789 resultados para driver safety


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Motorised countries have more fatal road crashes in rural areas than in urban areas. In Australia, over two thirds of the population live in urban areas, yet approximately 55 percent of the road fatalities occur in rural areas (ABS, 2006; Tziotis, Mabbot, Edmonston, Sheehan & Dwyer, 2005). Road and environmental factors increase the challenges of rural driving, but do not fully account for the disparity. Rural drivers are less compliant with recommendations regarding the “fatal four” behaviours of speeding, drink driving, seatbelt non-use and fatigue, and the reasons for their lower apparent receptivity for road safety messages are not well understood. Countermeasures targeting driver behaviour that have been effective in reducing road crashes in urban areas have been less successful in rural areas (FORS, 1995). However, potential barriers to receptivity for road safety information among rural road users have not been systematically investigated. This thesis aims to develop a road safety countermeasure that addresses three areas that potentially affect receptivity to rural road safety information. The first is psychological barriers of road users’ attitudes, including risk evaluation, optimism bias, locus of control and readiness to change. A second area is the timing and method of intervention delivery, which includes the production of a brief intervention and the feasibility of delivering it at a “teachable moment”. The third area under investigation is the content of the brief intervention. This study describes the process of developing an intervention that includes content to address road safety attitudes and improve safety behaviours of rural road users regarding the “fatal four”. The research commences with a review of the literature on rural road crashes, brief interventions, intervention design and implementation, and potential psychological barriers to receptivity. This literature provides a rationale for the development of a brief intervention for rural road safety with a focus on driver attitudes and behaviour. The research is then divided into four studies. The primary aim of Study One and Study Two is to investigate the receptivity of rural drivers to road safety interventions, with a view to identifying barriers to the efficacy of these strategies.

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This paper reports on a study investigating preferred driving speeds and frequency of speeding of 320 Queensland drivers. Despite growing community concern about speeding and extensive research linking it to road trauma, speeding remains a pervasive, and arguably, socially acceptable behaviour. This presents an apparent paradox regarding the mismatch between beliefs and behaviours, and highlights the necessity to better understand the factors contributing to speeding. Utilising self-reported behaviour and attitudinal measures, results of this study support the notion of a speed paradox. Two thirds of participants agreed that exceeding the limit is not worth the risks nor is it okay to exceed the posted limit. Despite this, more than half (58.4%) of the participants reported a preference to exceed the 100km/hour speed limit, with one third preferring to do so by 10 to 20 km/hour. Further, mean preferred driving speeds on both urban and open roads suggest a perceived enforcement tolerance of 10%, suggesting that posted limits have limited direct influence on speed choice. Factors that significantly predicted the frequency of speeding included: exposure to role models who speed; favourable attitudes to speeding; experiences of punishment avoidance; and the perceived certainty of punishment for speeding. These findings have important policy implications, particularly relating to the use of enforcement tolerances.

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Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

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The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

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Human error, its causes and consequences, and the ways in which it can be prevented, remain of great interest to road safety practitioners. This paper presents the findings derived from an on-road study of driver errors in which 25 participants drove a pre-determined route using MUARC's On-Road Test Vehicle (ORTeV). In-vehicle observers recorded the different errors made, and a range of other data was collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. The drivers tested made a range of different errors, with speeding violations, both intentional and unintentional, being the most common. Further more detailed analysis of a sub-set of specific error types indicates that driver errors have various causes, including failures in the wider road 'system' such as poor roadway design, infrastructure failures and unclear road rules. In closing, a range of potential error prevention strategies, including intelligent speed adaptation and road infrastructure design, are discussed.

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The term “road toll” quantifies road deaths and attracts media attention, particularly during Easter/Christmas holiday periods. Since the media focuses considerable attention on this issue, we might expect that this would translate into awareness among drivers the number of people killed, which in turn, would hopefully encourage safer driving. Road safety professionals are cognisant of road toll trends but there is little information available to indicate awareness of road fatalities among the general population. This research investigated awareness of fatalities on Queensland and Australian roads among Queensland drivers.

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Mindfulness is a concept which has been widely used in studies on consciousness, but has recently been applied to the understanding of behaviours in other areas, including clinical psychology, meditation, physical activity, education and business. It has been suggested that mindfulness can also be applied to road safety, though this has not yet been researched. A standard definition of mindfulness is “paying attention in a particular way, on purpose in the present moment and non-judgemental to the unfolding of experience moment by moment” [1]. Scales have been developed to measure mindfulness; however, there are different views in the literature on the nature of the mindfulness construct. This paper reviews the issues raised in the literature and arrives at an operational definition of mindfulness considered relevant to road safety. It is further proposed that mindfulness is best construed as operating together with other psychosocial factors to influence road safety behaviours. The specific case of speeding behaviour is outlined, where the psychosocial variables in the Theory of Planned Behaviour (TPB) have been demonstrated to predict both intention to speed and actual speeding behaviour. A role is proposed for mindfulness in enhancing the explanatory and predictive powers of the TPB concerning speeding. The implications of mindfulness for speeding countermeasures are discussed and a program of future research is outlined.

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This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.

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One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

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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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Driver distraction is a research area that continues to receive considerable research interest but the drivers’ perspective is less well documented. The current research focuses on how drivers perceive the risks associated with a range of driver distractions with the aim of identifying features that contribute to their risk perception judgements. Multidimensional scaling analysis was employed to better understand drivers’ risk perceptions for 15 in-vehicle and external distractions. Results identify both salient qualitative characteristics that underpin drivers’ risk perceptions, such as the probability of a crash, as well as identify other features inherent in the distractions that may also contribute to risk perceptions. The implications of the results are discussed for better understanding drivers’ perceptions of distractions and the potential for improving road safety messages related to distracted driving.

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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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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.