Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Multiple-choice versus short-response items: Differences in omit behavior

The overall rate of omission of items for 28,331 17 year old Australian students on a high stakes test of achievement in the common elements or cognitive skills of the senior school curriculum is reported for a subtest in multiple choice format and a subtest in short response format. For the former, the omit rates were minuscule and there was no significant difference by gender or by type of school attended. For the latter, where an item can be 'worth' up to five times that of a single multiple choice item, the omit rates were between 10 and 20 times that for multiple choice and the difference between male and female omit rate was significant as was the difference between students from government and non-government schools. For both formats, females from single sex schools omitted significantly fewer items than did females from co-educational schools. Some possible explanations of omit behaviour are alluded to.

Identifying programs to reduce road trauma to A.C.T. motorcyclists

A broad range of motorcycle safety programs and systems exist in Australia and New Zealand. These vary from statewide licensing and training systems run by government licensing and transport agencies to safety programs run in small communities and by individual rider groups. While the effectiveness of licensing and training has been reviewed and recommendations for improvement have been developed (e.g. Haworth & Mulvihill, 2005), little is known about many smaller or innovative programs, and their potential to improve motorcycle safety in the ACT.

Opportunities for enhancing the Australian national road safety strategy

With the current National Road Safety Strategy [1] coming to the end of its term, it is timely to consider ways in which the next iteration of this strategy can be enhanced. Strategic planning should be a cyclic process in which learning and adaptation are just as important as planning and implementation. It will always be the case that some actions are not as effective as expected, or that barriers to effective implementation will emerge. Rather than being setbacks, these are opportunities for learning about the validity of our assumptions. They are also opportunities for us to adapt to meet unanticipated or emerging challenges. One of the positive aspects of the implementation of the first and second National Road Safety Strategies has been the willingness of road safety agencies to critically assess progress and to identify where and how actions would be better focused. This has been reflected in the evolving nature of the periodic National Road Safety Action Plans. As the decade of the current Strategy reaches an end, there is a need to take this process further, and undertake a thorough critical evaluation of the Strategy development and implementation. While not an attempt to be exhaustive, the following article will identify some key priorities for consideration as part of this process.

The effect of social support derived from World of Warcraft on negative psychological symptoms

Previous research examining players of Massively-Multiplayer Online Games (MMOGs) suggests that players form meaningful relationships with each other. Other research indicates that people may derive social support from online sources and this social support has been associated with greater wellbeing. This study used an online survey of players (N = 206) of the MMOG “World of Warcraft” (WoW) to examine if social support can be derived from MMOGs, and to examine its relationship with negative psychological symptoms. Players of WoW were found to derive social support from playing and a positive relationship was found between game engagement and levels of in-game social support. Higher levels of in-game social support were associated with fewer negative psychological symptoms, although this effect was not maintained after accounting for social support derived from the offline sources. Additionally, a small subsample of players (N = 21) were identified that played for between 44 and 82 hours per week (M = 63.33). These players had significantly lower levels of offline social support and higher levels of negative symptoms compared to the rest of the sample. This study provides evidence that social support can be derived from MMOGs and the associated potential to promote well being, but also highlights the potential harm from spending excessive hours playing.

At-risk students and classroom engagement : listening to “voices of possibility and hope"

In my work with secondary school students who have disengaged from mainstream classrooms, I have often been surprised at the ways they enthusiastically engage with the projects on offer. They have demonstrated that, in apparent contradiction of their classroom behaviour, they still maintain hope in achieving a positive outcome from education. In a long-running schools-university project employing a “students-as-researchers” approach to investigating educational disadvantage, “at-risk” students have produced high quality results. Naturally, I wanted to know what it was about this sort of pedagogy that seemed to work for them. In this chapter, then, I outline the project and discuss some reasons for disengagement. I then address the features of the project that the participants themselves have identified as being instrumental in their re-engagement with formal education. Finally, I consider how these features may be transposed to maintaining the educational engagement of at-risk students in mainstream classrooms.

