983 resultados para Accident risk forecasting.


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A managed team of discipline-experienced and trained later year students are used as Student Success Advisors (SSAs) in the Student Success Program, an intervention program that manages student engagement by identifying and supporting first year students at-risk of disengaging from learning. This report focuses on the recruitment and training of SSAs and the day-to-day challenges they and their managers face. The Nuts & Bolts session provides participants with opportunities to discuss the applicability to their institutional contexts of the recruitment and training processes and the “solutions” to the challenges used at QUT.

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Background and significance: Older adults with chronic diseases are at increasing risk of hospital admission and readmission. Approximately 75% of adults have at least one chronic condition, and the odds of developing a chronic condition increases with age. Chronic diseases consume about 70% of the total Australian health expenditure, and about 59% of hospital events for chronic conditions are potentially preventable. These figures have brought to light the importance of the management of chronic disease among the growing older population. Many studies have endeavoured to develop effective chronic disease management programs by applying social cognitive theory. However, limited studies have focused on chronic disease self-management in older adults at high risk of hospital readmission. Moreover, although the majority of studies have covered wide and valuable outcome measures, there is scant evidence on examining the fundamental health outcomes such as nutritional status, functional status and health-related quality of life. Aim: The aim of this research was to test social cognitive theory in relation to self-efficacy in managing chronic disease and three health outcomes, namely nutritional status, functional status, and health-related quality of life, in older adults at high risk of hospital readmission. Methods: A cross-sectional study design was employed for this research. Three studies were undertaken. Study One examined the nutritional status and validation of a nutritional screening tool; Study Two explored the relationships between participants. characteristics, self-efficacy beliefs, and health outcomes based on the study.s hypothesized model; Study Three tested a theoretical model based on social cognitive theory, which examines potential mechanisms of the mediation effects of social support and self-efficacy beliefs. One hundred and fifty-seven patients aged 65 years and older with a medical admission and at least one risk factor for readmission were recruited. Data were collected from medical records on demographics, medical history, and from self-report questionnaires. The nutrition data were collected by two registered nurses. For Study One, a contingency table and the kappa statistic was used to determine the validity of the Malnutrition Screening Tool. In Study Two, standard multiple regression, hierarchical multiple regression and logistic regression were undertaken to determine the significant influential predictors for the three health outcome measures. For Study Three, a structural equation modelling approach was taken to test the hypothesized self-efficacy model. Results: The findings of Study One suggested that a high prevalence of malnutrition continues to be a concern in older adults as the prevalence of malnutrition was 20.6% according to the Subjective Global Assessment. Additionally, the findings confirmed that the Malnutrition Screening Tool is a valid nutritional screening tool for hospitalized older adults at risk of readmission when compared to the Subjective Global Assessment with high sensitivity (94%), and specificity (89%) and substantial agreement between these two methods (k = .74, p < .001; 95% CI .62-.86). Analysis data for Study Two found that depressive symptoms and perceived social support were the two strongest influential factors for self-efficacy in managing chronic disease in a hierarchical multiple regression. Results of multivariable regression models suggested advancing age, depressive symptoms and less tangible support were three important predictors for malnutrition. In terms of functional status, a standard regression model found that social support was the strongest predictor for the Instrumental Activities of Daily Living, followed by self-efficacy in managing chronic disease. The results of standard multiple regression revealed that the number of hospital readmission risk factors adversely affected the physical component score, while depressive symptoms and self-efficacy beliefs were two significant predictors for the mental component score. In Study Three, the results of the structural equation modelling found that self-efficacy partially mediated the effect of health characteristics and depression on health-related quality of life. The health characteristics had strong direct effects on functional status and body mass index. The results also indicated that social support partially mediated the relationship between health characteristics and functional status. With regard to the joint effects of social support and self-efficacy, social support fully mediated the effect of health characteristics on self-efficacy, and self-efficacy partially mediated the effect of social support on functional status and health-related quality of life. The results also demonstrated that the models fitted the data well with relative high variance explained by the models, implying the hypothesized constructs under discussion were highly relevant, and hence the application for social cognitive theory in this context was supported. Conclusion: This thesis highlights the applicability of social cognitive theory on chronic disease self-management in older adults at risk of hospital readmission. Further studies are recommended to validate and continue to extend the development of social cognitive theory on chronic disease self-management in older adults to improve their nutritional and functional status, and health-related quality of life.

