950 resultados para Automobile driving on highways


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Police services in a number of Australian states and overseas jurisdictions have begun to implement or consider random road-side drug testing of drivers. This paper outlines research conducted to provide an estimate of the extent of drug driving in a sample of Queensland drivers in regional, rural and metropolitan areas. Oral fluid samples were collected from 2657 Queensland motorists and screened for illicit substances including cannabis (delta 9 tetrahydrocannibinol [THC]), amphetamines, ecstasy, and cocaine. Overall, 3.8% of the sample (n = 101) screened positive for at least one illicit substance, although multiple drugs were identified in a sample of 23 respondents. The most common drugs detected in oral fluid were ecstasy (n = 53), and cannabis (n = 46) followed by amphetamines (n = 23). A key finding was that cannabis was confirmed as the most common self-reported drug combined with driving and that individuals who tested positive to any drug through oral fluid analysis were also more likely to report the highest frequency of drug driving. Furthermore, a comparison between drug vs. drink driving detection rates for one region of the study, revealed a higher detection rate for drug driving (3.8%) vs. drink driving (0.8%). This research provides evidence that drug driving is relatively prevalent on Queensland roads, and may in fact be more common than drink driving. This paper will further outline the study findings’ and present possible directions for future drug driving research.

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Crash data involving taxis indicates that such drivers are over represented in crashes and are one to two times more likely to be involved in a fatality crash. This study reports on the pre intervention survey to provide a baseline measure of the self-reported attitudes and corresponding driving behaviours of a sample of taxi drivers. Results indicate that some taxi drivers willingly admit to engaging in unsafe driving practices. In addition, preliminary results of a post intervention survey revealed that taxi drivers’ safety perceptions, attitude and behaviours improved after completing a Driving Diary intervention.

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Work-related driving safety is an emerging concern for Australian and overseas organisations. An in depth investigation was undertaken into a group of fleet drivers’ attitudes regarding what personal and environment factors have the greatest impact upon driving behaviours. A number of new and unique factors not previously identified were found including: vehicle features, vehicle ownership, road conditions, weather, etc. The major findings of the study are discussed in regards to practical solutions to improve fleet safety.

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Objective: To define characteristics of vehicle crashes occurring on rural private property in north Queensland with an exploration of associated risk factors. Design: Descriptive analysis of private property crash data collected by the Rural and Remote Road Safety Study. Setting: Rural and remote north Queensland. Participants: A total of 305 vehicle controllers aged 16 years or over hospitalised at Atherton, Cairns, Mount Isa or Townsville for at least 24 hours as a result of a vehicle crash. Main outcome measure: A structured questionnaire completed by participants covering crash details, lifestyle and demographic characteristics, driving history, medical history, alcohol and drug use and attitudes to road use. Results: Overall, 27.9% of interviewees crashed on private property, with the highest proportion of private road crashes occurring in the North West Statistical Division (45%). Risk factors shown to be associated with private property crashes included male sex, riding off-road motorcycle or all-terrain vehicle, first-time driving at that site, lack of licence for vehicle type, recreational use and not wearing a helmet or seatbelt. Conclusions: Considerable trauma results from vehicle crashes on rural private property. These crashes are not included in most crash data sets, which are limited to public road crashes. Legislation and regulations applicable to private property vehicle use are largely focused on workplace health and safety, yet work-related crashes represent a minority of private property crashes in north Queensland.

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Road crashes are now the most common cause of work-related injury, death and absence in a number of countries. Given the impact of workrelated driving crashes on social and economic aspects of business and the community, workrelated road safety and risk management has received increasing attention in recent years. However, limited academic research has progressed on improving safety within the work-related driving sector. The aim of this paper is to present a review of work-related driving safety research to date, and provide an intervention framework for the future development and implementation of workrelated driving safety intervention strategies.

