315 resultados para Automobile driving on highways


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A new method for the detection of abnormal vehicle trajectories is proposed. It couples optical flow extraction of vehicle velocities with a neural network classifier. Abnormal trajectories are indicative of drunk or sleepy drivers. A single feature of the vehicle, eg., a tail light, is isolated and the optical flow computed only around this feature rather than at each pixel in the image.

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Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.

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In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

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Alcohol-related driving is a longstanding, serious problem in China (Li, Xie, Nie, & Zhang, 2012). On 1st May, 2011 a national law was introduced to criminalize drunk driving, and imposed serious penalties including jail for driving with a blood alcohol level of above 80mg/100ml. This pilot study, undertaken a year after introduction of the law, sought traffic police officers’ perceptions of drink driving and the practice of breath alcohol testing (BAT) in a large city in Guangdong Province, southern China. A questionnaire survey and semi-structured interviews were used to gain an in-depth understanding of issues relevant to alcohol-related driving. Fifty-five traffic police officers were recruited for the survey and six traffic police officers with a variety of working experience including roadside alcohol breath testing, traffic crash investigation and police resourcing were interviewed individually. The officers were recruited by the first author with the assistance of the staff from Guangdong Institute of Public Health, Centre for Disease Control and Prevention (CDC). Interview participants reported three primary reasons why people drink and drive: 1) being prepared to take the chance of not being apprehended by police; 2) the strong traditional Chinese drinking culture; and 3) insufficient public awareness about the harmfulness of drink driving. Problems associated with the process of breath alcohol testing (BAT) were described and fit broadly into two categories: resourcing and avoiding detection. It was reported that there were insufficient traffic police officers to conduct routine traffic policing, including alcohol testing. Police BAT equipment was considered sufficient for routine traffic situations but not highway traffic operations. Local media and posters are used by the Public Security Bureau which is responsible for education about safe driving but participants thought that the education campaigns are limited in scope. Participants also described detection avoidance strategies used by drivers including: changing route; ignoring a police instruction to stop; staying inside the vehicle with windows and doors locked to avoid being tested; intentionally not performing breath tests correctly; and arguing with officers. This pilot study provided important insights from traffic police in one Chinese city which suggest there may be potential unintended effects of introducing more severe penalties including a range of strategies reportedly used by drivers to avoid detection. Recommendations for future research include a larger study to confirm these findings and examine the training and education of drivers; the focus and reach of publicity; and possible resource needs to support police enforcement.

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Impaired driver alertness increases the likelihood of drivers’ making mistakes and reacting too late to unexpected events while driving. This is particularly a concern on monotonous roads, where a driver’s attention can decrease rapidly. While effective countermeasures do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real-time. The aim of this study is to predict drivers’ level of alertness through surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, data was collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device. Various classification models were tested from linear regressions to Bayesians and data mining techniques. Results indicated that Neural Networks were the most efficient model in detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to 5 minutes in advance with 90% accuracy, using surrogate measures such as time to line crossing, blink frequency and skin conductance level. Such a method could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring, in real-time, drivers' behavior on highways.

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OBJECTIVE: To examine whether some drivers with hemianopia or quadrantanopia display safe driving skills on the road compared with drivers with normal visual fields. ---------- METHOD: An occupational therapist evaluated 22 people with hemianopia, 8 with quadrantanopia, and 30 with normal vision for driving skills during naturalistic driving using six rating scales. ---------- RESULTS: Of drivers with normal vision, >90% drove flawlessly or had minor errors. Although drivers with hemianopia were more likely to receive poorer ratings for all skills, 59.1%–81.8% performed with no or minor errors. A skill commonly problematic for them was lane keeping (40.9%). Of 8 drivers with quadrantanopia, 7 (87.5%) exhibited no or minor errors. ---------- CONCLUSION: This study of people with hemianopia or quadrantanopia with no lateral spatial neglect highlights the need to provide individual opportunities for on-road driving evaluation under natural traffic conditions if a person is motivated to return to driving after brain injury.

