Effects of particle size distribution in the response of model granular materials in multi-ring shear

Rail track undergoes complex loading patterns under moving traffic conditions compared to roads due to its continued and discontinued multi-layered structure, including rail, sleepers, ballast layer, sub-ballast layer, and subgrade. Particle size distributions (PSDs) of ballast, subballast, and subgrade layers can be critical in cyclic plastic deformation of rail track under moving traffic on frequent track degradation of rail tracks, especially at bridge transition zones. Conventional test approaches: static shear and cyclic single-point load tests are however unable to replicate actual loading patterns of moving train. Multi-ring shear apparatus; a new type of torsional simple shear apparatus, which can reproduce moving traffic conditions, was used in this study to investigate influence of particle size distribution of rail track layers on cyclic plastic deformation. Three particle size distributions, using glass beads were examined under different loading patterns: cyclic sin-gle-point load, and cyclic moving wheel load to evaluate cyclic plastic deformation of rail track under different loading methods. The results of these tests suggest that particle size distributions of rail track structural layers have significant impacts on cyclic plastic deformation under moving train load. Further, the limitations in con-ventional test methods used in laboratories to estimate the plastic deformation of rail track materials lead to underestimate the plastic deformation of rail tracks.

Factors related to seat belt use : A Turkish case

Seat belts are effective safety devices used to protect car occupants from severe injuries and fatalities during road vehicle accidents. Despite the proven effectiveness of seat belts, seat belt use rates are quite low, especially in developing countries, such as Turkey. The general aim of the present study was to investigate a large variety of factors related to seat belt use among Turkish car occupants using different perspectives and methods and therefore, to contribute to the design of effective seat belt use interventions for increasing seat belt use rates in Turkey. Five sub-studies were conducted within the present study. In the first sub-study, environmental (e.g., road type) and psycho-social factors (e.g., belt use by other car occupants) related to the seat belt use of front-seat occupants were investigated using observation techniques. Being male, of a young age, and traveling on city roads were the main factors negatively related to seat belt use. Furthermore, seat belt use by the drivers and front-seat passengers was highly correlated and a significant predictors of each other. In the second sub-study, the motivations of the car occupants for seat belt use and non-use were investigated using interview techniques. Situational conditions, such as traveling on city roads and for short distances, and not believing in the effectiveness and relevance of seat belt use for safety, were the most frequently reported reasons for not using a seat belt. Safety, habit and avoiding punishment were among the most frequently reported reasons for using a seat belt. In the third sub-study, the Theory of Planned Behavior (TPB) and the Health Belief Model (HBM) were applied to seat belt use using Structural Equation Modeling techniques. The TPB model showed a good fit to the data, whereas the HBM showed a poor fit to the data. Within the TPB model, attitude and subjective norm were significant predictors of intentions to use a seat belt on both urban and rural roads. In the fourth sub-study, seat belt use frequency and motivations for seat belt use among taxi drivers were investigated and compared between free-time and work-time driving using a survey. The results showed that taxi drivers used seat belts more when driving a private car in their free-times compared to when driving a taxi during their work-times. The lack of a legal obligation to use a seat belt in city traffic and fear of being attacked or robbed by the passengers were found as two specific reasons for not using a seat belt when driving a taxi. Lastly, in the fifth sub-study, the relationship of seat belt use to driver and health behaviors was investigated using a survey. Although seat belt use was related both to health and driver behaviors, factor analysis results showed that it grouped with driver behaviors. Based on the results of the sub-studies, a tentative empirical model showing different predictors of seat belt use was proposed. According to the model, safety and normative motivations and perceived physical barriers related to seat belt use are the three important predictors of seat belt use. Keywords: Seat belt use; environmental factors; psycho-social factors; safety and normative motivations; the Theory of Planned Behavior; the Health Belief Model; health behaviors; driver behaviors; front-seat occupants; taxi drivers; Turkey.

