956 resultados para driver tiredness


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This paper reports profiling information for speeding offenders and is part of a larger project that assessed the deterrent effects of increased speeding penalties in Queensland, Australia, using a total of 84,456 speeding offences. The speeding offenders were classified into three groups based on the extent and severity of an index offence: once-only low-rang offenders; repeat high-range offenders; and other offenders. The three groups were then compared in terms of personal characteristics, traffic offences, crash history and criminal history. Results revealed a number of significant differences between repeat high-range offenders and those in the other two offender groups. Repeat high-range speeding offenders were more likely to be male, younger, hold a provisional and a motorcycle licence, to have committed a range of previous traffic offences, to have a significantly greater likelihood of crash involvement, and to have been involved in multiple-vehicle crashes than drivers in the other two offender types. Additionally, when a subset of offenders’ criminal histories were examined, results revealed that repeat high-range speeding offenders were also more likely to have committed a previous criminal offence compared to once only low-range and other offenders and that 55.2% of the repeat high-range offenders had a criminal history. They were also significantly more likely to have committed drug offences and offences against order than the once only low-range speeding offenders, and significantly more likely to have committed regulation offences than those in the other offenders group. Overall, the results indicate that speeding offenders are not an homogeneous group and that, therefore, more tailored and innovative sanctions should be considered and evaluated for high-range recidivist speeders because they are a high-risk road user group.

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This report presents the final deliverable from the project titled Conceptual and statistical framework for a water quality component of an integrated report card’ funded by the Marine and Tropical Sciences Research Facility (MTSRF; Project 3.7.7). The key management driver of this, and a number of other MTSRF projects concerned with indicator development, is the requirement for state and federal government authorities and other stakeholders to provide robust assessments of the present ‘state’ or ‘health’ of regional ecosystems in the Great Barrier Reef (GBR) catchments and adjacent marine waters. An integrated report card format, that encompasses both biophysical and socioeconomic factors, is an appropriate framework through which to deliver these assessments and meet a variety of reporting requirements. It is now well recognised that a ‘report card’ format for environmental reporting is very effective for community and stakeholder communication and engagement, and can be a key driver in galvanising community and political commitment and action. Although a report card it needs to be understandable by all levels of the community, it also needs to be underpinned by sound, quality-assured science. In this regard this project was to develop approaches to address the statistical issues that arise from amalgamation or integration of sets of discrete indicators into a final score or assessment of the state of the system. In brief, the two main issues are (1) selecting, measuring and interpreting specific indicators that vary both in space and time, and (2) integrating a range of indicators in such a way as to provide a succinct but robust overview of the state of the system. Although there is considerable research and knowledge of the use of indicators to inform the management of ecological, social and economic systems, methods on how to best to integrate multiple disparate indicators remain poorly developed. Therefore the objective of this project was to (i) focus on statistical approaches aimed at ensuring that estimates of individual indicators are as robust as possible, and (ii) present methods that can be used to report on the overall state of the system by integrating estimates of individual indicators. It was agreed at the outset, that this project was to focus on developing methods for a water quality report card. This was driven largely by the requirements of Reef Water Quality Protection Plan (RWQPP) and led to strong partner engagement with the Reef Water Quality Partnership.

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Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.

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The Haddon Matrix was developed in the 1960s road safety arena, and has since been used in many public health settings. The literature and two specific case studies are reviewed to describe the background to the Haddon Matrix, identify how it has been critiqued and developed over time and practical applications in the work-related road safety context. Haddon’s original focus on the road, vehicle and driver has been extended and applied to include organisational safety culture, journey management and wider issues in society that affect occupational drivers and the communities in which they work. The paper shows that the Haddon Matrix has been applied in many projects and contexts. Practical work-related road safety applications include providing a comprehensive systems-based safety management framework to inform strategy. It has also been used to structure the review or gap analysis of current programs and processes, identify and develop prevention measures and as a tool for effective post-event investigations.