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Information communication and technology (ICT) systems are almost ubiquitous in the modern world. It is hard to identify any industry, or for that matter any part of society, that is not in some way dependent on these systems and their continued secure operation. Therefore the security of information infrastructures, both on an organisational and societal level, is of critical importance. Information security risk assessment is an essential part of ensuring that these systems are appropriately protected and positioned to deal with a rapidly changing threat environment. The complexity of these systems and their inter-dependencies however, introduces a similar complexity to the information security risk assessment task. This complexity suggests that information security risk assessment cannot, optimally, be undertaken manually. Information security risk assessment for individual components of the information infrastructure can be aided by the use of a software tool, a type of simulation, which concentrates on modelling failure rather than normal operational simulation. Avoiding the modelling of the operational system will once again reduce the level of complexity of the assessment task. The use of such a tool provides the opportunity to reuse information in many different ways by developing a repository of relevant information to aid in both risk assessment and management and governance and compliance activities. Widespread use of such a tool allows the opportunity for the risk models developed for individual information infrastructure components to be connected in order to develop a model of information security exposures across the entire information infrastructure. In this thesis conceptual and practical aspects of risk and its underlying epistemology are analysed to produce a model suitable for application to information security risk assessment. Based on this work prototype software has been developed to explore these concepts for information security risk assessment. Initial work has been carried out to investigate the use of this software for information security compliance and governance activities. Finally, an initial concept for extending the use of this approach across an information infrastructure is presented.

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The objective of this chapter is to provide rail practitioners with a practical approach for determining safety requirements of low-cost level crossing warning devices (LCLCWDs) on an Australian railway by way of a case study. LCLCWDs, in theory, allow railway operators to improve the safety of passively controlled crossing by upgrading a larger number of level crossings with the same budget that would otherwise be used to upgrade these using the conventional active level crossing control technologies, e.g. track circuit initiated flashing light systems. The chapter discusses the experience and obstacles of adopting LCLCWDs in Australia, and demonstrates how the risk-based approach may be used to make the case for LCLCWDs.

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The relationship between intellectual functioning and criminal offending has received considerable focus within the literature. While there remains debate regarding the existence (and strength) of this relationship, there is a wider consensus that individuals with below average functioning (in particular cognitive impairments) are disproportionately represented within the prison population. This paper focuses on research that has implications for the effective management of lower functioning individuals within correctional environments as well as the successful rehabilitation and release of such individuals back into the community. This includes a review of the literature regarding the link between lower intelligence and offending and the identification of possible factors that either facilitate (or confound) this relationship. The main themes to emerge from this review are that individuals with lower intellectual functioning continue to be disproportionately represented in custodial settings and that there is a need to increase the provision of specialised programs to cater for their needs. Further research is also needed into a range of areas including: (1) the reason for this over-representation in custodial settings, (2) the existence and effectiveness of rehabilitation and release programs that cater for lower IQ offenders, (3) the effectiveness of custodial alternatives for this group (e.g. intensive corrections orders) and (4) what post-custodial release services are needed to reduce the risk of recidivism.