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Driving on motorways has largely been reduced to a lane-keeping task with cruise control. Rapidly, drivers are likely to get bored with such a task and take their attention away from the road. This is of concern in terms of road safety – particularly for professional drivers - since inattention has been identified as one of the main contributing factors to road crashes and is estimated to be involved in 20 to 30% of these crashes. Furthermore, drivers are not aware that their vigilance level has decreased and that their driving performance is impaired. Intelligent Transportation System (ITS) intervention can be used as a countermeasure against vigilance decrement. This paper aims to identify a variety of metrics impacted during monotonous driving - ranging from vehicle data to physiological variables - and relate them to two monotonous factors namely the monotony of the road design (straightness) and the monotony of the environment (landscape, signage, traffic). Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). The two monotonous factors are varied (high and low) leading to the use of four different driving scenarios (40 minutes each). We show with Generalised Linear Mixed Models that driver performance decreases faster when the road is monotonous. We also highlight that road monotony impairs a variety of driving performance and vigilance measures, ranging from speed, lateral position of the vehicle to physiological measurements such as heart rate variability, blink frequency and electrodermal activity. This study informs road designers of the importance of having a varied road environment. It also provides a range of metrics that can be used to detect in real-time the impairment of driving performance on monotonous roads. Such knowledge could result in the development of an in-vehicle device warning drivers at early signs of driving performance impairment on monotonous roads.

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Driving is often nominated as problematic by individuals with chronic whiplash associated disorders (WAD), yet driving-related performance has not been evaluated objectively. The purpose of this study was to test driving-related performance in persons with chronic WAD against healthy controls of similar age, gender and driving experience to determine if driving-related performance in the WAD group was sufficiently impaired to recommend fitness to drive assessment. Driving-related performance was assessed using an advanced driving simulator during three driving scenarios; freeway, residential and a central business district (CBD). Total driving duration was approximately 15 min. Five driving tasks which could cause a collision (critical events) were included in the scenarios. In addition, the effect of divided attention (identify red dots projected onto side or rear view mirrors) was assessed three times in each scenario. Driving performance was measured using the simulator performance index (SPI) which is calculated from 12 measures. z-Scores for all SPI measures were calculated for each WAD subject based on mean values of the control subjects. The z-scores were then averaged for the WAD group. A z-score of ≤−2 indicated a driving failing grade in the simulator. The number of collisions over the five critical events was compared between the WAD and control groups as was reaction time and missed response ratio in identifying the red dots. Seventeen WAD and 26 control subjects commenced the driving assessment. Demographic data were comparable between the groups. All subjects completed the freeway scenario but four withdrew during the residential and eight during the CBD scenario because of motion sickness. All scenarios were completed by 14 WAD and 17 control subjects. Mean z-scores for the SPI over the three scenarios was statistically lower in the WAD group (−0.3 ± 0.3; P < 0.05) but the score was not below the cut-off point for safe driving. There were no differences in the reaction time and missed response ratio in divided attention tasks between the groups (All P > 0.05). Assessment of driving in an advanced driving simulator for approximately 15 min revealed that driving-related performance in chronic WAD was not sufficiently impaired to recommend the need for fitness to drive assessment.

