928 resultados para road traffic injury


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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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Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.

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The Silk Road Project was a practice-based research project investigating the potential of motion capture technology to inform perceptions of embodiment in dance performance. The project created a multi-disciplinary collaborative performance event using dance performance and real-time motion capture at Deakin University’s Deakin Motion Lab. Performances at Deakin University, December 2007.

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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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Hazard perception in driving is the one of the few driving-specific skills associated with crash involvement. However, this relationship has only been examined in studies where the majority of individuals were younger than 65. We present the first data revealing an association between hazard perception and self-reported crash involvement in drivers aged 65 and over. In a sample of 271 drivers, we found that individuals whose mean response time to traffic hazards was slower than 6.68 seconds (the ROC-curve derived pass mark for the test) were 2.32 times (95% CI 1.46, 3.22) more likely to have been involved in a self-reported crash within the previous five years than those with faster response times. This likelihood ratio became 2.37 (95% CI 1.49, 3.28) when driving exposure was controlled for. As a comparison, individuals who failed a test of useful field of view were 2.70 (95% CI 1.44, 4.44) times more likely to crash than those who passed. The hazard perception test and the useful field of view measure accounted for separate variance in crash involvement. These findings indicate that hazard perception testing and training could be potentially useful for road safety interventions for this age group.

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An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE and GAIA. Initial analyses established high, low and moderate traffic scenarios as well as low, low to moderate, moderate, high and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75µm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 µm, whereas metal concentrations in finer size range of <1-75 µm were not affected. As practical implications, solids <1 µm and organic matter from 1 - >300 µm can be targeted for removal of Ni, Cu, Pb, Cd, Cr and Zn from build-up whilst organic matter from <1 - >300 µm can be targeted for removal of Cd, Cr, Pb and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

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In this paper, we presented an automatic system for precise urban road model reconstruction based on aerial images with high spatial resolution. The proposed approach consists of two steps: i) road surface detection and ii) road pavement marking extraction. In the first step, support vector machine (SVM) was utilized to classify the images into two categories: road and non-road. In the second step, road lane markings are further extracted on the generated road surface based on 2D Gabor filters. The experiments using several pan-sharpened aerial images of Brisbane, Queensland have validated the proposed method.

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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.

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Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.

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Questionnaires and interviews were conducted with employees and senior managers from three Australian organisations to explore the relationship between perceived managerial ownership of safety responsibilities and occupational road safety. It was found that the perceived authority of the person primarily responsible for managing road risks and perceived shared ownership of safety tasks were both significant independent predictors of safer driving behaviours. It was identified that the position of the person accepting primary risk management responsibilities was typically a member of the OHS team and typically in a management position. The extent that ownership was shared across members within the researched organisations varied, with personnel from OHS and fleet management typically accepting partial ownership of managing occupational road risks. Based on the findings, several recommendations are made to assist practitioners in managing occupational road risks.

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Level crossing crashes have been shown to result in enormous human and financial cost to society. According to the Australian Transport Safety Bureau (ATSB) [5] a total of 632 Railway Level crossing (RLX) collisions, between trains and road vehicles, occurred in Australia between 2001 and June 2009. The cost of RLX collisions runs into the tens of millions of dollars each year in Australia [6]. In addition, loss of life and injury are commonplace in instances where collisions occur. Based on estimates that 40% of rail related fatalities occur at level crossings [12], it is estimated that 142 deaths between 2001 and June 2009 occurred at RLX. The aim of this paper is to (i) summarise crash patterns in Australia, (ii) review existing international ITS interventions to improve level crossing and (iii) highlights open human factors research related issues. Human factors (e.g., driver error, lapses or violations) have been evidenced as a significant contributing factor in RLX collisions, with drivers of road vehicles particularly responsible for many collisions. Unintentional errors have been found to contribute to 46% of RLX collisions [6] and appear to be far more commonplace than deliberate violations. Humans have been found to be inherently inadequate at using the sensory information available to them to facilitate safe decision-making at RLX and tend to underestimate the speed of approaching large objects due to the non-linear increases in perceived size [6]. Collisions resulting from misjudgements of train approach speed and distance are common [20]. Thus, a fundamental goal for improved RLX safety is the provision of sufficient contextual information to road vehicle drivers to facilitate safe decision-making regarding crossing behaviours.

