695 resultados para road vehicles


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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.

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Queensland Department of Main Roads, Australia, spends approximately A$ 1 billion annually for road infrastructure asset management. To effectively manage road infrastructure, firstly road agencies not only need to optimise the expenditure for data collection, but at the same time, not jeopardise 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 could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. This paper presents the results of case studies in using the probability-based method for an integrated approach (i.e. assessing optimal costs of pavement strength data collection; calibrating deterioration prediction models that suit local condition and assessing risk-adjusted budget estimates for road maintenance and rehabilitation for assessing life-cycle budget estimates). The probability concept is opening the path to having the means to predict life-cycle maintenance and rehabilitation budget estimates that have a known probability of success (e.g. produce budget estimates for a project life-cycle cost with 5% probability of exceeding). The paper also presents a conceptual decision-making framework in the form of risk mapping in which the life-cycle budget/cost investment could be considered in conjunction with social, environmental and political issues.

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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.

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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.

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Toll plazas are particularly susceptible to build-ups of vehicle-emitted pollutants because vehicles pass through in low gear. To look at this, three-dimensional computational fluid dynamics simulations of pollutant dispersion are used on the standard k e turbulence model. The effects of wind speed, wind direction and topography on pollutant dispersion were discussed. The Wuzhuang toll plaza on the Hefei-Nanjing expressway is considered, and the effects of the retaining walls along both sides of the plaza on pollutant dispersion is analysed. There are greater pollutant concentrations near the tollbooths as the angle between the direction of the wind and traffic increases implying that retaining walls impede dispersion. The slope of the walls has little influence on the variations in pollutant concentration.

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Aims: The Rural and Remote Road Safety Study (RRRSS) addresses a recognised need for greater research on road trauma in rural and remote Australia, the costs of which are disproportionately high compared with urban areas. The 5-year multi-phase study with whole-of-government support concluded in June 2008. Drawing on RRRSS data, we analysed fatal motorcycle crashes which occurred over 39 months to provide a description of crash characteristics, contributing factors and people involved. The descriptive analysis and discussion may inform development of tailored motorcycle safety interventions. Methods: RRRSS criteria sought vehicle crashes resulting in death or hospitalisation for 24 hours minimum of at least 1 person aged 16 years or over, in the study area defined roughly as the Queensland area north from Bowen in the east and Boulia in the west (excluding Townsville and Cairns urban areas). Fatal motorcycle crashes were selected from the RRRSS dataset. Analysis considered medical data covering injury types and severity, evidence of alcohol, drugs and prior medical conditions, as well as crash descriptions supplied by police to Queensland Transport on contributing circumstances, vehicle types, environmental conditions and people involved. Crash data were plotted in a geographic information system (MapInfo) for spatial analysis. Results: There were 23 deaths from 22 motorcycle crashes on public roads meeting RRRSS criteria. Of these, half were single vehicle crashes and half involved 2 or more vehicles. In contrast to general patterns for driver/rider age distribution in crashes, riders below 25 years of age were represented proportionally within the population. Riders in their thirties comprised 41% of fatalities, with a further 36% accounted for by riders in their fifties. 18 crashes occurred in the Far North Statistical Division (SD), with 2 crashes in both the Northern and North West SDs. Behavioural factors comprised the vast majority of contributing circumstances cited by police, with adverse environmental conditions noted in only 4 cases. Conclusions: Fatal motorcycle crashes were more likely to involve another vehicle and less likely to involve a young rider than non-fatal crashes recorded by the RRRSS. Rider behaviour contributed to the majority of crashes and should be a major focus of research, education and policy development, while other road users’ behaviour and awareness also remains important. With 68% of crashes occurring on major and secondary roads within a 130km radius of Cairns, efforts should focus on this geographic area.

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Research has noted a ‘pronounced pattern of increase with increasing remoteness' of death rates in road crashes. However, crash characteristics by remoteness are not commonly or consistently reported, with definitions of rural and urban often relying on proxy representations such as prevailing speed limit. The current paper seeks to evaluate the efficacy of the Accessibility / Remoteness Index of Australia (ARIA+) to identifying trends in road crashes. ARIA+ does not rely on road-specific measures and uses distances to populated centres to attribute a score to an area, which can in turn be grouped into 5 classifications of increasing remoteness. The current paper uses applications of these classifications at the broad level of Australian Bureau of Statistics' Statistical Local Areas, thus avoiding precise crash locating or dedicated mapping software. Analyses used Queensland road crash database details for all 31,346 crashes resulting in a fatality or hospitalisation occurring between 1st July, 2001 and 30th June 2006 inclusive. Results showed that this simplified application of ARIA+ aligned with previous definitions such as speed limit, while also providing further delineation. Differences in crash contributing factors were noted with increasing remoteness such as a greater representation of alcohol and ‘excessive speed for circumstances.' Other factors such as the predominance of younger drivers in crashes differed little by remoteness classification. The results are discussed in terms of the utility of remoteness as a graduated rather than binary (rural/urban) construct and the potential for combining ARIA crash data with census and hospital datasets.