Pavement management: Capturing surface treatment effectiveness

Acquiring detailed knowledge of surface treatments effectiveness is required to improve performance-based decisions for allocating resources to preserve and maintain pavements on any road network. Measurement of treatment effectiveness is a complex task that requires historical records of treatments with observations of before and after performance trends. Lack of data is often an obstacle that impedes development and incorporation of surface maintenance treatments into pavement management. This paper analyzes the effect of surface treatments on asphalt paved arterial roads for several control sections of New Brunswick. The method uses a Transition Probability Matrix to capture main effects by mapping mean trends of surface improvement and pavement structure decay. It was found that surface treatments have an immediate effect reducing the rate of loss of structural capacity. Pavements with international roughness index (IRI) smaller than 1.4 m/km did not seem to benefit from surface treatments. Those with IRI higher than 1.66 m/km gained from 6 to 8 years of additional life. Reset value for surface treatments fall between 1.18 and 1.29 m/km. This paper aims to serve to practitioners seeking to capture and incorporate effectiveness of surface treatments (i.e., crack-sealing) into Pavement Management.

Driver sleepiness on YouTube: A content analysis

Driver sleepiness is a major contributor to severe crashes and fatalities on our roads. Many people continue to drive despite being aware of feeling tired. Prevention relies heavily on education campaigns as it is difficult to police driver sleepiness. The video sharing social media site YouTube is extremely popular, particularly with at risk driver demographics. Content and popularity of uploaded videos can provide insight into the quality of publicly accessible driver sleepiness information. The purpose of this research was to answer two questions; firstly, how prevalent are driver sleepiness videos on YouTube? And secondly, what are the general characteristics of driver sleepiness videos in terms of (a) outlook on driver sleepiness, (b) tone, (c) countermeasures to driver sleepiness, and, (d) driver demographics. Using a keywords search, 442 relevant videos were found from a five year period (2nd December 2009–2nd December 2014). Tone, outlook, and countermeasure use were thematically coded. Driver demographic and video popularity data also were recorded. The majority of videos portrayed driver sleepiness as dangerous. However, videos that had an outlook towards driver sleepiness being amusing were viewed more often and had more mean per video comments and likes. Humorous videos regardless of outlook, were most popular. Most information regarding countermeasures to deal with driver sleepiness was accurate. Worryingly, 39.8% of videos with countermeasure information contained some kind of ineffective countermeasure. The use of humour to convey messages about the dangers of driver sleepiness may be a useful approach in educational interventions.

A contemporary assessment of land condition in the Northern Gulf region of Queensland

A framework using assessments of soil condition, pasture composition and woodland density was applied to describe 14 grazing land types as being in A (100% of original carrying capacity), B (75%), C (45%) or D (20%) condition. We assessed the condition of 260 sites, principally along public and some station roads, to provide a benchmark for current land condition. Land types were also assigned relative grazing values between 10 (best) and 0, reflecting soil fertility and potential biomass production. The method identifies particular, 'at-risk' land types for priority investment of resources, while the rationale behind assessments might point to management interventions to improve the condition of those land types. Across all land types, 47% of sites were in A condition, 34% in B condition, 17% in C condition and only 2% in D condition. Seventy-five percent of land types with grazing values >5 were in A or B condition, compared with 88% for those with grazing values ?5. For Georgetown granites, only 27% of sites were in A or B condition, with values for other land types being: alluvials 59%, black soils 64% and red duplex soils 57%, suggesting that improving management of these land types is a priority issue. On land types with high grazing value, the major discounting factor was pasture composition (72% of sites discounted), while increasing woodland density was the main discount (73% of sites discounted) on low grazing value land types.

Mobile assessment of on-road air pollution and its sources along the East-West Highway in Bhutan

