926 resultados para driver simulator
Resumo:
Aggressive driving is increasingly a concern for drivers in highly motorised countries. However, the role of driver intent in this behaviour is problematic and there is little research on driver cognitions in relation to aggressive driving incidents. In addition, while drivers who admit to behaving aggressively on the road also frequently report being recipients of similar behaviours, little is known about the relationship between perpetration and victimisation or about how road incidents escalate into the more serious events that feature in capture media attention. The current study used qualitative interviews to explore driver cognitions and underlying motivations for aggressive behaviours on the road. A total of 30 drivers aged 18-49 years were interviewed about their experiences with aggressive driving. A key theme identified in responses was driver aggression as an attempt to manage or modify the behaviour of other road users. Two subthemes were identified and appeared related to separate motivations for aggressive responses: ‘teaching them a lesson’ referred to situations where respondents intended to convey criticism or disapproval, usually of unintended behaviours by the other driver, and thus encourage self-correction; and ‘justified retaliation’ which referred to situations where respondents perceived deliberate intent on the part of the other driver and responded aggressively in return. Mildly aggressive driver behaviour appears to be common. Moreover such behaviour has a sufficiently negative impact on other drivers that it may be worth addressing because of its potential for triggering retaliation in kind or escalation of aggression, thus compromising safety.
Resumo:
Driving is a vigilance task, requiring sustained attention to maintain performance and avoid crashes. Hypovigilance (i.e., marked reduction in vigilance) while driving manifests as poor driving performance and is commonly attributed to fatigue (Dinges, 1995). However, poor driving performance has been found to be more frequent when driving in monotonous road environments, suggesting that monotony plays a role in generating hypovigilance (Thiffault & Bergeron, 2003b). Research to date has tended to conceptualise monotony as a uni-dimensional task characteristic, typically used over a prolonged period of time to facilitate other factors under investigation, most notably fatigue. However, more often than not, more than one exogenous factor relating to the task or operating environment is manipulated to vary or generate monotony (Mascord & Heath, 1992). Here we aimed to explore whether monotony is a multi-dimensional construct that is determined by characteristics of both the task proper and the task environment. The general assumption that monotony is a task characteristic used solely to elicit hypovigilance or poor performance related to fatigue appears to have led to there being little rigorous investigation into the exact nature of the relationship. While the two concepts are undoubtedly linked, the independent effect of monotony on hypovigilance remains largely ignored. Notwithstanding, there is evidence that monotony effects can emerge very early in vigilance tasks and are not necessarily accompanied by fatigue (see Meuter, Rakotonirainy, Johns, & Wagner, 2005). This phenomenon raises a largely untested, empirical question explored in two studies: Can hypovigilance emerge as a consequence of task and/or environmental monotony, independent of time on task and fatigue? In Study 1, using a short computerised vigilance task requiring responses to be withheld to infrequent targets, we explored the differential impacts of stimuli and task demand manipulations on the development of a monotonous context and the associated effects on vigilance performance (as indexed by respone errors and response times), independent of fatigue and time on task. The role of individual differences (sensation seeking, extroversion and cognitive failures) in moderating monotony effects was also considered. The results indicate that monotony affects sustained attention, with hypovigilance and associated performance worse in monotonous than in non-monotonous contexts. Critically, performance decrements emerged early in the task (within 4.3 minutes) and remained consistent over the course of the experiment (21.5 minutes), suggesting that monotony effects can operate independent of time on task and fatigue. A combination of low task demands and low stimulus variability form a monotonous context characterised by hypovigilance and poor task performance. Variations to task demand and stimulus variability were also found to independently affect performance, suggesting that monotony is a multi-dimensional construct relating to both task monotony (associated with the task itself) and environmental monotony (related to characteristics of the stimulus). Consequently, it can be concluded that monotony is multi-dimensional and is characterised by low variability in stimuli and/or task demands. The proposition that individual differences emerge under conditions of varying monotony with high sensation seekers and/or extroverts performing worse in monotonous contexts was only partially supported. Using a driving simulator, the findings of Study 1 were extended to a driving context to identify the behavioural and psychophysiological indices of monotony-related hypovigilance associated with variations to road design and road side scenery (Study 2). Supporting the proposition that monotony is a multi-dimensional construct, road design variability emerged as a key moderating characteristic of environmental monotony, resulting in poor driving performance indexed by decrements in steering wheel measures (mean lateral position). Sensation seeking also emerged as a moderating factor, where participants high in sensation seeking tendencies displayed worse driving behaviour in monotonous conditions. Importantly, impaired driving performance was observed within 8 minutes of commencing the driving task characterised by environmental monotony (low variability in road design) and was not accompanied by a decline in psychophysiological arousal. In addition, no subjective declines in alertness were reported. With fatigue effects associated with prolonged driving (van der Hulst, Meijman, & Rothengatter, 2001) and indexed by drowsiness, this pattern of results indicates that monotony can affect driver vigilance, independent of time on task and fatigue. Perceptual load theory (Lavie, 1995, 2005) and mindlessness theory (Robertson, Manly, Andrade, Baddley, & Yiend, 1997) provide useful theoretical frameworks for explaining and predicting monotony effects by positing that the low load (of task and/or stimuli) associated with a monotonous task results in spare attentional capacity which spills over involuntarily, resulting in the processing of task-irrelevant stimuli or task unrelated thoughts. That is, individuals – even when not fatigued - become easily distracted when performing a highly monotonous task, resulting in hypovigilance and impaired performance. The implications for road safety, including the likely effectiveness of fatigue countermeasures to mitigate monotony-related driver hypovigilance are discussed.
