530 resultados para Crash Hazards.


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Traffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways. Identifying the critical determinants of travel delays has been of significant importance to the incident management systems which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard-based models to develop in-depth insights into how the crash-specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland and the differential effects of determinants on crash survival functions have been studied on these two motorways individually. A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, have been compared to random parameter AFT structures in terms of goodness of fit to the duration data and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway exhibits durations that are on average 19% shorter compared to the durations on motorway. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that, looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.

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Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

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Evidence increasingly suggests that our behaviour on the road mirrors our behaviour across other aspects of our life. The idea that we drive as we live, described by Tillman and Hobbs more than 65 years ago when examining off-road behaviours of taxi drivers (1949), is the focus of the current paper. As part of a larger study examining the impact of penalty changes on a large cohort of Queensland speeding offenders, criminal (lifetime) and crash history (10 year period) data for a sub-sample of 1000 offenders were obtained. Based on the ‘drive as we live’ maxim, it was hypothesised that crash-involved speeding offenders would be more likely to have a criminal history than non-crash involved offenders. Overall, only 30% of speeding offenders had a criminal history. However, crash-involved offenders were significantly more likely to have a criminal history (49.4%) than non-crash involved offenders (28.6%), supporting the hypothesis. Furthermore, those deemed ‘most at fault’ in a crash were the group most likely to have at least one criminal offence (52.2%). When compared to the non-crash involved offenders, those deemed ‘not most at fault’ in a crash were also more likely to have had at least one criminal offence (46.5%). Therefore, when compared to non-crash involved speeding offenders, those offenders involved in a crash were more likely to have been convicted of at least one criminal offence, irrespective of whether they were deemed ‘most at fault’ in that crash. Implications for traffic offender management and policing are discussed.

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Alcohol is a major factor in road deaths and serious injuries. In Victoria, between 2008 and 2013, 30% of drivers killed were involved in alcohol-related crashes. From the early 1980s Victoria progressively introduced a series of measures, such as driver licence cancellation and alcohol interlocks, to reduce the level of drink-driving on Victoria's roads. This project tracked drink-driving offenders to measure and understand their re-offence and road trauma involvement levels during and after periods of licensing and driving interventions. The methodology controlled for exposure by aggregating crashes and traffic violations within relevant categories (e.g. licence cancelled/relicensed/relicensing not sought) and calculated as rates 'per thousand person-years'. Inferential statistical techniques were used to compare crash and offence rates between control and treatment groups across three distinct time periods, which coincided with the introduction of new interventions. This paper focuses on the extent to which the Victorian drink-driving measures have been successful in reducing re-offending and road trauma involvement during and after periods of licence interventions. It was found that a licence cancellation/ban is an effective drink-driving countermeasure as it reduced drink-driving offending and drink-driving crashes. Interlocks also had a positive effect on drink-driving offences as they were reduced during the interlock period as well as for the entire intervention period. Possible drink-driving policy implications are briefly discussed.

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Over recent years, the focus in road safety has shifted towards a greater understanding of road crash serious injuries in addition to fatalities. Police reported crash data are often the primary source of crash information; however, the definition of serious injury within these data is not consistent across jurisdictions and may not be accurately operationalised. This study examined the linkage of police-reported road crash data with hospital data to explore the potential for linked data to enhance the quantification of serious injury. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. Nine different estimates of serious road crash injury were produced. Results showed that there was a large amount of variation in the estimates of the number and profile of serious road crash injuries depending on the definition or measure used. The results also showed that as the definition of serious injury becomes more precise the vulnerable road users become more prominent. These results have major implications in terms of how serious injuries are identified for reporting purposes. Depending on the definitions used, the calculation of cost and understanding of the impact of serious injuries would vary greatly. This study has shown how data linkage can be used to investigate issues of data quality. It has also demonstrated the potential improvements to the understanding of the road safety problem, particularly serious injury, by conducting data linkage.

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- Objective Driver sleepiness is a major crash risk factor, but may be under-recognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding. - Methods In total, 300 Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants perception of crash risk was assessed for five different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, night-time) of driving. - Results The analysis confirmed that sleepy driving was considered a risky driving behavior, but not as risky as high levels of speeding (p < .05). Yet, the risk of crashing at 4 am was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky due to time of day/circadian influences were not reported as high risk. - Conclusions The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long distance driving and driver sleepiness. Further efforts are required to improve the community’s awareness of the impairing effects from sleepiness and in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.

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This paper presents some results from preliminary analyses of the data of an international online survey of bicycle riders, who reported riding at least once a month. On 4 July 2015, data from 7528 participants from 17 countries was available in the survey, and were subsequently cleaned and checked for consistency. The median distance ridden ranged from 30 km/week in Israel to 150 km/week in Greece (overall median 54 km/week). City/hybrid bicycles were the most common type of bicycle ridden (44%), followed by mountain (20%) and road bikes (15%). Almost half (47%) of the respondents rode “nearly daily”. About a quarter rode daily to work or study (27%). Overall, 40% of respondents reported wearing a helmet ‘always’, varying from 2% in the Netherlands to 80% in Norway, while 25% reported ‘never’ wearing a helmet. Thus, individuals appeared to consistently either use or not use helmets. Helmet wearing rates were generally higher when riding for health/fitness than other purposes and appeared to be little affected by the type of riding location, but some divergences in these patterns were found among countries. Almost 29% of respondents reported being involved in at least one bicycle crash in the last year (ranging from 12% in Israel to 53% in Turkey). Among the most severe crashes for each respondent, about half of the crashes involved falling off a bicycle. Just under 10% of the most severe crashes for each respondent were reported to police. Among the bicycle-motor vehicle crashes, only a third were reported to police. Further analyses will address questions regarding the influence of factors such as demographic characteristics, type of bicycle ridden, and attitudes on both bi-cycle use and helmet wearing rates.

