952 resultados para crossing the road


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Road safety education is not just about safe driving. Best practice road safety education seeks to improve knowledge and change attitudes relating to being safe, and making sure others are safe on the road. Typical topics might include: • Strengthening attitudes toward safe road use behaviours and avoiding risks • Supporting behaviours to ensure others are safe • Promoting knowledge of traffic rules.

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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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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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Freeway barriers used to be just great slabs of concrete that lined the road to tr and protect nearby residents from the constant rumble of the traffic. But in recent years, their visual appeal has become as important as their practical purpose with architects and designers clamouring to show off their ideas to the vast traveling public. Melbourne's Craigieburn Bypass is the latest to be recognised for its dual appeal winning the Urban Design Award at the recent Victorian Architecture Awards.

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A continuing challenge for pre-service teacher education is the learning transfer between the university based components and the practical school based components of their training. It is not clear how easily pre-service teachers can transfer university learnings into ‘in school’ practice. Similarly, it is not clear how easily knowledge learned in the school context can be disembedded from this particular context and understood more generally by the pre-service teacher. This paper examines the effect of a community of practice formed specifically to explore learning transfer via collaboration and professional enquiry, in ‘real time’, across the globe. “Activity Theory” (Engestrom, 1999) provided the theoretical framework through which the cognitive, physical and social processes involved could be understood. For the study, three activity systems formed community of practice network. The first activity system involved pre-service teachers at a large university in Queensland, Australia. The second activity system was introduced by the pre-service teachers and involved Year 12 students and teachers at a private secondary school also in Queensland, Australia. The third activity system involved university staff engineers at a large university in Pennsylvania, USA. The common object among the three activity systems was to explore the principles and applications of nanotechnology. The participants in the two Queensland activity systems, controlled laboratory equipment (a high powered Atomic Force Microscope – CPII) in Pennsylvania, USA, with the aim of investigating surface topography and the properties of nano particles. The pre-service teachers were to develop their remote ‘real time’ experience into school classroom tasks, implement these tasks, and later report their findings to other pre-service teachers in the university activity system. As an extension to the project, the pre-service teachers were invited to co-author papers relating to the project. Data were collected from (a) reflective journals; (b) participant field notes – a pre-service teacher initiative; (c) surveys – a pre-service teacher initiative; (d) lesson reflections and digital recordings – a pre-service teacher initiative; and (e) interviews with participants. The findings are reported in terms of the major themes: boundary crossing, the philosophy of teaching, and professional relationships The findings have implications for teacher education. The researchers feel that deliberate planning for networking between activity systems may well be a solution to the apparent theory/practice gap. Proximity of activity systems need not be a hindering issue.

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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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The continued growth in popularity of motorcycling is an area of concern within the road safety domain due to the vulnerability of motorcyclists sustaining injury in the event of a crash. Currently in Australia only motorcycle helmets are mandatory for motorcyclists or pillions to wear and there is no legislative standard for other protective apparel. This paper reports the results obtained from a series of motorcyclists’ apparel observational studies undertaken in the Brisbane and Canberra regions. The sites selected for the research were designed to enable the observation of both recreational and commuter riders. The results highlight both similarities and differences in the type of protective apparel worn by motorcyclists and pillions observed across the two regions. Encouragingly, across all the sites the majority of riders were wearing protective apparel on their upper body. However, a lower proportion of riders were observed wearing protective apparel on their lower body, particularly at the commuter sites in Brisbane. Similarly, the wearing of full face helmets was very high, except at the commuter sites in Brisbane. The generally lower use of protective apparel among commuter riders in Brisbane would appear to reflect both situational factors, such as climate, and the higher proportion of scooters observed at the sites. The implications of these results are discussed and recommendations are made for future research to identify factors that influence the wearing of protective motorcycle apparel.

