410 resultados para cerebrovascular accident


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Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

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The costs of work-related crashes In Australia and overseas, fleet safety or work-related road safety is an issue gaining increased attention from researchers, organisations, road safety practitioners and the general community. This attention is primarily in response to the substantial physical, emotional and economic costs associated with work-related road crashes. The increased risk factors and subsequent costs of work-related driving are also now well documented in the literature. For example, it is noteworthy that research has demonstrated that work-related drivers on average report a higher level of crash involvement compared to personal car drivers (Downs et al., 1999; Kweon and Kockelman, 2003) and in particular within Australia, road crashes are the most common form of work-related fatalities (Haworth et al., 2000).

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This paper describes a number of techniques for GNSS navigation message authentication. A detailed analysis of the security facilitated by navigation message authentication is given. The analysis takes into consideration the risk of critical applications that rely on GPS including transportation, finance and telecommunication networks. We propose a number of cryptographic authentication schemes for navigation data authentication. These authentication schemes provide authenticity and integrity of the navigation data to the receiver. Through software simulation, the performance of the schemes is quantified. The use of software simulation enables the collection of authentication performance data of different data channels, and the impact of various schemes on the infrastructure and receiver. Navigation message authentication schemes have been simulated at the proposed data rates of Galileo and GPS services, for which the resulting performance data is presented. This paper concludes by making recommendations for optimal implementation of navigation message authentication for Galileo and next generation GPS systems.

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Tracking/remote monitoring systems using GNSS are a proven method to enhance the safety and security of personnel and vehicles carrying precious or hazardous cargo. While GNSS tracking appears to mitigate some of these threats, if not adequately secured, it can be a double-edged sword allowing adversaries to obtain sensitive shipment and vehicle position data to better coordinate their attacks, and to provide a false sense of security to monitoring centers. Tracking systems must be designed with the ability to perform route-compliance and thwart attacks ranging from low-level attacks such as the cutting of antenna cables to medium and high-level attacks involving radio jamming and signal / data-level simulation, especially where the goods transported have a potentially high value to terrorists. This paper discusses the use of GNSS in critical tracking applications, addressing the mitigation of GNSS security issues, augmentation systems and communication systems in order to provide highly robust and survivable tracking systems.

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Background: The C allele of a common polymorphism of the serotonin 2A receptor (HTR2A) gene, T102C, results in reduced synthesis of 5-HT2A receptors and has been associated with current smoking status in adults. The -1438A/G polymorphism, located in the regulatory region of this gene, is in linkage disequilibrium with T102C, and the A allele is associated with increased promoter activity and with smoking in adult males. We investigated the contributions of the HTR2A gene, chronic psychological stress, and impulsivity to the prediction of cigarette smoking status and dependence in young adults. Methods: T102C and -1438A/G genotyping was conducted on 132 healthy Caucasian young adults (47 smokers) who completed self-report measures of chronic stress, depressive symptoms, impulsive personality and cigarette use. Results: A logistic regression analysis of current cigarette smoker user status, after adjusting for gender, depressive symptom severity and chronic stress, indicated that the T102C TT genotype relative to the CC genotype (OR = 7.53), and lower punishment sensitivity (OR = 0.91) were each significant predictive risk factors. However, for number of cigarettes smoked, only lower punishment sensitivity was a significant predictor (OR = 0.81). Conclusions: These data indicate the importance of the T102C polymorphism to tobacco use but not number of cigarettes smoked for Caucasian young adults. Future studies should examine whether this is explained by effects of nicotine on the serotonin system. Lower punishment sensitivity increased risk of both smoking and of greater consumption, perhaps via a reduced sensitivity to cigarette health warnings and negative physiological effects.

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Visibility limitations make cycling at night particularly dangerous. We previously reported cyclists’ perceptions of their own visibility at night and identified clothing configurations that made them feel visible. In this study we sought to determine whether these self-perceptions reflect actual visibility when wearing these clothing configurations. In a closed-road driving environment, cyclists wore black clothing, a fluorescent vest, a reflective vest, or a reflective vest plus ankle and knee reflectors. Drivers recognised more cyclists wearing the reflective vest plus reflectors (90%) than the reflective vest alone (50%), fluorescent vest (15%) or black clothing (2%). Older drivers recognised the cyclists less often than younger drivers (51% vs 27%). The findings suggest that reflective ankle and knee markings are particularly valuable at night, while fluorescent clothing is not. Cyclists wearing fluorescent clothing may be at particular risk if they incorrectly believe themselves to be conspicuous to drivers at night.

