152 resultados para Rear-End Collisions.


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The process of building safer roads and roadsides needs to be managed to minimise risks to both the road using public and roadworkers. However, detailed and accurate data on fatalities and injuries at roadworks across Australia are not available. The lack of reliable safety records and consequent poor understanding of the hazards at roadworks motivated this research to examine the common trends in incidents and to understand workers' perceptions of the causes of incidents at roadworks. To achieve these aims, 66 roadworks personnel were interviewed in Queensland including road construction workers, traffic controllers, engineers, and managers. Qualitative analyses identified several major issues and themes. Vehicles driving into work areas, traffic controllers hit by vehicles, rear end crashes at roadwork approaches, and reversing incidents involving work vehicles and machinery were the most common types of incidents. Roadworkers perceived driver errors, such as violation of speed limits, distracted driving, and ignoring signage and traffic controllers' instructions as the main causes of the incidents.

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Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

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This study proposes a five-level Z-source diode-clamped inverter designed with two intermediate Z-source networks connected between the dc input sources and rear-end inverter circuitry. By partially shorting the Z-source networks, new operating states not previously reported for two-level Z-source inverter are introduced here for operating the proposed inverter with voltage buck-boost energy conversion ability and five-level phase voltage switching. These characteristic features are in fact always ensured at the inverter terminal output by simply adopting a properly designed carrier modulation scheme, which always inserts two partial shoot-through states per half carrier cycle for smooth balanced operation. Theoretical findings and practical issues identified are eventually verified by constructing a scaled down laboratory prototype for testing.

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Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18 to 26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 seconds in time headway when a driver is engaged in hands-free phone conversation and a 0.75 seconds increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

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Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

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Our survey findings confirm that 11 factors influence information and communication technology (ICT) diffusion for experienced ICT users. We offer a model that consists of 4 groups of categories: management (M); individual (I); technology (T); and environment (E). Our conclusions reinforce the importance of a coherent ICT diffusion strategy and supportive environment. This requires substantial investment in training and collegial learning support mechanisms. This paper provides an overview of the work undertaken and an analysis of its implications for the construction industry and we provide useful insights that a wide range of construction industry professionals and contractors may find useful.

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This chapter deals with the increasing issues surrounding end-of-life decision making. As the life trajectory for older people changes, the need for open discussion about their health problems and treatment becomes more critical. Acceptance of the ageing process itself is often not easy so the matter of a good death is even more distressing for some people to consider. The vignette provides an excellent discussion on the need for open dialogue with the older person and their families, whether they are acutely ill or have chronic health problems. How a person wishes to be treated when quality of life is not going to improve, no matter what interventions are put in place, seems essential for person-centred care. The issue of competency is one that must be determined before any decision is made by any person involved in care.

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Total cross sections for neutron scattering from nuclei, with energies ranging from 10 to 600 MeV and from many nuclei spanning the mass range 6Li to 238U, have been analyzed using a simple, three-parameter, functional form. The calculated cross sections are compared with results obtained by using microscopic (g-folding) optical potentials as well as with experimental data. The functional form reproduces those total cross sections very well. When allowance is made for Ramsauer-like effects in the scattering, the parameters of the functional form required vary smoothly with energy and target mass. They too can be represented by functions of energy and mass.

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We aim to assess the effects of end-of-life care pathways, compared with usual care or with care guided by another end-of-life care pathway across all healthcare settings (hospitals, residential aged care facilities, community). In particular, we aim to assess the effects on symptom severity and quality of life of people who are dying and/or those related to the care such as families, caregivers and health professionals.

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This paper presents effects of end-winding on shaft voltage in AC generators. A variety of design parameters have been considered to calculate the parasitic capacitive couplings in the machine structure with Finite Elements simulations and mathematical calculations. End-winding capacitances have also been calculated to have a precise estimation of shaft voltage and its relationship with design parameters in AC generators.

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Background In many clinical areas, integrated care pathways are utilised as structured multidisciplinary care plans which detail essential steps in caring for patients with specific clinical problems. Particularly, care pathways for the dying have been developed as a model to improve the end-of-life care of all patients. They aim to ensure that the most appropriate management occurs at the most appropriate time and that it is provided by the most appropriate health professional. Clinical pathways for end-of-life care management are used widely around the world and have been regarded as the gold standard. Therefore, there is a significant need for clinicians to be informed about the utilisation of end-of-life care pathways with a systematic review. Objectives To assess the effects of end-of-life care pathways, compared with usual care (no pathway) or with care guided by another end-of-life care pathway across all healthcare settings (e.g. hospitals, residential aged care facilities, community). Search strategy The Cochrane Register of controlled Trials (CENTRAL), the Pain, Palliative and Supportive Care Review group specialised register,MEDLINE, EMBASE, review articles and reference lists of relevant articles were searched. The search was carried out in September 2009. Selection criteria All randomised controlled trials (RCTs), quasi-randomised trial or high quality controlled before and after studies comparing use versus non-use of an end-of-life care pathway in caring for the dying. Data collection and analysis Results of searches were reviewed against the pre-determined criteria for inclusion by two review authors. Main results The search identified 920 potentially relevant titles, but no studies met criteria for inclusion in the review. Authors’ conclusions Without further available evidence, recommendations for the use of end-of-life pathways in caring for the dying cannot be made. RCTs or other well designed controlled studies are needed for evaluating the use of end-of-life care pathways in caring for dying people.