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Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

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The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

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With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

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Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

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Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

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Presbyopia affects individuals from the age of 45 years onwards, resulting in difficulty in accurately focusing on near objects. There are many optical corrections available including spectacles or contact lenses that are designed to enable presbyopes to see clearly at both far and near distances. However, presbyopic vision corrections also disturb aspects of visual function under certain circumstances. The impact of these changes on activities of daily living such as driving are, however, poorly understood. Therefore, the aim of this study was to determine which aspects of driving performance might be affected by wearing different types of presbyopic vision corrections. In order to achieve this aim, three experiments were undertaken. The first experiment involved administration of a questionnaire to compare the subjective driving difficulties experienced when wearing a range of common presbyopic contact lens and spectacle corrections. The questionnaire was developed and piloted, and included a series of items regarding difficulties experienced while driving under day and night-time conditions. Two hundred and fifty five presbyopic patients responded to the questionnaire and were categorised into five groups, including those wearing no vision correction for driving (n = 50), bifocal spectacles (BIF, n = 54), progressive addition lenses spectacles (PAL, n = 50), monovision (MV, n = 53) and multifocal contact lenses (MTF CL, n = 48). Overall, ratings of satisfaction during daytime driving were relatively high for all correction types. However, MV and MTF CL wearers were significantly less satisfied with aspects of their vision during night-time than daytime driving, particularly with regard to disturbances from glare and haloes. Progressive addition lens wearers noticed more distortion of peripheral vision, while BIF wearers reported more difficulties with tasks requiring changes in focus and those who wore no vision correction for driving reported problems with intermediate and near tasks. Overall, the mean level of satisfaction for daytime driving was quite high for all of the groups (over 80%), with the BIF wearers being the least satisfied with their vision for driving. Conversely, at night, MTF CL wearers expressed the least satisfaction. Research into eye and head movements has become increasingly of interest in driving research as it provides a means of understanding how the driver responds to visual stimuli in traffic. Previous studies have found that wearing PAL can affect eye and head movement performance resulting in slower eye movement velocities and longer times to stabilize the gaze for fixation. These changes in eye and head movement patterns may have implications for driving safety, given that the visual tasks for driving include a range of dynamic search tasks. Therefore, the second study was designed to investigate the influence of different presbyopic corrections on driving-related eye and head movements under standardized laboratory-based conditions. Twenty presbyopes (mean age: 56.1 ± 5.7 years) who had no experience of wearing presbyopic vision corrections, apart from single vision reading spectacles, were recruited. Each participant wore five different types of vision correction: single vision distance lenses (SV), PAL, BIF, MV and MTF CL. For each visual condition, participants were required to view videotape recordings of traffic scenes, track a reference vehicle and identify a series of peripherally presented targets while their eye and head movements were recorded using the faceLAB® eye and head tracking system. Digital numerical display panels were also included as near visual stimuli (simulating the visual displays of a vehicle speedometer and radio). The results demonstrated that the path length of eye movements while viewing and responding to driving-related traffic scenes was significantly longer when wearing BIF and PAL than MV and MTF CL. The path length of head movements was greater with SV, BIF and PAL than MV and MTF CL. Target recognition was less accurate when the near stimulus was located at eccentricities inferiorly and to the left, rather than directly below the primary position of gaze, regardless of vision correction type. The third experiment aimed to investigate the real world driving performance of presbyopes while wearing different vision corrections measured on a closed-road circuit at night-time. Eye movements were recorded using the ASL Mobile Eye, eye tracking system (as the faceLAB® system proved to be impractical for use outside of the laboratory). Eleven participants (mean age: 57.25 ± 5.78 years) were fitted with four types of prescribed vision corrections (SV, PAL, MV and MTF CL). The measures of driving performance on the closed-road circuit included distance to sign recognition, near target recognition, peripheral light-emitting-diode (LED) recognition, low contrast road hazards recognition and avoidance, recognition of all the road signs, time to complete the course, and driving behaviours such as braking, accelerating, and cornering. The results demonstrated that driving performance at night was most affected by MTF CL compared to PAL, resulting in shorter distances to read signs, slower driving speeds, and longer times spent fixating road signs. Monovision resulted in worse performance in the task of distance to read a signs compared to SV and PAL. The SV condition resulted in significantly more errors made in interpreting information from in-vehicle devices, despite spending longer time fixating on these devices. Progressive addition lenses were ranked as the most preferred vision correction, while MTF CL were the least preferred vision correction for night-time driving. This thesis addressed the research question of how presbyopic vision corrections affect driving performance and the results of the three experiments demonstrated that the different types of presbyopic vision corrections (e.g. BIF, PAL, MV and MTF CL) can affect driving performance in different ways. Distance-related driving tasks showed reduced performance with MV and MTF CL, while tasks which involved viewing in-vehicle devices were significantly hampered by wearing SV corrections. Wearing spectacles such as SV, BIF and PAL induced greater eye and head movements in the simulated driving condition, however this did not directly translate to impaired performance on the closed- road circuit tasks. These findings are important for understanding the influence of presbyopic vision corrections on vision under real world driving conditions. They will also assist the eye care practitioner to understand and convey to patients the potential driving difficulties associated with wearing certain types of presbyopic vision corrections and accordingly to support them in the process of matching patients to optical corrections which meet their visual needs.