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Newly licensed drivers on a provisional or intermediate licence have the highest crash risk when compared with any other group of drivers. In comparison, learner drivers have the lowest crash risk. Graduated driver licensing is one countermeasure that has been demonstrated to effectively reduce the crashes of novice drivers. This thesis examined the graduated driver licensing systems in two Australian states in order to better understand the behaviour of learner drivers, provisional drivers and the supervisors of learner drivers. By doing this, the thesis investigated the personal, social and environmental influences on novice driver behaviour as well as providing effective baseline data against which to measure subsequent changes to the licensing systems. In the first study, conducted prior to the changes to the graduated driver licensing system introduced in mid-2007, drivers who had recently obtained their provisional licence in Queensland and New South Wales were interviewed by telephone regarding their experiences while driving on their learner licence. Of the 687 eligible people approached to participate at driver licensing centres, 392 completed the study representing a response rate of 57.1 per cent. At the time the data was collected, New South Wales represented a more extensive graduated driver licensing system when compared with Queensland. The results suggested that requiring learners to complete a mandated number of hours of supervised practice impacts on the amount of hours that learners report completing. While most learners from New South Wales reported meeting the requirement to complete 50 hours of practice, it appears that many stopped practising soon after this goal was achieved. In contrast, learners from Queensland, who were not required to complete a specific number of hours at the time of the survey, tended to fall into three groups. The first group appeared to complete the minimum number of hours required to pass the test (less than 26 hours), the second group completed 26 to 50 hours of supervised practice while the third group completed significantly more practice than the first two groups (over 100 hours of supervised practice). Learner drivers in both states reported generally complying with the road laws and were unlikely to report that they had been caught breaking the road rules. They also indicated that they planned to obey the road laws once they obtained their provisional licence. However, they were less likely to intend to comply with recommended actions to reduce crash risk such as limiting their driving at night. This study also identified that there were relatively low levels of unaccompanied driving (approximately 15 per cent of the sample), very few driving offences committed (five per cent of the sample) and that learner drivers tended to use a mix of private and professional supervisors (although the majority of practice is undertaken with private supervisors). Consistent with the international literature, this study identified that very few learner drivers had experienced a crash (six per cent) while on their learner licence. The second study was also conducted prior to changes to the graduated driver licensing system and involved follow up interviews with the participants of the first study after they had approximately 21 months driving experience on their provisional licence. Of the 392 participants that completed the first study, 233 participants completed the second interview (representing a response rate of 59.4 per cent). As with the first study, at the time the data was collected, New South Wales had a more extensive graduated driver licensing system than Queensland. For instance, novice drivers from New South Wales were required to progress through two provisional licence phases (P1 and P2) while there was only one provisional licence phase in Queensland. Among the participants in this second study, almost all provisional drivers (97.9 per cent) owned or had access to a vehicle for regular driving. They reported that they were unlikely to break road rules, such as driving after a couple of drinks, but were also unlikely to comply with recommended actions, such as limiting their driving at night. When their provisional driving behaviour was compared to the stated intentions from the first study, the results suggested that their intentions were not a strong predictor of their subsequent behaviour. Their perception of risk associated with driving declined from when they first obtained their learner licence to when they had acquired provisional driving experience. Just over 25 per cent of participants in study two reported that they had been caught committing driving offences while on their provisional licence. Nearly one-third of participants had crashed while driving on a provisional licence, although few of these crashes resulted in injuries or hospitalisations. To complement the first two studies, the third study examined the experiences of supervisors of learner drivers, as well as their perceptions of their learner’s experiences. This study was undertaken after the introduction of the new graduated driver licensing systems in Queensland and New South Wales in mid- 2007, providing insights into the impacts of these changes from the perspective of supervisors. The third study involved an internet survey of 552 supervisors of learner drivers. Within the sample, approximately 50 per cent of participants supervised their own child. Other supervisors of the learner drivers included other parents or stepparents, professional driving instructors and siblings. For two-thirds of the sample, this was the first learner driver that they had supervised. Participants had provided an average of 54.82 hours (sd = 67.19) of supervision. Seventy-three per cent of participants indicated that their learners’ logbooks were accurate or very accurate in most cases, although parents were more likely than non-parents to report that their learners’ logbook was accurate (F (1,546) = 7.74, p = .006). There was no difference between parents and non-parents regarding whether they believed the log book system was effective (F (1,546) = .01, p = .913). The majority of the sample reported that their learner driver had had some professional driving lessons. Notwithstanding this, a significant proportion (72.5 per cent) believed that parents should be either very involved or involved in teaching their child to drive, with parents being more likely than non-parents to hold this belief. In the post mid-2007 graduated driver licensing system, Queensland learner drivers are able to record three hours of supervised practice in their log book for every hour that is completed with a professional driving instructor, up to a total of ten hours. Despite this, there was no difference identified between Queensland and New South Wales participants regarding the amount of time that they reported their learners spent with professional driving instructors (X2(1) = 2.56, p = .110). Supervisors from New South Wales were more likely to ensure that their learner driver complied with the road laws. Additionally, with the exception of drug driving laws, New South Wales supervisors believed it was more important to teach safety-related behaviours such as remaining within the speed limit, car control and hazard perception than those from Queensland. This may be indicative of more intensive road safety educational efforts in New South Wales or the longer time that graduated driver licensing has operated in that jurisdiction. However, other factors may have contributed to these findings and further research is required to explore the issue. In addition, supervisors reported that their learner driver was involved in very few crashes (3.4 per cent) and offences (2.7 per cent). This relatively low reported crash rate is similar to that identified in the first study. Most of the graduated driver licensing research to date has been applied in nature and lacked a strong theoretical foundation. These studies used Akers’ social learning theory to explore the self-reported behaviour of novice drivers and their supervisors. This theory was selected as it has previously been found to provide a relatively comprehensive framework for explaining a range of driver behaviours including novice driver behaviour. Sensation seeking was also used in the first two studies to complement the non-social rewards component of Akers’ social learning theory. This program of research identified that both Akers’ social learning theory and sensation seeking were useful in predicting the behaviour of learner and provisional drivers over and above socio-demographic factors. Within the first study, Akers’ social learning theory accounted for an additional 22 per cent of the variance in learner driver compliance with the law, over and above a range of socio-demographic factors such as age, gender and income. The two constructs within Akers’ theory which were significant predictors of learner driver compliance were the behavioural dimension of differential association relating to friends, and anticipated rewards. Sensation seeking predicted an additional six per cent of the variance in learner driver compliance with the law. When considering a learner driver’s intention to comply with the law while driving on a provisional licence, Akers’ social learning theory accounted for an additional 10 per cent of the variance above socio-demographic factors with anticipated rewards being a significant predictor. Sensation seeking predicted an additional four per cent of the variance. The results suggest that the more rewards individuals anticipate for complying with the law, the more likely they are to obey the road rules. Further research is needed to identify which specific rewards are most likely to encourage novice drivers’ compliance with the law. In the second study, Akers’ social learning theory predicted an additional 40 per cent of the variance in self-reported compliance with road rules over and above socio-demographic factors while sensation seeking accounted for an additional five per cent of the variance. A number of Aker’s social learning theory constructs significantly predicted provisional driver compliance with the law, including the behavioural dimension of differential association for friends, the normative dimension of differential association, personal attitudes and anticipated punishments. The consistent prediction of additional variance by sensation seeking over and above the variables within Akers’ social learning theory in both studies one and two suggests that sensation seeking is not fully captured within the non social rewards dimension of Akers’ social learning theory, at least for novice drivers. It appears that novice drivers are strongly influenced by the desire to engage in new and intense experiences. While socio-demographic factors and the perception of risk associated with driving had an important role in predicting the behaviour of the supervisors of learner drivers, Akers’ social learning theory provided further levels of prediction over and above these factors. The Akers’ social learning theory variables predicted an additional 14 per cent of the variance in the extent to which supervisors ensured that their learners complied with the law and an additional eight per cent of the variance in the supervisors’ provision of a range of practice experiences. The normative dimension of differential association, personal attitudes towards the use of professional driving instructors and anticipated rewards were significant predictors for supervisors ensuring that their learner complied with the road laws, while the normative dimension was important for range of practice. This suggests that supervisors who engage with other supervisors who ensure their learner complies with the road laws and provide a range of practice to their own learners are more likely to also engage in these behaviours. Within this program of research, there were several limitations including the method of recruitment of participants within the first study, the lower participation rate in the second study, an inability to calculate a response rate for study three and the use of self-report data for all three studies. Within the first study, participants were only recruited from larger driver licensing centres to ensure that there was a sufficient throughput of drivers to approach. This may have biased the results due to the possible differences in learners that obtain their licences in locations with smaller licensing centres. Only 59.4 per cent of the sample in the first study completed the second study. This may be a limitation if there was a common reason why those not participating were unable to complete the interview leading to a systematic impact on the results. The third study used a combination of a convenience and snowball sampling which meant that it was not possible to calculate a response rate. All three studies used self-report data which, in many cases, is considered a limitation. However, self-report data may be the only method that can be used to obtain some information. This program of research has a number of implications for countermeasures in both the learner licence phase and the provisional licence phase. During the learner phase, licensing authorities need to carefully consider the number of hours that they mandate learner drivers must complete before they obtain their provisional driving licence. If they mandate an insufficient number of hours, there may be inadvertent negative effects as a result of setting too low a limit. This research suggests that logbooks may be a useful tool for learners and their supervisors in recording and structuring their supervised practice. However, it would appear that the usage rates for logbooks will remain low if they remain voluntary. One strategy for achieving larger amounts of supervised practice is for learner drivers and their supervisors to make supervised practice part of their everyday activities. As well as assisting the learner driver to accumulate the required number of hours of supervised practice, it would ensure that they gain experience in the types of environments that they will probably encounter when driving unaccompanied in the future, such as to and from education or work commitments. There is also a need for policy processes to ensure that parents and professional driving instructors communicate effectively regarding the learner driver’s progress. This is required as most learners spend at least some time with a professional instructor despite receiving significant amounts of practice with a private supervisor. However, many supervisors did not discuss their learner’s progress with the driving instructor. During the provisional phase, there is a need to strengthen countermeasures to address the high crash risk of these drivers. Although many of these crashes are minor, most involve at least one other vehicle. Therefore, there are social and economic benefits to reducing these crashes. If the new, post-2007 graduated driver licensing systems do not significantly reduce crash risk, there may be a need to introduce further provisional licence restrictions such as separate night driving and peer passenger restrictions (as opposed to the hybrid version of these two restrictions operating in both Queensland and New South Wales). Provisional drivers appear to be more likely to obey some provisional licence laws, such as lower blood alcohol content limits, than others such as speed limits. Therefore, there may be a need to introduce countermeasures to encourage provisional drivers to comply with specific restrictions. When combined, these studies provided significant information regarding graduated driver licensing programs. This program of research has investigated graduated driver licensing utilising a cross-sectional and longitudinal design in order to develop our understanding of the experiences of novice drivers that progress through the system in order to help reduce crash risk once novice drivers commence driving by themselves.