Human exposures in transportation microenvironments are poorly represented by ambient stationary monitoring. A number of on-road studies using vehicle-based mobile monitoring have been conducted to address this. Most previous studies were conducted on urban roads in developed countries where the primary emission source was vehicles. Few studies have examined on-road pollution in developing countries in urban settings. Currently, no study has been conducted for roadways in rural environments where a substantial proportion of the population live. This study aimed to characterize on-road air quality on the East-West Highway (EWH) in Bhutan and identify its principal sources. We conducted six mobile measurements of PM10, particle number (PN) count and CO along the entire 570 km length of the EWH. We divided the EWH into five segments, R1-R5, taking the road length between two district towns as a single road segment. The pollutant concentrations varied widely along the different road segments, with the highest concentrations for R5 compared with other road segments (PM10 = 149 µg/m3, PN = 5.74 × 104 particles/cm-3, CO = 0.19 ppm), which is the final segment of the road to the capital. Apart from vehicle emissions, the dominant sources were road works, unpaved roads and roadside combustion activities. Overall, the highest contributions above the background levels were made by unpaved roads for PM10 (6 times background), and vehicle emissions for PN and CO (5 and 15 times background, respectively). Notwithstanding the differences in instrumentation used and particle size range measured, the current study showed lower PN concentrations compared with similar on-road studies. However, concentrations were still high enough that commuters, road maintenance workers and residents living along the EWH, were potentially exposed to elevated pollutant concentrations from combustion and non-combustion sources. Future studies should focus on assessing the dispersion patterns of roadway pollutants and defining the short- and long-term health impacts of exposure in Bhutan, as well as in other developing countries with similar characteristics.

Is night-time wind direction important to best practice wild dog trapping and baiting?

We discovered a significant bias for wild dog scent station spoor (scats and scratches) to be positioned on the north-easterly side of roads and intersections. Counts of this spoor, 50 metres in each direction of north-south and east-west intersections were made in state forests near Roma in southwest Queensland, Cecil Plains on the Darling Downs and Maryborough on the coast during mating season in April/May 2007. While 51% of 190 and 83% of 120 scent station spoor were located on the north-eastern sector of the intersections at Cecil Plains and Roma respectively, spoor were more evenly distributed across all four sectors at Maryborough (n=47).

Evaluation of the Red Light Camera Program and the Owner Onus Legislation

Red light cameras were introduced in Victoria in August 1983, with the intention of reducing the number of accidents that result from motorists disobeying red traffic signals at signalised intersections. Accident data from 46 treated and 46 control sites from 1981 to 1986 were analysed. The analysis indicated that red light camera use resulted in a reduction in the incidence of right angle accidents, and in the number of accident casualties. Legislation was introduced in March 1986 to place the onus for red light camera offences onto the vehicle owner. This legislation was intended to improve Police efficiency and therefore increase the number of red light cameras in operation. Data supplied by the Police indicated that these aims have beneficial road safety effects.

The efficacy and potential risks of controlling sprouting in Finnish birches (Betula spp.) with the fungal decomposer Chondrostereum purpureum

Sprouting of fast-growing broad-leaved trees causes problems in young coniferous stands, under power transmission lines and along roads and railways. Public opinion and the Finnish Forest Certification System oppose the use of chemical herbicides to control sprouting, which means that most areas with problems rely on mechanical cutting. However, cutting is a poor control method for many broad-leaved species because the removal of leaders can stimulate the sprouting of side branches and cut stumps quickly re-sprout. In order to be effective, cutting must be carried out frequently but each cut increases the costs, making this control method increasingly difficult and expensive once begun. As such, alternative methods for sprout control that are both effective and environmentally sound represent a continuing challenge to managers and research biologists. Using biological control agents to prevent sprouting has been given serious consideration recently. Dutch and Canadian researchers have demonstrated the potential of the white-rot fungus Chondrostereum purpureum (Pers. ex Fr.) Pouzar as a control agent of stump sprouting in many hardwoods. These findings have focused the attention of the Finnish forestry community on the utilization of C. purpureum for biocontrol purposes. Primarily, this study sought determines the efficacy of native C. purpureum as an inhibitor of birch stump sprouting in Finland and to clarify its mode of action. Additionally, genotypic variation in Finnish C. purpureum was examined and the environmental risks posed by a biocontrol program using this fungus were assessed. Experimental results of the study demonstrated that C. purpureum clearly affects the sprouting of birch: both the frequency of living stumps and the number of living sprouts per stump were effectively reduced by the treatment. However, the treatment had no effect on the maximum height of new sprouts. There were clear differences among fungal isolates in preventing sprouting and those that possessed high oxidative activities as measured in the laboratory inhibited sprouting most efficiently in the field. The most effective treatment time during the growing season was in early and mid summer (May July). Genetic diversity in Nordic and Baltic populations of C. purpureum was found to be high at the regional scale but locally homogeneous. This natural distribution of diversity means that using local genotypes in biocontrol programs would effectively prevent the introduction of novel genes or genotypes. While a biocontrol program using local strains of C. purpureum would be environmentally neutral, pruned birches that are close to the treatment site would have a high susceptibility to infect by the fungus during the early spring.