Resumo:
Eco-driving is an initiative driving behavior which aims to reduce fuel consumption and emissions from automobiles. Recently, it has attracted increasing interests and has been adopted by many drivers in Australia. Although many of the studies have revealed considerable benefits in terms of fuel consumption and emissions after utilising eco-driving, most of the literature investigated eco-driving effects on individual driver but not traffic flow. The driving behavior of eco-drivers will potentially affect other drivers and thereby affects the entire traffic flow. To comprehensively assess and understand how effectively eco-driving can perform, therefore, measurement on traffic flow is necessary. In this paper, we proposed and demonstrated an evaluation method based on a microscopic traffic simulator (Aimsun). We focus on one particular eco-driving style which involves moderate and smooth acceleration. We evaluated both traffic performance (travel time) and environmental performance (fuel consumption and CO2 emission) at traffic intersection level in a simple simulation model. The before-and-after comparisons indicated potentially negative impacts when using eco-driving, which highlighted the necessity to carefully evaluate and improve eco-driving before wide promotion and implementation.
Resumo:
Background: A key element of graduated driver licensing systems is the level of support provided by parents. In mid-2007 changes were made to Queensland’s graduated driver licensing system, including amendments to the learner licence with one of the more significant changes requiring learners to record 100 hours of supervised driving practice in a logbook. Prior to mid-2007, there was no minimum supervision requirement. Aims: The aim of this study was to document the experiences of the supervisors of Queensland learner drivers after the changes made to the graduated driver licensing system in mid-2007. Methods: The sample of 552 supervisors of learner drivers was recruited using a combination of convenience and snowball sampling techniques. The internet survey was open for completion between July 2009 and May 2010 and took approximately 15 to 20 minutes for participants to complete. Results: For 59.7 per cent of the participants, this was the first time that they had supervised a learner driver. For 63.2 per cent, they classified themselves as the main supervisor for the learner driver. Participants provided an average of 79.62 hours of supervision (sd = 92.38), while other private supervisors provided 34.89 hours of supervision (sd = 41.74) to the same learner and professional driving instructors 18.55 hours of supervision (sd = 27.54). The vast majority of supervisors recorded all or most of the practice that they provided their learner driver in their log book with most supervisors indicating that they believed that the hours recorded in the learner’s logbook were either accurate or very accurate. While many supervisors stated that they did not receive any advice regarding the supervision of learner drivers, some had received advice from others such as friends or through discussions with a professional driving instructor. Discussion and conclusions: While graduated driver licensing systems implicitly encourage the involvement of parents and other private supervisors, these people tend not to be systematically involved. As demonstrated in this study, private supervisors provide a significant amount of supervised practice and seek to record this practice accurately and honestly in the learner’s logbook. However, even though a significant number of participants reported that this was the first time that they had supervised a learner driver, they accessed little support or guidance for their role. This suggests a need to more overtly encourage and support the role of private supervisors for learner drivers.