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Background Situational driving factors, including fatigue, distraction, inattention and monotony, are recognised killers in Australia, contributing to an estimated 40% of fatal crashes and 34% of all crashes . More often than not the main contributing factor is identified as fatigue, yet poor driving performance has been found to emerge early in monotonous conditions, independent of fatigue symptoms and time on task. This early emergence suggests an important role for monotony. However, much road safety research suggests that monotony is solely a task characteristic that directly causes fatigue and associated symptoms and there remains an absence of consistent evidence explaining the relationship. Objectives We report an experimental study designed to disentangle the characteristics and effects of monotony from those associated with fatigue. Specifically, we examined whether poor driving performance associated with hypovigilance emerges as a consequence of monotony, independent of fatigue. We also examined whether monotony is a multidimensional construct, determined by environmental characteristics and/or task demands that independently moderate sustained attention and associated driving performance. Method Using a driving simulator, participants completed four, 40 minute driving scenarios. The scenarios varied in the degree of monotony as determined by the degree of variation in road design (e.g., straight roads vs. curves) and/or road side scenery. Fatigue, as well as a number of other factors known to moderate vigilance and driving performance, was controlled for. To track changes across time, driving performance was assessed in five minute time periods using a range of behavioural, subjective and physiological measures, including steering wheel movements, lane positioning, electroencephalograms, skin conductance, and oculomotor activity. Results Results indicate that driving performance is worse in monotonous driving conditions characterised by low variability in road design. Critically, performance decrements associated with monotony emerge very early, suggesting monotony effects operate independent of fatigue. Conclusion Monotony is a multi-dimensional construct where, in a driving context, roads containing low variability in design are monotonous and those high in variability are non-monotonous. Importantly, low variability in road side scenery does not appear to exacerbate monotony or associated poor performance. However, high variability in road side scenery can act as a distraction and impair sustained attention and poor performance when driving on monotonous roads. Furthermore, high sensation seekers seem to be more susceptible to distraction when driving on monotonous roads. Implications of our results for the relationship between monotony and fatigue, and the possible construct-specific detection methods in a road safety context, will be 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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This study explored the psychological influences of hands-free and hand-held mobile phone use while driving. Participants were 796 Australian drivers aged 17 to 76 years who owned mobile phones. A cross-sectional survey assessed frequency of calling and text messaging while driving (overall, hands-free, hand-held) as well as drivers’ behavioural, normative, and control beliefs relating to mobile phone use while driving. Irrespective of handset type, 43% of drivers reported answering calls while driving on a daily basis, followed by making calls (36%), reading text messages (27%), and sending text messages (18%). In total, 63.9% of drivers did not own hands-free kits and, of the drivers that owned hand-free kits, 32% did not use it most or all of the time. Significant differences were found in the behavioural, normative, and control beliefs of frequent and infrequent users of both types of handset while driving. As expected, frequent users reported more advantages of, more approval from others for, and fewer barriers that would prevent them from, using either a hands-free or a hand-held mobile phone while driving than infrequent users. Campaigns to reduce mobile phone use while driving should attempt to minimise the perceived benefits of the behaviour and highlight the risks of this unsafe driving practice.

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Monotony has been identified as a contributing factor to road crashes. Drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.

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A range of interventions are being implemented in Australia to apprehend and deter drug driving behaviour, in particular the recent implementation of random roadside drug testing procedures in Queensland. Given this countermeasure has a strong deterrence foundation, it is of interest to determine whether deterrence-based perceptual factors are influencing this offending behaviour or whether self-reported drug driving is heavily dependent upon illicit substance consumption levels and past offending behaviour. This study involves a sample of Queensland motorists (N = 898) who completed a self-report questionnaire that collected a range of information, including drug driving and drug consumption practices, conviction history, and perceptual deterrence factors. The aim was to examine what factors influence current drug driving behaviours. Analysis of the collected data revealed that approximately 20% of participants reported drug driving at least once in the last six months. Overall, there was considerable variability in the respondents' perceptions regarding the certainty, severity and swiftness of legal sanctions, although the largest proportion of the sample did not consider such sanctions to be certain, severe or swift. In regard to predicting those who intended to drug drive again in the future, a combination of perceptual and behavioural-based factors were associated with such intentions. However, a closer examination revealed that behaviours, rather than perceptions, proved to have a greater level of influence on the current sample's future intentions to offend. This paper further outlines the major findings of the study and highlights that multi-modal interventions are most likely required to reduce the prevalence of drug driving on public roads.