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The efficacy of road safety countermeasures to deter motorists from engaging in illegal behaviours is extremely important when considering the personal and economic impact of road accidents on the community. Within many countries, deterrence theory has remained a cornerstone to criminology and criminal justice policy, particularly within the field of road safety, as policy makers and enforcement agencies attempt to increase perceptions regarding the certainty, severity and swiftness of sanctions for those who engage in illegal motoring behaviours. Using the Australian experience (particularly the tremendous amount of research into drink driving), the current paper reviews the principles underpinning deterrence theory, the utilisation of the approach within some contemporary road safety initiatives (e.g., Random Breath Testing) as well as highlights some methods to enhance a deterrent effect. The paper also provides direction for future deterrence-based research, in particular, considering the powerful impact of non-legal sanctions, punishment avoidance as well as creating culturally embedded behavioural change.

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Of the numerous factors that play a role in fatal pedestrian collisions, the time of day, day of the week, and time of year can be significant determinants. More than 60% of all pedestrian collisions in 2007 occurred at night, despite the presumed decrease in both pedestrian and automobile exposure during the night. Although this trend is partially explained by factors such as fatigue and alcohol consumption, prior analysis of the Fatality Analysis Reporting System database suggests that pedestrian fatalities increase as light decreases after controlling for other factors. This study applies graphical cross-tabulation, a novel visual assessment approach, to explore the relationships among collision variables. The results reveal that twilight and the first hour of darkness typically observe the greatest frequency of pedestrian fatal collisions. These hours are not necessarily the most risky on a per mile travelled basis, however, because pedestrian volumes are often still high. Additional analysis is needed to quantify the extent to which pedestrian exposure (walking/crossing activity) in these time periods plays a role in pedestrian crash involvement. Weekly patterns of pedestrian fatal collisions vary by time of year due to the seasonal changes in sunset time. In December, collisions are concentrated around twilight and the first hour of darkness throughout the week while, in June, collisions are most heavily concentrated around twilight and the first hours of darkness on Friday and Saturday. Friday and Saturday nights in June may be the most dangerous times for pedestrians. Knowing when pedestrian risk is highest is critically important for formulating effective mitigation strategies and for efficiently investing safety funds. This applied visual approach is a helpful tool for researchers intending to communicate with policy-makers and to identify relationships that can then be tested with more sophisticated statistical tools.

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Current guidelines on clear zone selection and roadside hazard management adopt the US approach based on the likelihood of roadside encroachment by drivers. This approach is based on the available research conducted in the 1960s and 70s. Over time, questions have been raised regarding the robustness and applicability of this research in Australasia in 2010 and in the Safe System context. This paper presents a review of the fundamental research relating to selection of clear zones. Results of extensive rural highway statistical data modelling suggest that a significant proportion of run-off-road to the left casualty crashes occurs in clear zones exceeding 13 m. They also show that the risk of run-off-road to the left casualty crashes was 21% lower where clear zones exceeded 8 m when compared with clear zones in the 4 – 8 m range. The paper discusses a possible approach to selection of clear zones based on managing crash outcomes, rather than on the likelihood of roadside encroachment which is the basis for the current practice. It is expected that this approach would encourage selection of clear zones wider than 8 m when the combination of other road features suggests higher than average casualty crash risk.

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Currently in Australia, there are no decision support tools for traffic and transport engineers to assess the crash risk potential of proposed road projects at design level. A selection of equivalent tools already exists for traffic performance assessment, e.g. aaSIDRA or VISSIM. The Urban Crash Risk Assessment Tool (UCRAT) was developed for VicRoads by ARRB Group to promote methodical identification of future crash risks arising from proposed road infrastructure, where safety cannot be evaluated based on past crash history. The tool will assist practitioners with key design decisions to arrive at the safest and the most cost -optimal design options. This paper details the development and application of UCRAT software. This professional tool may be used to calculate an expected mean number of casualty crashes for an intersection, a road link or defined road network consisting of a number of such elements. The mean number of crashes provides a measure of risk associated with the proposed functional design and allows evaluation of alternative options. The tool is based on historical data for existing road infrastructure in metropolitan Melbourne and takes into account the influence of key design features, traffic volumes, road function and the speed environment. Crash prediction modelling and risk assessment approaches were combined to develop its unique algorithms. The tool has application in such projects as road access proposals associated with land use developments, public transport integration projects and new road corridor upgrade proposals.