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Aggressive driving has been associated with engagement in other risky driving behaviours, such as speeding; while drivers using their mobile phones have an increased crash risk, despite the tendency to reduce their speed. Research has amassed separately for mobile phone use and aggressive driving among younger drivers, however little is known about the extent to which these behaviours may function independently and in combination to influence speed selection behaviour. The main aim of the current study was to investigate the effect of driver aggression (measured by the Driving Anger Expression Inventory) and mobile phone use on speed selection by young drivers. The CARRS-Q advanced driving simulator was used to test the speed selection of drivers aged 18 to 26 years (N = 32) in a suburban (60kph zone) driving context. A 2 (level of driving anger expression: low, high) X 3 (mobile phone use condition: baseline, hands-free, hand-held) mixed factorial ANOVA was conducted with speed selection as the dependent variable. Results revealed a significant main effect for mobile phone use condition such that speed selection was lowest for the hand-held condition and highest for the baseline condition. Speed selection, however, was not significantly different across the levels of driving anger expression; nor was there a significant interaction effect between the mobile phone use and driving anger expression. As young drivers are over-represented in road crash statistics, future research should further investigate the combined impact of driver aggression and mobile phone use on speed selection.

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This study investigated whether the night-time conspicuity of road workers can be enhanced by positioning retroreflective strips on the moveable joints in patterns that convey varying degrees of biological motion. Participants were 24 visually normal adults (12 young M = 26.8 years; 12 older M = 72.9 years). Visual acuity, contrast sensitivity and glare sensitivity were recorded for each participant. Experimenters acting as road workers walked in place on a closed road circuit within simulated road work sites, facing either the oncoming driver or the roadway (presenting sideways to the driver) and wearing one of four clothing conditions: (i) standard road worker vest; (ii) standard vest plus thigh-mounted retroreflective strips; (iii) standard vest plus retroreflective strips on ankles and knees; (iv) standard vest plus retroreflective strips positioned on the extremities in a configuration that conveyed biological motion (“biomotion”). As they drove along the closed road participants were instructed to press a button to indicate when they first recognized that a road worker was present. The results demonstrated that regardless of the direction of walking, road workers wearing biomotion clothing were recognized at significantly (p < 0.05) longer distances (3×), relative to the standard vest alone. Response distances were significantly shorter for the older drivers. Contrast sensitivity was a better predictor of the ability to recognize road workers than was visual acuity or glare sensitivity. We conclude that adding retroreflective strips in the biomotion configuration can significantly improve road worker conspicuity regardless of the road worker's orientation and the age of the driver.

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Introduction: Research that has focused on the ability of self-report assessment tools to predict crash outcomes has proven to be mixed. As a result, researchers are now beginning to explore whether examining culpability of crash involvement can subsequently improve this predictive efficacy. This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to predict crash involvement among a sample of general Queensland motorists, and in particular, whether including a crash culpability variable improves predictive outcomes. Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results: Consistent with previous research, a factor analysis revealed a three factor solution for the DBQ accounting for 40.5% of the overall variance. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement. Rather, exposure to the road was found to be predictive of crashes. An analysis into culpability revealed 88 participants reported being “at fault” for their most recent crash. Corresponding between and multi-variate analyses that included the culpability variable did not result in an improvement in identifying those involved in crashes. Conclusions: While preliminary, the results suggest that including crash culpability may not necessarily improve predictive outcomes in self-report methodologies, although it is noted the current small sample size may also have had a deleterious effect on this endeavour. This paper also outlines the need for future research (which also includes official crash and offence outcomes) to better understand the actual contribution of self-report assessment tools, and culpability variables, to understanding and improving road safety.

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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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Purpose – This paper aims to recognise the importance of informal processes within corporate governance and complement existing research in this area by investigating factors associated with the existence of informal interactions between audit committees and internal audit functions and in providing directions for future research. Design/methodology/approach – To examine the existence and drivers of informal interactions between audit committees and internal audit functions, this paper relies on a questionnaire survey of chief audit executives (CAEs) in the UK from listed and non-listed, as well as financial and non-financial, companies. While prior qualitative research suggests that informal interactions do take place, most of the evidence is based on particular organisational setting or on a very small range of interviews. The use of a questionnaire enabled the examination of the existence of internal interactions across a relatively larger number of entities. Findings – The paper finds evidence of audit committees and internal audit functions engaging in informal interactions in addition to formal pre-scheduled regular meetings. Informal interactions complement formal meetings with the audit committee and as such represent additional opportunities for the audit committees to monitor internal audit functions. Audit committees’ informal interactions are significantly and positively associated with audit committee independence, audit chair’s knowledge and experience, and internal audit quality. Originality/value – The results demonstrate the importance of the background of the audit committee chair for the effectiveness of the governance process. This is possibly the first paper to examine the relationship between audit committee quality and internal audit, on the existence and driver of informal interactions. Policy makers should recognize that in addition to formal mechanisms, informal processes, such as communication outside of formal pre-scheduled meetings, play a significant role in corporate governance.

