraction are generated mainly by traffic related activities whereas the > 150 ìm size fraction is generated by both traffic and land use related sources. Atmospheric deposition is an important source for HMs build-up on roads, whereas the contribution of PAHs from atmospheric sources is limited. A comprehensive approach was developed to predict traffic and other land use related pollutants in urban stormwater based on traffic and other land use characteristics. This approach primarily included the development of a set of mathematical equations to predict traffic generated pollutants by linking traffic and land use characteristics to stormwater quality through mathematical modelling. The outcomes of this research will contribute to the design of appropriate treatment systems to safeguard urban receiving water quality for future traffic growth scenarios. The „real world. application of knowledge generated was demonstrated through mathematical modelling of solids in urban stormwater, accounting for the variability in traffic and land use characteristics.

Teaching Teachers for the Future (TTF) : building the ICT in education capacity of the next generation of teachers in Australia

The Teaching Teachers for the Future (TTF) project is a unique nationally significant project funded by the Australian Government through the Department of Employment, Education and Workplace Relations (DEEWR, Au$8.8 million) and the Information and Communication Technology Innovation Fund (ICTIF). This 2011-2012 project has ambitiously attempted to build the ICT education (ICTE) capacity of the next generation of Australian teachers through its focus on pre-service teachers, teacher educators and the new Australian Curriculum. This paper will provide an overview of the project including a description of its genesis in a changing educational and political landscape, its structure and operations, its grounding in contemporary theory, the research opportunities it has engendered and its tangible outcomes.

Loss to assets : production of power from speed breaker

In this work, prospect and feasibility of power generation by using speed breakers has been investigated. In this project a mechanism to generate power by converting the potential energy generated by a vehicle going up on a speed breaker into kinetic energy. This arrangement is made one rotation as soon as the vehicle moves over the speed breaker and has been increased using gears. After the production electricity, a storing unit has been used to hoard the generated electricity during the day and will be used during the night. Two prototypes have made using rack and pinion gear, spur gear, springs and generator .From which a considerable amount of energy is obtained. Nonetheless the cost of the prototype was inexpensive which proves the feasibility of this project and the idea can be applied on heavy traffic roads. Further investigation is being carried on to introduce the technology for practical approach.

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.

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.