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This paper provides much needed consolidation of the available evidence in relation to the design and evaluation of road safety advertising messages. Drawing upon current knowledge, the paper identifies some key challenges for improving both the persuasiveness of messages and the methods utilised to assess their effectiveness. The paper identifies some key message-related and individual difference factors, such as response efficacy, emotion, gender and involvement, which theoretical and empirical evidence has shown to be key determinants of message persuasiveness. In relation to message evaluation, the paper focuses upon research relating to the direct, persuasive role of advertising as opposed to evaluations of the combined effects of advertising and enforcement. The paper reviews methodological limitations of previous studies and gaps in existing knowledge that together limit the ability to draw accurate and comprehensive conclusions regarding message effectiveness. Overall, this paper provides a significant and timely review of what is currently known about road safety advertising design and evaluation.

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Research has shown that road lane width impacts on driver behaviour. This literature review provides guidelines to assist in the design, construction and retrofitting of urban roads to accommodate road users' safety requirements. It focuses on the impacts of lane widths on cyclists and motor vehicle safety behaviour. The literature review commenced with a search of library databases. Peer reviewed articles and road authority (local, state and national) reports were reviewed. The majority of studies investigating the effects of lane width on driver behaviour were simulator based, while research into cycling safety involved data collected from actual traffic environments. Results show that marked road lane width influences perceived task difficulty, risk perception and possibly speed choice. The positioning of cyclists in traffic lanes is influenced by the presence of on-road cycling facilities and the total roadway width. The lateral displacement between bicycle and vehicle is smallest when a bicycle facility is present. Lower, or reduced, vehicle speeds play a significant role in improving bicyclist and pedestrian safety. It is also shown that if road lane widths in urban areas were reduced, to a functional width that was less than the current guidelines of 3.5m, it could result in a safer road environment for all road users.

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Street racing and associated (hooning) behaviours have attracted increasing concern in recent years. While New Zealand and all Australian jurisdictions have introduced “antihooning” legislation and allocated significant police resources to managing the problem, there is limited evidence of the road safety implications of hooning. However, international and Australian data suggests that drivers charged with a hooning offence tend to be young males who are accompanied by one or more peers, and hooning-related crashes tend to occur at night. In this regard, there is considerable evidence that drivers under the age of 25 are over-represented in crash statistics, and are particularly vulnerable soon after obtaining a Provisional licence, when driving at night, and when carrying peer-aged passengers. The similarity between the nature of hooning offenders, offences and crashes, and road safety risks for young drivers in general, suggests that hooning is an issue that may be viewed as part of the broader young driver problem. Many jurisdictions have recently implemented a range of evidence-based strategies to address young driver road safety, and this paper will present Queensland crash and offence data to highlight the potential benefit of Graduated Driver Licensing initiatives, such as night driving restrictions and peer-aged passenger restrictions, to related road safety issues, including hooning. An understanding of potential flow-on effects is important for evaluations of anti-hooning legislation and Graduated Driver Licensing programs, and may have implications for future law enforcement resource allocation and policy development.

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Vehicle detectors have been installed at approximately every 300 meters on each lane on Tokyo metropolitan expressway. Various traffic data such as traffic volume, average speed and time occupancy are collected by vehicle detectors. We can understand traffic characteristics of every point by comparing traffic data collected at consecutive points. In this study, we focused on average speed, analyzed road potential by operating speed during free-flow conditions, and identified latent bottlenecks. Furthermore, we analyzed effects for road potential by the rainfall level and day of the week. It’s expected that this method of analysis will be utilized for installation of ITS such as drive assist, estimation of parameters for traffic simulation and feedback to road design as congestion measures.

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This paper reports the application of multicriteria decision making techniques, PROMETHEE and GAIA, and receptor models, PCA/APCS and PMF, to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. While PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulphate, sea salt and road dust/soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.

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To explore potential barriers to and facilitators for implementing occupational road safety initiatives, in-depth interviews were conducted with personnel from four major Australian organizations. Twenty-four participants were involved in the interviews comprising 16 front line employees and eight managers. The interviews identified that employees perceived six organizational characteristics as potential barriers to implementing occupational road safety initiatives. These included: prioritisation of production over safety; complacency towards occupational road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. Of these organizational characteristics, prioritisation of production over safety and complacency were the most frequently cited barriers. In regards to facilitators, participants perceived three organizational characteristics as potential facilitators to implementing occupational road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Of these organizational characteristics, management commitment was the most frequently cited facilitator.