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This literature review examines the relationship between traffic lane widths on the safety of road users. It focuses on the impacts of lane widths on motor vehicle behaviour and cyclists’ safety. The review commenced with a search of available databases. Peer reviewed articles and road authority reports were reviewed, as well as current engineering guidelines. Research shows that traffic lane width influences drivers’ perceived difficulty of the task, risk perception and possibly speed choices. Total roadway width, and the presence of onroad cycling facilities, influence cyclists’ positioning on the road. Lateral displacement between bicycles and vehicles is smallest when a marked bicycle facility is present. Reduced motor vehicle speeds can significantly improve the safety of vulnerable road users, particularly pedestrians and cyclists. It has been shown that if road lane widths on urban roads were reduced, through various mechanisms, it could result in a safety environment for all road users.

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The contribution of risky behaviour to the increased crash and fatality rates of young novice drivers is recognised in the road safety literature around the world. Exploring such risky driver behaviour has led to the development of tools like the Driver Behaviour Questionnaire (DBQ) to examine driving violations, errors, and lapses [1]. Whilst the DBQ has been utilised in young novice driver research, some items within this tool seem specifically designed for the older, more experienced driver, whilst others appear to asses both behaviour and related motives. The current study was prompted by the need for a risky behaviour measurement tool that can be utilised with young drivers with a provisional driving licence. Sixty-three items exploring young driver risky behaviour developed from the road safety literature were incorporated into an online survey. These items assessed driver, passenger, journey, car and crash-related issues. A sample of 476 drivers aged 17-25 years (M = 19, SD = 1.59 years) with a provisional driving licence and matched for age, gender, and education were drawn from a state-wide sample of 761 young drivers who completed the survey. Factor analysis based upon a principal components extraction of factors was followed by an oblique rotation to investigate the underlying dimensions to young novice driver risky behaviour. A five factor solution comprising 44 items was identified, accounting for 55% of the variance in young driver risky behaviour. Factor 1 accounted for 32.5% of the variance and appeared to measure driving violations that were transient in nature - risky behaviours that followed risky decisions that occurred during the journey (e.g., speeding). Factor 2 accounted for 10.0% of variance and appeared to measure driving violations that were fixed in nature; the risky decisions being undertaken before the journey (e.g., drink driving). Factor 3 accounted for 5.4% of variance and appeared to measure misjudgment (e.g., misjudged speed of oncoming vehicle). Factor 4 accounted for 4.3% of variance and appeared to measure risky driving exposure (e.g., driving at night with friends as passengers). Factor 5 accounted for 2.8% of variance and appeared to measure driver emotions or mood (e.g., anger). Given that the aim of the study was to create a research tool, the factors informed the development of five subscales and one composite scale. The composite scale had a very high internal consistency measure (Cronbach’s alpha) of .947. Self-reported data relating to police-detected driving offences, their crash involvement, and their intentions to break road rules within the next year were also collected. While the composite scale was only weakly correlated with self-reported crashes (r = .16, p < .001), it was moderately correlated with offences (r = .26, p < .001), and highly correlated with their intentions to break the road rules (r = .57, p < .001). Further application of the developed scale is needed to confirm the factor structure within other samples of young drivers both in Australia and in other countries. In addition, future research could explore the applicability of the scale for investigating the behaviour of other types of drivers.