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Introduction: Previous studies investigating mothers’ sleep in the postpartum period commonly demonstrated elevated levels of sleepiness in this population. A Karolinska Sleepiness Scale (KSS) rating of 5 or above is associated with an exponential increase in vehicle crash risk. To date, no studies have investigated the relationship between mothers’ sleep in the postpartum period and their driving behaviour. Methods: Sleep-wake diary data was collected from 14 mother-infant dyads during two 7-day assessment periods when the infants were 6 and 12 weeks old. The mothers’ indicated all driving episodes during these weeks and their respective sleepiness level using the KSS. Semi-structured interviews were conducted with the mothers when their infant was 12 weeks old. Results: The infants slept significantly more than their mothers at 6 weeks and 12 weeks of age. During both time points, mothers and infants had a similar number of night awakenings (waking between 22:00 and 06:00), with some mothers experiencing greater than 19 awakenings over 7 nights. Notably, 36% of the mothers did not experience a continuous sleep period longer than 4.5 hours when their infant was 6 weeks old. A total of 141 driving episodes were reported during the 7 day assessment period when the infants were 6 weeks old. Over 50% of the driving episodes were denoted with a KSS score of 5 or above. Strategies mothers cited they employed during this period included only driving when feeling alert, postponing driving until another person is present, and driving in the morning when less sleepy. Conclusion: Mothers are experiencing disrupted sleep at night and some mothers do not obtain more than 4.5 hours of continuous sleep during the early postpartum weeks. In this sample, some mothers reported self-regulating driving behaviour, however over half of the driving episodes were undertaken with a sleepiness rating linked with elevated crash risk.