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Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Particularly, highway design reduces the driving task mainly to a lane-keeping one. It contributes to hypovigilance and road crashes as drivers are often not aware that their driving behaviour is impaired. Monotony increases fatigue, however, the fatigue community has mainly focused on endogenous factors leading to fatigue such as sleep deprivation. This paper focuses on the exogenous factor monotony which contributes to hypovigilance. Objective measurements of the effects of monotonous driving conditions on the driver and the vehicle's dynamics is systematically reviewed with the aim of justifying the relevance of the need for a mathematical framework that could predict hypovigilance in real-time. Although electroencephalography (EEG) is one of the most reliable measures of vigilance, it is obtrusive. This suggests to predict from observable variables the time when the driver is hypovigilant. Outlined is a vision for future research in the modelling of driver vigilance decrement due to monotonous driving conditions. A mathematical model for predicting drivers’ hypovigilance using information like lane positioning, steering wheel movements and eye blinks is provided. Such a modelling of driver vigilance should enable the future development of an in-vehicle device that detects driver hypovigilance in advance, thus offering the potential to enhance road safety and prevent road crashes.

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In this paper, cognitive load analysis via acoustic- and CAN-Bus-based driver performance metrics is employed to assess two different commercial speech dialog systems (SDS) during in-vehicle use. Several metrics are proposed to measure increases in stress, distraction and cognitive load and we compare these measures with statistical analysis of the speech recognition component of each SDS. It is found that care must be taken when designing an SDS as it may increase cognitive load which can be observed through increased speech response delay (SRD), changes in speech production due to negative emotion towards the SDS, and decreased driving performance on lateral control tasks. From this study, guidelines are presented for designing systems which are to be used in vehicular environments.

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Fatigue in the postnatal period is such a common experience for most mothers that the term ‘postpartum fatigue’ (PPF) has been coined to describe it. When new mothers experience extreme fatigue, it follows that their physical health, mental health, and social-wellbeing is negatively affected. It is interesting to note that there is a distinct lack of empirical investigations focusing on the link between PPF and increased risk of injury; particularly when the links between fatigue and increased risk of road crashes are well documented. The purpose of this investigation was to undertake pilot research to develop an understanding of the duration of PPF and the performance impairments experienced by new mothers when involved in safety-sensitive activities, such as driving a motor vehicle. Semi-structured interviews were undertaken with women (N = 24) at 12 weeks postpartum living in South-east Queensland, Australia. Key themes were identified; with a particular emphasis towards understanding the link between the participant’s experience of postpartum fatigue and the impact this has on their overall cognitive and physiological functioning, as well as their experience of the driving task. Further, sleep/wake data was collected and using the Karolinska Sleepiness Scale (KSS) the potential crash risk for this group of mothers is discussed. It is proposed that the findings of this investigation could be used to improve current knowledge among new mothers and practitioners regarding the mechanisms and consequences of fatigue and to inform interventions that lead to a decreased risk of injury associated with postpartum fatigue.

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The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. Experienced drivers have better hazard perception ability compared to inexperienced drivers. Eye gaze patterns have been found to be an indicator of the driver's competency level. The aim of this paper is to develop an in-vehicle system which correlates information about the driver's gaze and vehicle dynamics, which is then used to assist driver trainers in assessing driving competency. This system allows visualization of the complete driving manoeuvre data on interactive maps. It uses an eye tracker and perspective projection algorithms to compute the depth of gaze and plots it on Google maps. This interactive map also features the trajectory of the vehicle and turn indicator usage. This system allows efficient and user friendly analysis of the driving task. It can be used by driver trainers and trainees to understand objectively the risks encountered during driving manoeuvres. This paper presents a prototype that plots the driver's eye gaze depth and direction on an interactive map along with the vehicle dynamics information. This prototype will be used in future to study the difference in gaze patterns in novice and experienced drivers prior to a certain manoeuvre.

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Young adults are at the greatest risk of experiences road trauma disproportionately to those in other age groups. While the influence of peers is commonly associated with motor vehicle crashes and injury few studies examine whether their influence can be positive. In particular friends may be able to actively intervene to reduce the likelihood of risky driving (e.g. speeding, drink driving or drug driving) and alcohol use. The aim of this paper is to conduct a systematic review on intervening in risky driving behaviour including the situations in which it is likely or unlikely to occur, factors associated with individuals who might or report having intervened and any evaluated programs that make use of such strategies. In addition a study was conducted with 247 first year university students (32% males) to examine whether young adults report engaging in protective behaviour with their peers in South-east Queensland. In particular, if they intervene if their friends are about to drive after drinking, drive after taking illicit drugs or when speeding. It examines any differences in reported likelihood of discouraging such illegal and dangerous behaviour (in the past 12 months prior to the survey). Findings showed that young adults (17-25 years) did indeed report protective behaviour in relation to friends’ drink driving, drug driving, speeding and binge drinking. Conclusions will be drawn regarding important considerations in developing positive strategies and advertising campaigns that encourage positive behaviours (e.g. ‘don’t let mates drink and drive’).