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Automatic-dishwasher detergent is a common household substance which is extremely corrosive and potentially fatal if ingested. In this report, we discuss the implications of the ingestion of automatic-dishwasher detergent in 18 children over a three-year period. Ten of the 18 children gained access to the automatic-dishwasher detergent from the dishwasher on the completion of the washing-cycle, while the remainder ingested the detergent directly from the packet. There was a poor correlation between the presenting signs and symptoms and the subsequent endoscopic finding in the 14 children who underwent endoscopy.

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Speed is recognised as a key contributor to crash likelihood and severity, and to road safety performance in general. Its fundamental role has been recognised by making Safe Speeds one of the four pillars of the Safe System. In this context, impact speeds above which humans are likely to sustain fatal injuries have been accepted as a reference in many Safe System infrastructure policy and planning discussions. To date, there have been no proposed relationships for impact speeds above which humans are likely to sustain fatal or serious (severe) injury, a more relevant Safe System measure. A research project on Safe System intersection design required a critical review of published literature on the relationship between impact speed and probability of injury. This has led to a number of questions being raised about the origins, accuracy and appropriateness of the currently accepted impact speed–fatality probability relationships (Wramborg 2005) in many policy documents. The literature review identified alternative, more recent and more precise relationships derived from the US crash reconstruction databases (NASS/CDS). The paper proposes for discussion a set of alternative relationships between vehicle impact speed and probability of MAIS3+ (fatal and serious) injury for selected common crash types. Proposed Safe System critical impact speed values are also proposed for use in road infrastructure assessment. The paper presents the methodology and assumptions used in developing these relationships. It identifies further research needed to confirm and refine these relationships. Such relationships would form valuable inputs into future road safety policies in Australia and New Zealand.

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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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Purpose The object of this paper is to examine whether the improvements in technology that enhance community understanding of the frequency and severity of natural hazards also increased the risk of potential liability of planning authorities in negligence. In Australia, the National Strategy imposes a resilience based approach to disaster management and stresses that responsible land use planning can reduce or prevent the impact of natural hazards upon communities. Design/methodology/approach This paper analyses how the principles of negligence allocate responsibility for loss suffered by a landowner in a hazard prone area between the landowner and local government. Findings The analysis in this paper concludes that despite being able to establish a causal link between the loss suffered by a landowner and the approval of a local authority to build in a hazard prone area, it would be in the rarest of circumstances a negligence action may be proven. Research limitations/implications The focus of this paper is on planning policies and land development, not on the negligent provision of advice or information by the local authority. Practical implications This paper identifies the issues a landowner may face when seeking compensation from a local authority for loss suffered due to the occurrence of a natural hazard known or predicted to be possible in the area. Originality/value The paper establishes that as risk managers, local authorities must place reliance upon scientific modelling and predictive technology when determining planning processes in order to fulfil their responsibilities under the National Strategy and to limit any possible liability in negligence.

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Purpose To examine the effects of optical blur, auditory distractors and age on eye movement patterns while performing a driving hazard perception test (HPT). Methods Twenty young (mean age 27.1 ± 4.6 years) and 20 older (73.3 ± 5.7 years) drivers with normal vision completed a HPT in a repeated-measures counterbalanced design while their eye movements were recorded. Testing was performed under two visual (best-corrected vision and with +2.00DS blur) and two distractor (with and without auditory distraction) conditions. Participants were required to respond to road hazards appearing in the HPT videos of real-world driving scenes and their hazard response times were recorded. Results Blur and distractors each significantly delayed hazard response time, by 0.42 and 0.76s respectively (p<0.05). A significant interaction between age and distractors indicated that older drivers were more affected by distractors than young drivers (response with distractors delayed by 0.96 and 0.60s respectively). There were no other two- or three-way interaction effect on response time. With blur, both groups fixated significantly longer on hazards before responding compared to best-corrected vision. In the presence of distractors, both groups exhibited delayed first fixation on the hazards and spent less time fixating on the hazards. There were also significant differences in eye movement characteristics between groups, where older drivers exhibited smaller saccades, delayed first fixation on hazards, and shorter fixation duration on hazards compared to the young drivers. Conclusions Collectively, the findings of delayed hazard response times and alterations in eye movement patterns with blur and distractors provide further evidence that visual impairment and distractors are independently detrimental to driving safety given that delayed hazard response times are linked to increased crash risk.

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This paper presents a detailed description of the influence of critical parameters that govern the vulnerability of columns under lateral impact loads. Numerical simulations are conducted by using the Finite Element program LS-DYNA, incorporating steel reinforcement, material models and strain rate effects. A simplified method based on impact pulse generated from full scale impact tests is used for impact reconstruction and effects of the various pulse loading parameters are investigated under low to medium velocity impacts. A constitutive material model which can simulate failures under tri-axial state of stresses is used for concrete. Confinement effects are also introduced to the numerical simulation and columns of Grade 30 to 50 concrete under pure axial loading are analysed in detail. This research confirmed that the vulnerability of the axially loaded columns can be mitigated by reducing the slenderness ratio and concrete grade, and by choosing the design option with a minimal amount of longitudinal steel. Additionally, it is evident that approximately a 50% increase in impact capacity can be gained for columns in medium rise buildings by enhancing the confinement effects alone. Results also indicated that the ductility as well as the mode of failure under impact can be changed with the volumetric ratio of lateral steel. Moreover, to increase the impact capacity of the vulnerable columns, a higher confining stress is required. The general provisions of current design codes do not sufficiently cover this aspect and hence this research will provide additional guidelines to overcome the inadequacies of code provisions.