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Young novice drivers are at considerable risk of injury on the road. Their behaviour appears vulnerable to the social influence of their parents and friends. The nature and mechanisms of parent and peer influence on young novice driver (16–25 years) behaviour was explored via small group interviews (n = 21) and two surveys (n1 = 1170, n2 = 390) to inform more effective young driver countermeasures. Parental and peer influence occurred in preLicence, Learner, and Provisional (intermediate) periods. Pre-Licence and unsupervised Learner drivers reported their parents were less likely to punish risky driving (e.g., speeding). These drivers were more likely to imitate their parents and reported their parents were also risky drivers. Young novice drivers who experienced or expected social punishments from peers, including ‘being told off’ for risky driving, reported less riskiness. Conversely drivers who experienced or expected social rewards such as being ‘cheered on’ by friends – who were also more risky drivers – reported more risky driving including crashes and offences. Interventions enhancing positive influence and curtailing negative influence may improve road safety outcomes not only for young novice drivers, but for all persons who share the road with them. Parent-specific interventions warrant further development and evaluation including: modelling safe driving behaviour by parents; active monitoring of driving during novice licensure; and sharing the family vehicle during the intermediate phase. Peer-targeted interventions including modelling of safe driving behaviour and attitudes; minimisation of social reinforcement and promotion of social sanctions for risky driving also need further development and evaluation.

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Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

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The estimation of the critical gap has been an issue since the 1970s, when gap acceptance was introduced to evaluate the capacity of unsignalized intersections. The critical gap is the shortest gap that a driver is assumed to accept. A driver’s critical gap cannot be measured directly and a number of techniques have been developed to estimate the mean critical gaps of a sample of drivers. This paper reviews the ability of the Maximum Likelihood technique and the Probability Equilibrium Method to predict the mean and standard deviation of the critical gap with a simulation of 100 drivers, repeated 100 times for each flow condition. The Maximum Likelihood method gave consistent and unbiased estimates of the mean critical gap. Whereas the probability equilibrium method had a significant bias that was dependent on the flow in the priority stream. Both methods were reasonably consistent, although the Maximum Likelihood Method was slightly better. If drivers are inconsistent, then again the Maximum Likelihood method is superior. A criticism levelled at the Maximum Likelihood method is that a distribution of the critical gap has to be assumed. It was shown that this does not significantly affect its ability to predict the mean and standard deviation of the critical gaps. Finally, the Maximum Likelihood method can predict reasonable estimates with observations for 25 to 30 drivers. A spreadsheet procedure for using the Maximum Likelihood method is provided in this paper. The PEM can be improved if the maximum rejected gap is used.

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A number of Intelligent Transportation Systems (ITS) were used with an advanced driving simulator to assess its influence on driving behavior. Three types of ITS interventions namely, Video in-vehicle (ITS1), Audio in-vehicle (ITS2), and On-road flashing marker (ITS3) were tested. Then, the results from the driving simulator were used as inputs for a developed model using a traffic micro-simulation (Vissim 5.4) in order to assess the safety interventions. Using a driving simulator, 58 participants were required to drive through a number of active and passive crossings with and without an ITS device and in the presence or absence of an approaching train. The effect of driver behavior changing in terms of speed and compliance rate was greater at passive crossings than at active crossings. The difference in speed of drivers approaching ITS devices was very small which indicates that ITS helps drivers encounter the crossings in a safer way. Since the current traffic simulation was not able to replicate a dynamic speed change or a probability of stopping that varies based on different ITS safety devices, some modifications of the current traffic simulation were conducted. The results showed that exposure to ITS devices at active crossings did not influence the drivers’ behavior significantly according to the traffic performance indicators used, such as delay time, number of stops, speed, and stopped delay. On the other hand, the results of traffic simulation for passive crossings, where low traffic volumes and low train headway normally occur, showed that ITS devices improved overall traffic performance.

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It is important that we understand the factors and conditions that shape driver behaviour – those conditions within the road transport system that contribute to driver error and the situations where driver non-compliance to road regulations is likely. This report presents the findings derived from a program of research investigating the nature of errors made by drivers, involving a literature review and an on-road study. The review indicates that, despite significant investigation, the role of different error types in road traffic crashes remains unclear, as does the role of the wider road transport system failures in driver error causation.