982 resultados para Macadam roads.
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Mode of access: Internet.
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Poor air quality has a huge detrimental effect, both economic and on the quality of life, in Australia. Transit oriented design (TOD), which aims to minimise urban sprawl and lower dependency on vehicles, leads to an increasing number of buildings close to transport corridors. This project aims at providing guidelines that are appropriate to include within City Plan to inform future planning along road corridors, and provide recommendations on when mitigation measures should be utilised.
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The aim of this project is to develop a systematic investment decision-making framework for infrastructure asset management by incorporation economic justification, social and environmental consideration in the decision-making process. This project assesses the factors that are expected to provide significant impacts on the variability of expenditures. A procedure for assessing risk and reliability for project investment appraisals will be developed. The project investigates public perception, social and environmental impacts on road infrastructure investment. This research will contribute to the debate about how important social and environmental issues should be incorporated into the investment decision-making process for infrastructure asset management.
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Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.
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Objective: To define characteristics of vehicle crashes occurring on rural private property in north Queensland with an exploration of associated risk factors. Design: Descriptive analysis of private property crash data collected by the Rural and Remote Road Safety Study. Setting: Rural and remote north Queensland. Participants: A total of 305 vehicle controllers aged 16 years or over hospitalised at Atherton, Cairns, Mount Isa or Townsville for at least 24 hours as a result of a vehicle crash. Main outcome measure: A structured questionnaire completed by participants covering crash details, lifestyle and demographic characteristics, driving history, medical history, alcohol and drug use and attitudes to road use. Results: Overall, 27.9% of interviewees crashed on private property, with the highest proportion of private road crashes occurring in the North West Statistical Division (45%). Risk factors shown to be associated with private property crashes included male sex, riding off-road motorcycle or all-terrain vehicle, first-time driving at that site, lack of licence for vehicle type, recreational use and not wearing a helmet or seatbelt. Conclusions: Considerable trauma results from vehicle crashes on rural private property. These crashes are not included in most crash data sets, which are limited to public road crashes. Legislation and regulations applicable to private property vehicle use are largely focused on workplace health and safety, yet work-related crashes represent a minority of private property crashes in north Queensland.
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Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Particularly, highway design reduces the driving task mainly to a lane-keeping one. It contributes to hypovigilance and road crashes as drivers are often not aware that their driving behaviour is impaired. Monotony increases fatigue, however, the fatigue community has mainly focused on endogenous factors leading to fatigue such as sleep deprivation. This paper focuses on the exogenous factor monotony which contributes to hypovigilance. Objective measurements of the effects of monotonous driving conditions on the driver and the vehicle's dynamics is systematically reviewed with the aim of justifying the relevance of the need for a mathematical framework that could predict hypovigilance in real-time. Although electroencephalography (EEG) is one of the most reliable measures of vigilance, it is obtrusive. This suggests to predict from observable variables the time when the driver is hypovigilant. Outlined is a vision for future research in the modelling of driver vigilance decrement due to monotonous driving conditions. A mathematical model for predicting drivers’ hypovigilance using information like lane positioning, steering wheel movements and eye blinks is provided. Such a modelling of driver vigilance should enable the future development of an in-vehicle device that detects driver hypovigilance in advance, thus offering the potential to enhance road safety and prevent road crashes.
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Driving on motorways has largely been reduced to a lane-keeping task with cruise control. Rapidly, drivers are likely to get bored with such a task and take their attention away from the road. This is of concern in terms of road safety – particularly for professional drivers - since inattention has been identified as one of the main contributing factors to road crashes and is estimated to be involved in 20 to 30% of these crashes. Furthermore, drivers are not aware that their vigilance level has decreased and that their driving performance is impaired. Intelligent Transportation System (ITS) intervention can be used as a countermeasure against vigilance decrement. This paper aims to identify a variety of metrics impacted during monotonous driving - ranging from vehicle data to physiological variables - and relate them to two monotonous factors namely the monotony of the road design (straightness) and the monotony of the environment (landscape, signage, traffic). Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). The two monotonous factors are varied (high and low) leading to the use of four different driving scenarios (40 minutes each). We show with Generalised Linear Mixed Models that driver performance decreases faster when the road is monotonous. We also highlight that road monotony impairs a variety of driving performance and vigilance measures, ranging from speed, lateral position of the vehicle to physiological measurements such as heart rate variability, blink frequency and electrodermal activity. This study informs road designers of the importance of having a varied road environment. It also provides a range of metrics that can be used to detect in real-time the impairment of driving performance on monotonous roads. Such knowledge could result in the development of an in-vehicle device warning drivers at early signs of driving performance impairment on monotonous roads.
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Pedestrian and cyclist injuries are significant public health issues together accounting for 11-30% of road deaths in highly motorised countries. Children are particularly at risk. In Australia in 2009 children 0-16 years comprised 11.4% of pedestrian deaths and 6.4% of cyclist deaths. Parental attitudes and level of supervision are important to children’s road safety. Results from a telephone survey with parents of children 5-9 years (N=147) are reported. Questions addressed beliefs about preventability of injury, appropriate ages for children to cross the road or cycle independently, and the frequency of holding 5-9 year old children’s hands while crossing the road. Results suggest that parents believe most injuries are preventable and that they personally can act to improve their own safety in the home, on the road, at work, as well as in or on the water. Most parents (68%) indicated children should be 10 years or older before crossing the road or cycling independently. Parents were more likely to report holding younger children’s hands (5-6 years) when crossing the road and less likely to do so for 7-9 year olds. There was a small effect of child gender, with parents more likely to hold boy’s hand than a girl’s.
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Safety interventions (e.g., median barriers, photo enforcement) and road features (e.g., median type and width) can influence crash severity, crash frequency, or both. Both dimensions—crash frequency and crash severity—are needed to obtain a full accounting of road safety. Extensive literature and common sense both dictate that crashes are not created equal, with fatalities costing society more than 1,000 times the cost of property damage crashes on average. Despite this glaring disparity, the profession has not unanimously embraced or successfully defended a nonarbitrary severity weighting approach for analyzing safety data and conducting safety analyses. It is argued here that the two dimensions (frequency and severity) are made available by intelligently and reliably weighting crash frequencies and converting all crashes to property-damage-only crash equivalents (PDOEs) by using comprehensive societal unit crash costs. This approach is analogous to calculating axle load equivalents in the prediction of pavement damage: for instance, a 40,000-lb truck causes 4,025 times more stress than does a 4,000-lb car and so simply counting axles is not sufficient. Calculating PDOEs using unit crash costs is the most defensible and nonarbitrary weighting scheme, allows for the simple incorporation of severity and frequency, and leads to crash models that are sensitive to factors that affect crash severity. Moreover, using PDOEs diminishes the errors introduced by underreporting of less severe crashes—an added benefit of the PDOE analysis approach. The method is illustrated with rural road segment data from South Korea (which in practice would develop PDOEs with Korean crash cost data).