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Powered two wheelers (PTWs) come in diverse forms and are used for a range of purposes in very different parts of the world. In many parts of the world, the forms and uses of PTWs are changing, influenced by social, economic and demographic changes. Most of the challenges associated with PTWs relate to safety, while the majority of the opportunities relate to mobility. The challenges for improving safety relate to the PTW user, other road users, the road environment, the vehicle, data and research, and socio-political dimensions. The relative importance of particular challenges varies between developed and developing countries, and among developing countries according to whether PTWs are largely used for recreation or for transport. PTWs present a range of psychological, transport, economic and environmental opportunities to individuals and societies. The fun and excitement of riding PTWs is a major motivator for their purchase and use for recreational purposes, both off-road and on-road. The transport and economic advantages to the individual also need to be considered. At a societal level, research has examined the potential for increasing PTW volumes to reduce fossil fuel use and traffic congestion in busy cities. The future of PTWs may differ greatly between countries and environmental and technological changes are leading to an evolution in the form of PTWs to encompass new modes of personal transportation.

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Driver aggression is a road safety issue of growing concern throughout most highly motorised countries, yet to date there is no comprehensive model that deals with this issue in the road safety area. This paper sets out to examine the current state of research and theory on aggressive driving with a view to incorporating useful developments in the area of human aggression from mainstream psychological research. As a first step, evidence regarding the prevalence and incidence of driver aggression, including the impact of the phenomenon on crash rates is reviewed. Inconsistencies in the definition and operationalisation of driver aggression that have hampered research in the area are noted. Existing models of driver aggression are then identified and the need to distinguish and address the role of intentionality as well as the purpose of perpetrating behaviours within both these and research efforts is highlighted. Drawing on recent findings from psychological research into general aggression, it is argued that progress in understanding driver aggression requires models that acknowledge not only the person-related and situational factors, but the cognitive and emotional appraisal processes involved in driver aggression. An effective model is expected to allow the explanation of not only the likelihood and severity of driver aggression behaviours, but also the escalation of incidents within the context of the road environment.

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Driver aggression is an increasing concern for motorists, with some research suggesting that drivers who behave aggressively perceive their actions as justified by the poor driving of others. Thus attributions may play an important role in understanding driver aggression. A convenience sample of 193 drivers (aged 17-36) randomly assigned to two separate roles (‘perpetrators’ and ‘victims’) responded to eight scenarios of driver aggression. Drivers also completed the Aggression Questionnaire and Driving Anger Scale. Consistent with the actor-observer bias, ‘victims’ (or recipients) in this study were significantly more likely than ‘perpetrators’ (or instigators) to endorse inadequacies in the instigator’s driving skills as the cause of driver aggression. Instigators were significantly more likely attribute the depicted behaviours to external but temporary causes (lapses in judgement or errors) rather than stable causes. This suggests that instigators recognised drivers as responsible for driving aggressively but downplayed this somewhat in comparison to ‘victims’/recipients. Recipients and instigators agreed that the behaviours were examples of aggressive driving but instigators appeared to focus on the degree of intentionality of the driver in making their assessments while recipients appeared to focus on the safety implications. Contrary to expectations, instigators gave mean ratings of the emotional impact of driving aggression on recipients that were higher in all cases than the mean ratings given by the recipients. Drivers appear to perceive aggressive behaviours as modifiable, with the implication that interventions could appeal to drivers’ sense of self-efficacy to suggest strategies for overcoming plausible and modifiable attributions (e.g. lapses in judgement; errors) underpinning behaviours perceived as aggressive.

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Background: Young motorists engaging in anti-social and often dangerous driving manoeuvres (which is often referred to as “hooning” within Australia) is an increasing road safety problem. While anecdotal evidence suggests that such behaviour is positively linked with crash involvement, researchers have yet to examine whether younger drivers who deliberately break road rules and drive in an erratic manner (usually with peers) are in fact over represented in crash statistics. This paper outlines research that aimed to identify the characteristics of individuals most likely to engaging in hooning behaviours, as well as examine the frequency of such driving behaviours and if such activity is linked with self-reported crash involvement.---------- Methods: A total of 717 young drivers in Queensland voluntarily completed a questionnaire to investigate their driving behaviour and crash history.---------- Results: Quantitative analysis of the data revealed that almost half the sample reported engaging in some form of “hooning” behaviour at least once in their lifetime, although only 4% indicated heavy participation in the behaviour e.g., >50 times. Street racing was the most common activity reported by participants followed by “drifting” and then “burnouts”. Logistic regression analysis indicated that being younger and a male was predictive of reporting such anti-social driving behaviours, and importantly, a trend was identified between such behaviour and self-reported crash involvement.---------- Conclusions: This research provides preliminary evidence that younger male drivers are more likely to engage in dangerous driving behaviours, which ultimately may prove to increase their overall risk of becoming involved in a crash. This paper will further outline the study findings in regards to current enforcement efforts to deter such driving activity as well as provide direction for future research efforts in this area.---------- Research highlights: ► The self-reported driving behaviours of 717 younger Queensland drivers were examined to investigate the relationship between deliberately breaking road rules and self-reported crash involvement. ► Younger male drivers were most likely to engage in such aberrant driving behaviours and a trend was identified between such behaviour and self-reported crash involvement.