Resumo:
The World Health Organisation has highlighted the urgent need to address the escalating global public health crisis associated with road trauma. Low-income and middle-income countries bear the brunt of this, and rapid increases in private vehicle ownership in these nations present new challenges to authorities, citizens, and researchers alike. The role of human factors in the road safety equation is high. In China, human factors have been implicated in more than 90% of road crashes, with speeding identified as the primary cause (Wang, 2003). However, research investigating the factors that influence driving speeds in China is lacking (WHO, 2004). To help address this gap, we present qualitative findings from group interviews conducted with 35 Beijing car drivers in 2008. Some themes arising from data analysis showed strong similarities with findings from highly-motorised nations (e.g., UK, USA, and Australia) and include issues such as driver definitions of ‘speeding’ that appear to be aligned with legislative enforcement tolerances, factors relating to ease/difficulty of speed limit compliance, and the modifying influence of speed cameras. However, unique differences were evident, some of which, to our knowledge, are previously unreported in research literature. Themes included issues relating to an expressed lack of understanding about why speed limits are necessary and a perceived lack of transparency in traffic law enforcement and use of associated revenue. The perception of an unfair system seemed related to issues such as differential treatment of certain drivers and the large amount of individual discretion available to traffic police when administering sanctions. Additionally, a wide range of strategies to overtly avoid detection for speeding and/or the associated sanctions were reported. These strategies included the use of in-vehicle speed camera detectors, covering or removing vehicle licence number plates, and using personal networks of influential people to reduce or cancel a sanction. These findings have implications for traffic law, law enforcement, driver training, and public education in China. While not representative of all Beijing drivers, we believe that these research findings offer unique insights into driver behaviour in China.
Resumo:
Occupational driving crashes are the most common cause of death and injury in the workplace. The physical and psychological outcomes following injury are also very costly to organizations. Thus, safe driving poses a managerial challenge. Some research has attempted to address this issue through modifying discrete and often simple target behaviors (e.g., driver training programs). However, current intervention approaches in the occupational driving field generally do not consider the role of organizational factors in workplace safety. This study adopts the A-B-C framework to identify the contingencies associated with an effective exchange of safety information within the occupational driving context. Utilizing a sample of occupational drivers and their supervisors, this multi-level study examines the contingencies associated with the exchange of safety information within the supervisor-driver relationship. Safety values are identified as an antecedent of the safety information exchange, and the quality of the leader-member exchange relationship and safe driving performance is identified as the behavioral consequences. We also examine the function of role overload as a factor influencing the relationship between safety values and the safety information exchange. Hierarchical Linear Modelling found that role overload moderated the relationship between supervisors’ perceptions of the value given to safety and the safety information exchange. A significant relationship was also found between the safety information exchange and the subsequent quality of the leader-member exchange relationship. Finally, the quality of the leader-member exchange relationship was found to be significantly associated with safe driving performance. Theoretical and practical implications of these results are discussed.
Resumo:
This paper discusses human factors issues of low cost railway level crossings in Australia. Several issues are discussed in this paper including safety at passive level railway crossings, human factors considerations associated with unavailability of a warning device, and a conceptual model for how safety could be compromised at railway level crossings following prolonged or frequent unavailability. The research plans to quantify safety risk to motorists at level crossings using a Human Reliability Assessment (HRA) method, supported by data collected using an advanced driving simulator. This method aims to identify human error within tasks and task units identified as part of the task analysis process. It is anticipated that by modelling driver behaviour the current study will be able to quantify meaningful task variability including temporal parameters, between participants and within participants. The process of complex tasks such as driving through a level crossing is fundamentally context-bound. Therefore this study also aims to quantify those performance-shaping factors that contribute to vehicle train collisions by highlighting changes in the task units and driver physiology. Finally we will also consider a number of variables germane to ensuring external validity of our results. Without this inclusion, such an analysis could seriously underestimate the probabilistic risk assessment.
Resumo:
This paper discusses human factors issues of low cost railway level crossings in Australia. Several issues are discussed in this paper including safety at passive level railway crossings, human factors considerations associated with unavailability of a warning device, and a conceptual model for how safety could be compromised at railway level crossings following prolonged or frequent unavailability. The research plans to quantify safety risk to motorists at level crossings using a Human Reliability Assessment (HRA) method, supported by data collected using an advanced driving simulator. This method aims to identify human error within tasks and task units identified as part of the task analysis process. It is anticipated that by modelling driver behaviour the current study will be able to quantify meaningful task variability including temporal parameters, between participants and within participants. The process of complex tasks such as driving through a level crossing is fundamentally context-bound. Therefore this study also aims to quantify those performance-shaping factors that contribute to vehicle train collisions by highlighting changes in the task units and driver physiology. Finally we will also consider a number of variables germane to ensuring external validity of our results. Without this inclusion, such an analysis could seriously underestimate risk.
