997 resultados para crash


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Sleep-related (SR) crashes are an endemic problem the world over. However, police officers report difficulties in identifying sleepiness as a crash contributing factor. One approach to improving the sensitivity of SR crash identification is by applying a proxy definition post hoc to crash reports. To identify the prominent characteristics of SR crashes and highlight the influence of proxy definitions, ten years of Queensland (Australia) police reports of crashes occurring in ≥100 km/h speed zones were analysed. In Queensland, two approaches are routinely taken to identifying SR crashes. First, attending police officers identify crash causal factors; one possible option is ‘fatigue/fell asleep’. Second, a proxy definition is applied to all crash reports. Those meeting the definition are considered SR and added to the police-reported SR crashes. Of the 65,204 vehicle operators involved in crashes 3449 were police-reported as SR. Analyses of these data found that male drivers aged 16–24 years within the first two years of unsupervised driving were most likely to have a SR crash. Collision with a stationary object was more likely in SR than in not-SR crashes. Using the proxy definition 9739 (14.9%) crashes were classified as SR. Using the proxy definition removes the findings that SR crashes are more likely to involve males and be of high severity. Additionally, proxy defined SR crashes are no less likely at intersections than not-SR crashes. When interpreting crash data it is important to understand the implications of SR identification because strategies aimed at reducing the road toll are informed by such data. Without the correct interpretation, funding could be misdirected. Improving sleepiness identification should be a priority in terms of both improvement to police and proxy reporting.

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Curves are a common feature of road infrastructure; however crashes on road curves are associated with increased risk of injury and fatality to vehicle occupants. Countermeasures require the identification of contributing factors. However, current approaches to identifying contributors use traditional statistical methods and have not used self-reported narrative claim to identify factors related to the driver, vehicle and environment in a systemic way. Text mining of 3434 road-curve crash claim records filed between 1 January 2003 and 31 December 2005 at a major insurer in Queensland, Australia, was undertaken to identify risk levels and contributing factors. Rough set analysis was used on insurance claim narratives to identify significant contributing factors to crashes and their associated severity. New contributing factors unique to curve crashes were identified (e.g., tree, phone, over-steer) in addition to those previously identified via traditional statistical analysis of Police and licensing authority records. Text mining is a novel methodology to improve knowledge related to risk and contributing factors to road-curve crash severity. Future road-curve crash countermeasures should more fully consider the interrelationships between environment, the road, the driver and the vehicle, and education campaigns in particular could highlight the increased risk of crash on road-curves.

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The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

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Among the human factors that influence safe driving, visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the effect of visual functions of drivers in India on their road crash involvement. Experiments were conducted to assess vision functions of Indian licensed drivers belonging to various organizations, age groups and driving experience. The test results were further related to the crash involvement histories of drivers through statistical tools. A generalized linear model was developed to ascertain the influence of these traits on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision, depth perception, contrast sensitivity, acuity and phoria were found to influence their crash involvement rates. In India, there are no efficient standards and testing methods to assess the visual capabilities of drivers during their licensing process and this study highlights the need for the same.

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190 p.

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In the first part of this paper we show that a new technique exploiting 1D correlation of 2D or even 1D patches between successive frames may be sufficient to compute a satisfactory estimation of the optical flow field. The algorithm is well-suited to VLSI implementations. The sparse measurements provided by the technique can be used to compute qualitative properties of the flow for a number of different visual tsks. In particular, the second part of the paper shows how to combine our 1D correlation technique with a scheme for detecting expansion or rotation ([5]) in a simple algorithm which also suggests interesting biological implications. The algorithm provides a rough estimate of time-to-crash. It was tested on real image sequences. We show its performance and compare the results to previous approaches.

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Barker, M.; Arthurs, J. and Harindranath, R. (Eds.). (2001). Controversy: Censorship Campaigns and Film Reception. London: Wallflower Press. RAE2008