Dingoes at the doorstep: Preliminary data on the ecology of dingoes in urban areas

Wild carnivores are becoming increasing common in urban areas. In Australia, dingoes exist, in most large cities and towns within their extended range. However, little empirical data is available to inform dingo management or address potential dingo–human conflicts during urban planning. From GPS tracking data, the nine dingoes, predominately juvenile and female, we tracked lived within 700 m of residential homes at all times and frequently crossed roads, visited backyards and traversed built-up areas. Home range sizes ranged between 0.37 km2 and 100.32 km2. Dingoes were mostly nocturnal, averaging 591 m/h between dusk and dawn. Juvenile and adult dingoes spent up to 19% and 72% of their time in urban habitats. Fresh scats from most areas surveyed tested positive to a variety of common zoonoses. These data suggest dingoes are capable of exploiting peri-urban areas and might contribute to human health and safety risks, the significance of which remains unknown.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

A review of project evaluation methodologies to address net impacts and risks of toll road projects to the community

Project evaluation is a process of measuring costs, benefits, risks and uncertainties for the purpose of decision-making by estimating and assessing impacts of the project to the community. The effects of impacts of toll roads are similar but different from the general non-tolled roads. Project evaluation methodologies are extensively studied and applied to various transport infrastructure projects. However, there is no definitive methodology to evaluate toll roads. This review discusses the impacts of toll roads then reviews the limitations of existing project evaluation methodologies when evaluating toll road impacts. The review identified gaps of knowledge of toll evaluations. First, the treatment of toll in project evaluation, particularly in Cost-Benefit Analysis requires further study to explore the appropriate methodology. Secondly, the project evaluation methodology needs to place strong emphasis on empirically based risk and uncertainty assessment. Addressing the limitations of the existing project evaluation methodologies leads to improvements of the methodology in practical level as well as fills the gap of knowledge of project evaluation for toll roads with respect to net impacts to the community.

A review of project evaluation methodologies for toll road projects

Project evaluation is a process of measuring costs, benefits, risks and uncertainties for the purpose of decision-making by estimating and assessing impacts of the project to the community. The effects of impacts of toll roads are similar but different from the general non-tolled roads. Project evaluation methodologies are extensively studied and applied to various transport infrastructure projects. However, there is no definitive methodology to evaluate toll roads. This review discusses the impacts of toll roads then reviews the limitations of existing project evaluation methodologies when evaluating toll road impacts. The review identified gaps of knowledge of toll evaluations. First, the treatment of toll in project evaluation, particularly in Cost-Benefit Analysis requires further study to explore the appropriate methodology. Secondly, the project evaluation methodology needs to place strong emphasis on empirically based risk and uncertainty assessment. Addressing the limitations of the existing project evaluation methodologies leads to improvements of the methodology in practical level as well as fills the gap of knowledge of project evaluation for toll roads with respect to net impacts to the community.

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

Taxonomy of factors which influence heavy metal build-up on urban road surfaces

Heavy metals build-up on urban road surfaces is a complex process and influenced by a diverse range of factors. Although numerous research studies have been conducted in the area of heavy metals build-up, limited research has been undertaken to rank these factors in terms of their influence on the build-up process. This results in limitations in the identification of the most critical factor/s for accurately estimating heavy metal loads and for designing effective stormwater treatment measures. The research study undertook an in-depth analysis of the factors which influence heavy metals build-up based on data generated from a number of different geographical locations around the world. Traffic volume was found to be the highest ranked factor in terms of influencing heavy metals build-up while land use was ranked the second. Proximity to arterial roads, antecedent dry days and road surface roughness has a relatively lower ranking. Furthermore, the study outcomes advances the conceptual understanding of heavy metals build-up based on the finding that with increasing traffic volume, total heavy metal build-up load increases while the variability decreases. The outcomes from this research study are expected to contribute to more accurate estimation of heavy metals build-up loads leading to more effective stormwater treatment design.