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The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

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Drivers are known to be optimistic about their risk of crash involvement, believing that they are less likely to be involved in a crash than other drivers. However, little comparative research has been conducted among other road users. In addition, optimism about crash risk is conceptualised as applying only to an individual’s assessment of his or her personal risk of crash involvement. The possibility that the self-serving nature of optimism about safety might be generalised to the group-level as a cyclist or a pedestrian, i.e., becoming group-serving rather than self-serving, has been overlooked in relation to road safety. This study analysed a subset of data collected as part of a larger research project on the visibility of pedestrians, cyclists and road workers, focusing on a set of questionnaire items administered to 406 pedestrians, 838 cyclists and 622 drivers. The items related to safety in various scenarios involving drivers, pedestrians and cyclists, allowing predictions to be derived about group differences in agreement with items based on the assumption that the results would exhibit group-serving bias. Analysis of the responses indicated that specific hypotheses about group-serving interpretations of safety and responsibility were supported in 22 of the 26 comparisons. When the nine comparisons relevant to low lighting conditions were considered separately, seven were found to be supported. The findings of the research have implications for public education and for the likely acceptance of messages which are inconsistent with current assumptions and expectations of pedestrians and cyclists. They also suggest that research into group-serving interpretations of safety, even for temporary roles rather than enduring groups, could be fruitful. Further, there is an implication that gains in safety can be made by better educating road users about the limitations of their visibility and the ramifications of this for their own road safety, particularly in low light.

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Fatigue has been recognised as the primary contributing factor in approximately 15% of all fatal road crashes in Australia. To develop effective countermeasures for managing fatigue, this study investigates why drivers continue to drive when sleepy, and driver perceptions and behaviours in regards to countermeasures. Based on responses from 305 Australian drivers, it was identified that the major reasons why these participants continued to drive when sleepy were: wanting to get to their destination; being close to home; and time factors. Participants’ perceptions and use of 18 fatigue countermeasures were investigated. It was found that participants perceived the safest strategies, including stopping and sleeping, swapping drivers and stopping for a quick nap, to be the most effective countermeasures. However, it appeared that their knowledge of safe countermeasures did not translate into their use of these strategies. For example, although the drivers perceived stopping for a quick nap to be an effective countermeasure, they reported more frequent use of less safe methods such as stopping to eat or drink and winding down the window. This finding suggests that, while practitioners should continue educating drivers, they may need a greater focus on motivating drivers to implement safe fatigue countermeasures.

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A number of advanced driver assistance systems (ADAS) are currently being released on the market, providing safety functions to the drivers such as collision avoidance, adaptive cruise control or enhanced night-vision. These systems however are inherently limited by their sensory range: they cannot gather information from outside this range, also called their “perceptive horizon”. Cooperative systems are a developing research avenue that aims at providing extended safety and comfort functionalities by introducing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications to the road actors. This paper presents the problematic of cooperative systems, their advantages and contributions to road safety and exposes some limitations related to market penetration, sensors accuracy and communications scalability. It explains the issues of how to implement extended perception, a central contribution of cooperative systems. The initial steps of an evaluation of data fusion architectures for extended perception are exposed.

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International statistics indicate that occupational, or work-related driving, crashes are the most common cause of workplace injury, death, and absence from work. The majority of research examining unsafe driver behavior in the workplace has relied on general road safety questionnaires. However, past research has failed to consider the organizational context in the use of these questionnaires, and as such, there is ambiguity in the dimensions constituting occupational driving. Using a theoretical model developed by Hockey (1993, 1997), this article proposes and validates a new scale of occupational driver behavior. This scale incorporates four dimensions of driver behavior that are influenced by demanding workplace conditions; speeding, rule violation, inattention, and driving while tired. Following a content validation process, three samples of occupational drivers in Australia were used to assess the scale. Data from the first sample (n=145) were used to reduce the number of scale items and provide an assessment of the factorial validity of the scale. Data from the second sample (n=645) were then used to confirm the factor structure and psychometric properties of the scale including reliability and construct validity. Finally, data from the third sample (n=248) were used to establish criterion validity. The results indicated that the scale is a reliable and valid measure of occupational driver behavior.