Resumo:
Background: Trauma resulting from traffic crashes poses a significant problem in highly motorised countries. Over a million people worldwide are killed annually and 50 million are critically injured as a result of traffic collisions. In Australia, road crashes cost an average of $17 billion annually in personal loss of income and quality of life, organisational losses in productivity and workplace quality, and health care costs. Driver aggression has been identified as a key factor contributing to crashes, and many motorists report experiencing mild forms of aggression (e.g., rude gestures, horn honking). However despite this concern, driver aggression has received relatively little attention in empirical research, and existing research has been hampered by a number of methodological and conceptual shortcomings. Specifically, there has been substantial disagreement regarding what constitutes aggressive driving and a failure to examine both the situational factors and the emotional and cognitive processes underlying driver aggression. To enhance current understanding of aggressive driving, a model of driver aggression that highlights the cognitive and emotional processes at play in aggressive driving incidents is proposed. Aims: The research aims to improve current understanding of the complex nature of driver aggression by testing and refining a model of aggressive driving that incorporates the person-related and situational factors and the cognitive and emotional appraisal processes fundamental to driver aggression. In doing so, the research will assist to provide a clear definition of what constitutes aggressive driving, assist to identify on-road incidents that trigger driver aggression, and identify the emotional and cognitive appraisal processes that underlie driver aggression. Methods: The research involves three studies. Firstly, to contextualise the model and explore the cognitive and emotional aspects of driver aggression, a diary-based study using self-reports of aggressive driving events will be conducted with a general population of drivers. This data will be supplemented by in-depth follow-up interviews with a sub-sample of participants. Secondly, to test generalisability of the model, a large sample of drivers will be asked to respond to video-based scenarios depicting driving contexts derived from incidents identified in Study 1 as inciting aggression. Finally, to further operationalise and test the model an advanced driving simulator will be used with sample of drivers. These drivers will be exposed to various driving scenarios that would be expected to trigger negative emotional responses. Results: Work on the project has commenced and progress on the first study will be reported.
Resumo:
Digital human modeling (DHM), as a convenient and cost-effective tool, is increasingly incorporated into product and workplace design. In product design, it is predominantly used for the development of driver-vehicle systems. Most digital human modeling software tools, such as JACK, RAMSIS and DELMIA HUMANBUILDER provide functions to predict posture and positions for drivers with selected anthropometry according to SAE (Society of Automotive Engineers) Recommended Practices and other ergonomics guidelines. However, few studies have presented 2nd row passenger postural information, and digital human modeling of these passenger postures cannot be performed directly using the existing driver posture prediction functions. In this paper, the significant studies related to occupant posture and modeling were reviewed and a framework of determinants of driver vs. 2nd row occupant posture modeling was extracted. The determinants which are regarded as input factors for posture modeling include target population anthropometry, vehicle package geometry and seat design variables as well as task definitions. The differences between determinants of driver and 2nd row occupant posture models are significant, as driver posture modeling is primarily based on the position of the foot on the accelerator pedal (accelerator actuation point AAP, accelerator heel point AHP) and the hands on the steering wheel (steering wheel centre point A-Point). The objectives of this paper are aimed to investigate those differences between driver and passenger posture, and to supplement the existing parametric model for occupant posture prediction. With the guide of the framework, the associated input parameters of occupant digital human models of both driver and second row occupant will be identified. Beyond the existing occupant posture models, for example a driver posture model could be modified to predict second row occupant posture, by adjusting the associated input parameters introduced in this paper. This study combines results from a literature review and the theoretical modeling stage of a second row passenger posture prediction model project.
Resumo:
Comprehensive BCM plan testing for complex information systems is difficult and expensive, if not infeasible. This paper suggests that a simulator could be employed to ameliorate these problems. A general model for such a BCM simulator is presented, and the implementation of a prototype simulator is described. The simulator reacts to system disturbances by seeking alternative configurations provided within the BCM plan, reporting the resource availabilities in the updated system and identifying any failure to meet the requirements placed on the system. The simulator then explores any changes in data security introduced by the proposed post disturbance configuration and reports any enhanced risk.
Resumo:
The following discussion is in response to a 2010 article published in the Journal of Safety Research by J.C.F. de Winter and D. Dodou entitled “The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis” (Volume 41, Number 6, pp. 463-470, available on sciencedirect.com). The editors are pleased to provide a forum for this exchange and welcome further comments.
Resumo:
Effective digital human model (DHM) simulation of automotive driver packaging ergonomics, safety and comfort depends on accurate modelling of occupant posture, which is strongly related to the mechanical interaction between human body soft tissue and flexible seat components. This paper comprises: a study investigating the component mechanical behaviour of a spring-suspended, production level seat when indented by SAE J826 type, human thigh-buttock representing hard shell; a model of seated human buttock shape for improved indenter design using a multivariate representation of Australian population thigh-buttock anthropometry; and a finite-element study simulating the deflection of human buttock and thigh soft tissue when seated, based on seated MRI. The results of the three studies provide a description of the mechanical properties of the driver-seat interface, and allow validation of future dynamic simulations, involving multi-body and finite-element (FE) DHM in virtual ergonomic studies.