998 resultados para Traffic Gap Acceptance.


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Navigational safety analysis relying on collision statistics is often hampered because of low number of observations. A promising alternative approach that overcomes this problem is proposed in this paper. By analyzing critical vessel interactions this approach proactively measures collision risk in port waters. The proposed method is illustrated for quantitative measurement of collision risks in Singapore port fairways, and validated by examining correlations between the measured risks with those perceived by pilots. This method is an ethically appealing alternative to the collision-based analysis for fast, reliable and effective safety assessment, thus possesses great potential for managing collision risks in port waters.

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Navigational collisions are one of the major safety concerns for many seaports. Despite the extent of work recently done on collision risk analysis in port waters, little is known about the influencing factors of the risk. This paper develops a technique for modeling collision risks in port waterways in order to examine the associations between the risks and the geometric, traffic, and regulatory control characteristics of waterways. A binomial logistic model, which accounts for the correlations in the risks of a particular fairway at different time periods, is derived from traffic conflicts and calibrated for the Singapore port fairways. Estimation results show that the fairways attached to shoreline, traffic intersection and international fairway attribute higher risks, whereas those attached to confined water and local fairway possess lower risks. Higher risks are also found in the fairways featuring higher degree of bend, lower depth of water, higher numbers of cardinal and isolated danger marks, higher density of moving ships and lower operating speed. The risks are also found to be higher for night-time conditions.

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This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.

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Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

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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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Navigational collisions are one of the major safety concerns in many seaports. To address this safety concern, a comprehensive and structured method of collision risk management is necessary. Traditionally management of port water collision risks has been relied on historical collision data. However, this collision-data-based approach is hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of samples for a sound statistical analysis, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these shortcomings is the navigational traffic conflict technique that uses traffic conflicts as an alternative to the collision data. This paper proposes a collision risk management method by utilizing the principles of this technique. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which, consequently, has great potential for managing collision risks in a fast, reliable and efficient manner.

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Purpose: The aim of this study was to examine whether older people are prepared to engage in appropriate falls prevention strategies after discharge from hospital. Design and Methods We used a semi-structured interview to survey older patients about to be discharged from hospital and examined their knowledge regarding falls prevention strategies to utilize in the post-discharge period. The study was part of a prospective cohort study, nested within a larger, randomized controlled trial. Participants (n = 333) were asked to suggest strategies to reduce their falls risk at home after discharge, and their responses were compared with current reported research evidence for falls prevention interventions.  Results Participants’ strategies (n = 629) were classified into 7 categories: behavioral, support while mobilizing, approach to movement, physical environment, visual, medical, and activities or exercise. Although exercise has been identified as an effective falls risk reduction strategy, only 2.9% of participants suggested engaging in exercises. Falls prevention was most often conceptualized by participants as requiring 1 (35.4%) or 2 (40.8%) strategies for avoiding an accidental event, rather than engaging in sustained multiple risk reduction behaviors.  Implications Results demonstrate that older patients have low levels of knowledge about appropriate falls prevention strategies that could be used after discharge in spite of their increased falls risk during this period. Findings suggest that health care workers should design and deliver falls prevention education programs specifically targeted to older people who are to be discharged from hospital.

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Particles emitted by vehicles are known to cause detrimental health effects, with their size and oxidative potential among the main factors responsible. Therefore, understanding the relationship between traffic composition and both the physical characteristics and oxidative potential of particles is critical. To contribute to the limited knowledge base in this area, we investigated this relationship in a 4.5 km road tunnel in Brisbane, Australia. On-road concentrations of ultrafine particles (<100 nm, UFPs), fine particles (PM2.5), CO, CO2 and particle associated reactive oxygen species (ROS) were measured using vehicle-based mobile sampling. UFPs were measured using a condensation particle counter and PM2.5 with a DustTrak aerosol photometer. A new profluorescent nitroxide probe, BPEAnit, was used to determine ROS levels. Comparative measurements were also performed on an above-ground road to assess the role of emission dilution on the parameters measured. The profile of UFP and PM2.5 concentration with distance through the tunnel was determined, and demonstrated relationships with both road gradient and tunnel ventilation. ROS levels in the tunnel were found to be high compared to an open road with similar traffic characteristics, which was attributed to the substantial difference in estimated emission dilution ratios on the two roadways. Principal component analysis (PCA) revealed that the levels of pollutants and ROS were generally better correlated with total traffic count, rather than the traffic composition (i.e. diesel and gasoline-powered vehicles). A possible reason for the lack of correlation with HDV, which has previously been shown to be strongly associated with UFPs especially, was the low absolute numbers encountered during the sampling. This may have made their contribution to in-tunnel pollution largely indistinguishable from the total vehicle volume. For ROS, the stronger association observed with HDV and gasoline vehicles when combined (total traffic count) compared to when considered individually may signal a role for the interaction of their emissions as a determinant of on-road ROS in this pilot study. If further validated, this should not be overlooked in studies of on- or near-road particle exposure and its potential health effects.