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An earlier study by the Asian Development Bank (ADB) showed that the annual cost of road traffic accidents in 2001 was S$699.36 million which was 0.5% of the annual GDP. This paper attempts to update of the cost estimates of road traffic accidents. More precise methods of computing the human cost, lost output and property damage are adopted which grew in an annual cost of S$610.3 million or 0.338% of the annual GDP in 2003. A more conservative estimate of S$878,000 for fatal accident is also obtained, compared to the earlier figure of S$1.4 million. This study has shown that it is necessary to update the annual traffic accident costs regularly, as the figures vary with the number of accidents which change with time.

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Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

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Introduction: In Singapore, motorcycle crashes account for 50% of traffic fatalities and 53% of injuries. While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood. The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. Methods: To explore the rider behavior, a 61-item questionnaire examining sensation seeking (Zuckerman et al., 1978), impulsiveness (Eysenck et al., 1985), aggressiveness (Buss & Perry, 1992), and risk-taking behavior (Weber et al., 2002) was developed. A total of 240 respondents with at least one year riding experience form the sample that relate behavior to their crash history, traffic penalty awareness, and demographic characteristics. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk was developed. Results and Discussions: Crash-involved motorcyclists scored higher in impulsive sensation seeking, aggression and risk-taking behavior. Aggressive and high risk-taking motorcyclists were respectively 1.30 and 2.21 times more likely to fall under the high crash involvement group while impulsive sensation seeking was not found to be significant. Based on the scores on risk-taking and aggression, the motorcyclists were clustered into four distinct personality combinations namely, extrovert (aggressive, impulsive risk-takers), leader (cautious, aggressive risk-takers), follower (agreeable, ignorant risk-takers), and introvert (self-consciousness, fainthearted risk-takers). “Extrovert” motorcyclists were most prone to crashes, being 3.34 times more likely to involve in crash and 8.29 times more vulnerable than the “introvert”. Mediating factors like demographic characteristics, riding experience, and traffic penalty awareness were found not to be significant in reducing crash risk. Conclusion: The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business.

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This study proposes a full Bayes (FB) hierarchical modeling approach in traffic crash hotspot identification. The FB approach is able to account for all uncertainties associated with crash risk and various risk factors by estimating a posterior distribution of the site safety on which various ranking criteria could be based. Moreover, by use of hierarchical model specification, FB approach is able to flexibly take into account various heterogeneities of crash occurrence due to spatiotemporal effects on traffic safety. Using Singapore intersection crash data(1997-2006), an empirical evaluate was conducted to compare the proposed FB approach to the state-of-the-art approaches. Results show that the Bayesian hierarchical models with accommodation for site specific effect and serial correlation have better goodness-of-fit than non hierarchical models. Furthermore, all model-based approaches perform significantly better in safety ranking than the naive approach using raw crash count. The FB hierarchical models were found to significantly outperform the standard EB approach in correctly identifying hotspots.

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Distraction whilst driving on an approach to a signalized intersection is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. This study examines the decisions of distracted drivers during the onset of amber lights. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of IOWA - National Advanced Driving Simulator. Explanatory variables include age, gender, cell phone use, distance to stop-line, and speed. An iterative combination of decision tree and logistic regression analyses are employed to identify main effects, non-linearities, and interactions effects. Results show that novice (16-17 years) and younger (18-25 years) drivers’ had heightened amber light running risk while distracted by cell phone, and speed and distance thresholds yielded significant interaction effects. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Solutions are needed to combat the use of mobile phones whilst driving.

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Decline of alertness constitutes a normal physiological phenomenon but could be aggravated when drivers operate in monotonous environments, even in rested individuals. Driving performance is impaired and this increases crash risk due to inattention. This paper aims to show that road characteristics - namely road design (road geometry) and road side variability (signage and buildings) – influence subjective assessment of alertness by drivers. This study used a driving simulator to investigate the drivers’ ability to subjectively detect periods of time when their alertness is importantly reduced by varying road geometry and road environment. Driver’s EEG activity is recorded as a reference to evaluate objectively driver's alertness and is compared to self-reported alertness by participants. Twenty-five participants drove on four different scenarios (varying road design and road environment monotony) for forty minutes. It was observed that participants were significantly more accurate in their assessment before the driving task as compared to after (90% versus 60%). Errors in assessment were largely underestimations of their real alertness rather than over-estimations. The ability to detect low alertness as assessed with an EEG was highly dependent on the road monotony. Scenarios with low roadside variability resulted in high overestimation of the real alertness, which was not observed on monotonous road design. The findings have consequences for road safety and suggest that countermeasures to lapses of alertness cannot rely solely on self-assessment from drivers and road design should reduce environments with low variability.