Evaluation of valuation of noise amelioration treatments within and outside the road reserve

In urban environments road traffic volumes are increasing and the density of living is becoming higher. As a consequence the urban community is being exposed to increasing levels of road traffic noise. It is also evident that the noise reduction potential of within-the-road-reserve treatments such as noise barriers, mounding and pavement surfacing has been exhausted. This paper presents a strategy that involves the comparison of noise ameliorative treatments both within and outside the road reserve. The noise reduction resulting from the within-the-road-reserve component of treatments has been evaluated using a leading application of the CoRTN Model, developed by the UK Department of Transport 1988 [1], and the outside road reserve treatment has been evaluated in accordance with the Australian Standard 3671, Acoustics – Road traffic noise intrusion – Building sitting and construction [5]. The evaluation of noise treatments has been undertaken using a decision support tool (DST) currently being developed under the research program conducted at RMIT University and Department of Main Roads, Queensland. The case study has been based on data from a real project in Queensland, Australia. The research described here was carried out by the Australian Cooperative Research Centre for Construction Innovation [9], in collaboration with Department of Main Roads, Queensland, Department of Public Works, Queensland, Arup Pty. Ltd., Queensland University of technology and RMIT University.

Creating a proactive decision-support environment in managing road traffic noise

Properly designed decision support environments encourage proactive and objective decision making. The work presented in this paper inquires into developing a decision support environment and a tool to facilitate objective decision making in dealing with road traffic noise. The decision support methodology incorporates traffic amelioration strategies both within and outside the road reserve. The project is funded by the CRC for Construction Innovation and conducted jointly by the RMIT University and the Queensland Department of Main Roads (MR) in collaboration with the Queensland Department of Public Works, Arup Pty Ltd., and the Queensland University of Technology. In this paper, the proposed decision support framework is presented in the way of a flowchart which enabled the development of the decision support tool (DST). The underpinning concept is to establish and retain an information warehouse for each critical road segment (noise corridor) for a given planning horizon. It is understood that, in current practice, some components of the approach described are already in place but not fully integrated and supported. It provides an integrated user-friendly interface between traffic noise modeling software, noise management criteria and cost databases.

Framework for investment decision-making under risk and uncertainty for infrastructure asset management

A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.

Road Asset Management Investment

Australias civil infrastructure assets of roads, bridges, railways, buildings and other structures are worth billions of dollars. To effectively manage road infrastructures, road agencies firstly need to optimise the expenditure for data collection whilst not jeopardising the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates can be accurately calculated. Finally, the prediction of budgets for maintenance and rehabilitation must be reasonably reliable.

On-road ultrafine particle concentration in the M5 East road tunnel, Sydney, Australia

The human health effects following exposure to ultrafine (<100nm) particles (UFPs) produced by fuel combustion, while not completely understood, are generally regarded as detrimental. Road tunnels have emerged as locations where maximum exposure to these particles may occur for the vehicle occupants using them. This study aimed to quantify and investigate the determinants of UFP concentrations in the 4km twin-bore (eastbound and westbound) M5 East tunnel in Sydney, Australia. Sampling was undertaken using a condensation particle counter (CPC) mounted in a vehicle traversing both tunnel bores at various times of day from May through July, 2006. Supplementary measurements were conducted in February, 2008. Over three hundred transects of the tunnel were performed, and these were distributed evenly between the bores. Additional comparative measurements were conducted on a mixed route comprising major roads and shorter tunnels, all within Sydney. Individual trip average UFP concentrations in the M5 East tunnel bores ranged from 5.53 × 104 p cm-3 to 5.95 × 106 p cm-3. Data were sorted by hour of capture, and hourly median trip average (HMA) UFP concentrations ranged from 7.81 × 104 p cm-3 to 1.73 × 106 p cm-3. Hourly median UFP concentrations measured on the mixed route were between 3.71 × 104 p cm-3 and 1.55 × 105 p cm-3. Hourly heavy diesel vehicle (HDV) traffic volume was a very good determinant of UFP concentration in the eastbound tunnel bore (R2 = 0.87), but much less so in the westbound bore (R2 = 0.26). In both bores, the volume of passenger vehicles (i.e. unleaded gasoline-powered vehicles) was a significantly poorer determinant of particle concentration. When compared with similar studies reported previously, the measurements described here were among the highest recorded concentrations, which further highlights the contribution road tunnels may make to the overall UFP exposure of vehicle occupants.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.