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Research has highlighted the relationship between vehicle speed and increased crash risk and severity. Evidence suggests that police speed enforcement, in particular speed camera operations, can be an effective tool for reducing traffic crashes. A quantitative survey of Queensland drivers (n = 852) was conducted to investigate the impact of police speed enforcement methods on self-reported speeding behaviour. Results indicate that visible enforcement was associated with significantly greater self-reported compliance than covert operations irrespective of the mobility of the approach, and the effects on behaviour were longer lasting. The mobility of operations appeared to be moderated the visibility of the approach. Specifically, increased mobility was associated with increase reported compliant behaviour, but only for covert operations, and increased longevity of reported compliant behaviour, but only for overt operations. The perceived effectiveness of various speed enforcement approaches are also analysed across a range of driving scenarios. Results are discussed in light of the small effect sizes. Recommendations for policy and future research are presented.

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The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

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OBJECTIVES: To quantify the driving difficulties of older adults using a detailed assessment of driving performance and to link this with self-reported retrospective and prospective crashes. DESIGN: Prospective cohort study. SETTING: On-road driving assessment. PARTICIPANTS: Two hundred sixty-seven community-living adults aged 70 to 88 randomly recruited through the electoral roll. MEASUREMENTS: Performance on a standardized measure of driving performance. RESULTS: Lane positioning, approach, and blind spot monitoring were the most common error types, and errors occurred most frequently in situations involving merging and maneuvering. Drivers reporting more retrospective or prospective crashes made significantly more driving errors. Driver instructor interventions during self-navigation (where the instructor had to brake or take control of the steering to avoid an accident) were significantly associated with higher retrospective and prospective crashes; every instructor intervention almost doubled prospective crash risk. CONCLUSION: These findings suggest that on-road driving assessment provides useful information on older driver difficulties, with the self-directed component providing the most valuable information.

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Social and psychological theories have provided a plethora of evidence showing that the physical difficulty to express appropriate social interactions between drivers expresses itself in aggression, selfish driving and anti-social behaviour. Therefore there is a need to improve interactions between drivers and allow clearer collective decision making between them. Personal characteristics and the driving situations play strong roles in driver’s aggression. Our approach is centered around the driving situation as opposed to focusing on personality characteristics. It examines aggression and manipulates contextual variables such as driver’s eye contact exchanges. This paper presents a new unobtrusive in-vehicle system that aims at communicating drivers’ intentions, elicit social responses and increasing mutual awareness. It uses eye gaze as a social cue to affect collective decision making with the view to contribute to safe driving. The authors used a driving simulator to design a case control experiment in which eye gaze movements are conveyed with an avatar. Participants were asked to drive through different types of intersections. An avatar representing the head of the other driver was displayed and driver behaviour was analysed. Significant eye gaze pattern difference where observed when an avatar was displayed. Drivers cautiously refer to the avatar when information is required on the intention of others (e.g. when they do not have the right of way). The majority of participants reported the perception of “being looked at”. The number of glances and time spent gazing at the avatar did not indicate an unsafe distraction by standards of in-vehicle device ergonomic design. Avatars were visually consulted primarily in less demanding driving situations, which underlines their non-distractive nature.

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Secondary tasks such as cell phone calls or interaction with automated speech dialog systems (SDSs) increase the driver’s cognitive load as well as the probability of driving errors. This study analyzes speech production variations due to cognitive load and emotional state of drivers in real driving conditions. Speech samples were acquired from 24 female and 17 male subjects (approximately 8.5 h of data) while talking to a co-driver and communicating with two automated call centers, with emotional states (neutral, negative) and the number of necessary SDS query repetitions also labeled. A consistent shift in a number of speech production parameters (pitch, first format center frequency, spectral center of gravity, spectral energy spread, and duration of voiced segments) was observed when comparing SDS interaction against co-driver interaction; further increases were observed when considering negative emotion segments and the number of requested SDS query repetitions. A mel frequency cepstral coefficient based Gaussian mixture classifier trained on 10 male and 10 female sessions provided 91% accuracy in the open test set task of distinguishing co-driver interactions from SDS interactions, suggesting—together with the acoustic analysis—that it is possible to monitor the level of driver distraction directly from their speech.