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This thesis argues that through the prism of America’s Cold War, scientism has emerged as the metanarrative of the postnuclear age. The advent of the bomb brought about a new primacy for mechanical and hyperrational thinking in the corridors of power not just in terms of managing the bomb itself but diffusing this ideology throughout the culture in social sciences, economics and other such institutional systems. The human need to mitigate or ameliorate against the chaos of the universe lies at the heart of not just religious faith but in the desire for perfect control. Thus there has been a transference of power from religious faith to the apparent material power of science and technology and the terra firma these supposedly objective means supply. The Cold War, however was a highly ideologically charged opposition between the two superpowers, and the scientific methodology that sprang forth to manage the Cold War and the bomb, in the United States, was not an objective scientific system divorced from the paranoia and dogma but a system that assumed a radically fundamentalist idea of capitalism. This is apparent in the widespread diffusion of game theory throughout Western postindustrial institutions. The inquiry of the thesis thus examines the texts that engage and criticise American Cold War methodology, beginning with the nuclear moment, so to speak, and Dr Strangelove’s incisive satire of moral abdication to machine processes. Moving on chronologically, the thesis examines the diffusion of particular kinds of masculinity and sexuality in postnuclear culture in Crash and End Zone and finishing up its analysis with the ethnographic portrayal of a modern American city in The Wire. More than anything else, the thesis wishes to reveal to what extent this technocratic consciousness puts pressure on language and on binding narratives.

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Full-scale furnished cabin fires have been studied experimentally for the purpose of characterising the post-crash cabin fire environment by the US Federal Aviation Administration for many years. In this paper the Computational Fluid Dynamics fire field model SMARTFIRE is used to simulate one of these fires conducted in the C-133 test facility in order to provide further validation of the computational approach and the SMARTFIRE software. The experiment involves exposing the interior cabin materials to an external fuel fire, opening only one exit at the far end of the cabin (the same side as the rupture) for ventilation, and noting the subsequent spread of the external fire to the cabin interior and the onset of flashover at approximately 210 seconds. Through this analysis, the software is shown to be in good agreement with the experimental data, producing reasonable agreement with the fire dynamics prior to flashover and producing a reasonable prediction of the flashover time i.e. 225 seconds. The paper then proceeds to utilize the model to examine the impact on flashover time of the extent of cabin furnishings and cabin ventilation provided by available exits

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In the current paper, the authors present an analysis of the structural characteristics of an intermediate rail vehicle and their effects on crash performance of the vehicle. Theirs is a simulation based analysis involving four stages. First, the crashworthiness of the vehicle is assessed by simulating an impact of the vehicle with a rigid wall. Second, the structural characteristics of the vehicle are analysed based on the structural behaviour during this impact and then the structure is modified. Third, the modified vehicle is tested again in the same impact scenario with a rigid wall. Finally, the modified vehicle is subjected to a modelled head-on impact which mirrors the real-life impact interface between two intermediate vehicles in a train impact. The emphasis of the current study is on the structural characteristics of the intermediate vehicle and the differences compared to an impact of a leading vehicle. The study shows that, similar to a leading vehicle, bending, or jackknifing is a main form of failure in this conventionally designed intermediate vehicle. It has also been found that the location of the door openings creates a major difference in the behaviour of an intermediate vehicle. It causes instability of the vehicle in the door area and leads to high stresses at the joint of the end beam with the solebar and shear stresses at the joint of the inner pillar with the cantrail. Apart from this, the shapes of the vehicle ends and impact interfaces are also different and have an effect on the crash performance of the vehicles. The simulation results allow the identification of the structural characteristics and show the effectiveness of relevant modifications. The conclusions have general relevance for the crashworthiness of rail vehicle design

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The SMARTFIRE Computational Fluid Dynamics (CFD) fire field model has successfully reproduced the observed characteristics including measured temperatures, species concentrations and time to flashover for a post-crash fire experiment conducted by the FAA within their C-133 cabin test facility. In this test only one exit was open in order to provide ventilation for the developing cabin fire. In real post-crash fires, many exits are likely to be open as passangers attempt to evacuate. In this paper, the likely impacts on evacuation of a post-crash fire in which various exiting combinations are available are investigated. The fire scenario, investigated using the SMARTFIRE software, is based on the C-133 experiment but with a fully furnished cabin and with four different exit availability options. The fire data is imported into the airEXODUS evacuation simulation software and the resulting evacuations examined. The combined fire and evacuation analysis reveals that even though the aircraft configuration is predicted to comfortably satisfy the evacuation certification requirement, when fire is included, a number of casualties result, even from the certification compliant exit configuration.

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This paper presents a comparison of impact dynamic performance between articulated trains and non-articulated trains. This is carried out by investigation of the characteristics of the two trains types and analysis of their effects on impact dynamics. The analysis shows that the differences in bogie support positions on the carbody and coupling devices lead to differences in several structural and compositional characteristics. These characteristics result in different impact responses for the two types of train and are directly related to their impact stablity. Articulated trains have stiff connection and integral performance in collisions but with less capability for absorbing impact energy between carriages, whereas non-articulated trains show loose connection and scattered performance in collisions but with more options for energy absorber installation between carriages.