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Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

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Differing parental considerations for girls and boys in households are perceived as one of the primary causes of the gender gap in school enrolment and educational attainment in developing countries, particularly in the countries in Sub-Saharan Africa and South Asia. While there are a number of studies on the gender gap focusing on education and health provision in the countries in South Asia, little is known about Bhutan. This thesis aims to explore the gender gap in the intra-household allocation of resources on schooling and health provision for children in Bhutan. This thesis investigates whether boys are shown preference by their parents in terms of educational opportunities, including enrolment and spending on schooling as well as health. To conduct examination, this study makes use of household data from the Bhutan Living Standard Survey of 2007. Using cross-sectional as well as household fixed and random effect approaches, this study attempts to analyse the gender gap in allocation of resources across households as well as within households. The analysis includes characteristics of children and households such as gender and age of children, family wealth, education and gender of household head, number of dependents and the area of residence. The findings reveal a significant gender gap in schooling of children aged six to sixteen in Bhutan. However, no robust evidence of a gender gap has been found in the allocation of health expenditure on children aged less than sixteen. Policy recommendations to alleviate the gender bias in educational opportunities of females are proposed.

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Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time To Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.

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The purpose of traffic law enforcement is to encourage compliant driver behaviour. That is, the threat of an undesirable sanction encourages drivers to comply with traffic laws. However, not all traffic law violations are considered equal. For example, while drink driving is generally seen as socially unacceptable, behaviours such as speeding are arguably less so, and speed enforcement is often portrayed in the popular media as a means of “revenue raising”. The perceived legitimacy of traffic law enforcement has received limited research attention to date. Perceived legitimacy of traffic law enforcement may influence (or be influenced by) attitudes toward illegal driving behaviours, and both of these factors are likely to influence on-road driving behaviour. This study aimed to explore attitudes toward a number of illegal driving behaviours and traffic law enforcement approaches that typically target these behaviours using self-reported data from a large sample of drivers. The results of this research can be used to inform further research in this area, as well as the content of public education and advertising campaigns designed to influence attitudes toward illegal driving behaviours and perceived legitimacy of traffic law enforcement.

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Normative influences on road user behaviour have been well documented and include such things as personal, group, subjective and moral norms. Commonly, normative factors are examined within one cultural context, although a few examples of exploring the issue across cultures exist. Such examples add to our understanding of differences in perceptions of the normative factors that may exert influence on road users and can assist in determining whether successful road safety interventions in one location may be successful in another. Notably, the literature is relatively silent on such influences in countries experiencing rapidly escalating rates of motorization. China is one such country where new drivers are taking to the roads in unprecedented numbers and authorities are grappling with the associated challenges. This paper presents results from qualitative and quantitative research on self-reported driving speeds of car drivers and related issues in Australia and China. Focus group interviews and questionnaires conducted in each country examined normative factors that might influence driving in each cultural context. Qualitative findings indicated perceptions of community acceptance of speeding were present in both countries but appeared more widespread in China, yet quantitative results did not support this difference. Similarly, with regard to negative social feedback from speeding, qualitative findings suggested no embarrassment associated with speeding among Chinese participants and mixed results among Australian participants, yet quantitative results indicated greater embarrassment for Chinese drivers. This issue was also examined from the perspective of self-identity and findings were generally similar across both samples and appear related to whether it is important to be perceived as a skilled/safe driver by others. An interesting and important finding emerged with regard to how Chinese drivers may respond to questions about road safety issues if the answers might influence foreigners’ perceptions of China. In attempting to assess community norms associated with speeding, participants were asked to describe what they would tell a foreign visitor about the prevalence of speeding in China. Responses indicated that if asked by a foreigner, people may answer in a manner that portrayed China as a safe country (e.g., that drivers do not speed), irrespective of the actual situation. This ‘faking good for foreigners’ phenomenon highlights the importance of considering ‘face’ when conducting research in China – a concept absent from the road safety literature. An additional noteworthy finding that has been briefly described in the road safety literature is the importance and strength of the normative influence of social networks (guanxi) in China. The use of personal networks to assist in avoiding penalties for traffic violations was described by Chinese participants and is an area that could be addressed to strengthen the deterrent effect of traffic law enforcement. Overall, the findings suggest important considerations for developing and implementing road safety countermeasures in different cultural contexts.