943 resultados para Road Safety, Crash Barrier, Flexible Road Barrier, LS-DYNA, Impact Energy
Resumo:
Motorcyclists are the most crash-prone road-user group in many Asian countries including Singapore; however, factors influencing motorcycle crashes are still not well understood. This study examines the effects of various roadway characteristics, traffic control measures and environmental factors on motorcycle crashes at different location types including expressways and intersections. Using techniques of categorical data analysis, this study has developed a set of log-linear models to investigate multi-vehicle motorcycle crashes in Singapore. Motorcycle crash risks in different circumstances have been calculated after controlling for the exposure estimated by the induced exposure technique. Results show that night-time influence increases crash risks of motorcycles particularly during merging and diverging manoeuvres on expressways, and turning manoeuvres at intersections. Riders appear to exercise more care while riding on wet road surfaces particularly during night. Many hazardous interactions at intersections tend to be related to the failure of drivers to notice a motorcycle as well as to judge correctly the speed/distance of an oncoming motorcycle. Road side conflicts due to stopping/waiting vehicles and interactions with opposing traffic on undivided roads have been found to be as detrimental factors on motorcycle safety along arterial, main and local roads away from intersections. Based on the findings of this study, several targeted countermeasures in the form of legislations, rider training, and safety awareness programmes have been recommended.
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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. To explore the rider behavior, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behavior was developed. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk has been developed. Results show that crash-involved motorcyclists score higher in all three behavioral traits. Aggressive and high risk-taking motorcyclists are more likely to fall under the high vulnerable group while impulsive sensation seeking is not found to be significant. Defining personality types from aggression and risk-taking behavior, “Extrovert” and “Follower” personality type of motorcyclists are more prone to crashes. 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
Resumo:
Singapore crash statistics show that motorcycles are involved in about 54% of crashes at intersections. Moreover, about 46% of fatal and 67% of injury motorcycle crashes occur at signalized intersections. The objective of this study is to identify causal factors affecting the motorcycle crashes at both four-legged and three-legged signalized intersections. Treating the data in time-series cross-section panels, this study explores different Hierarchical Poisson models and found that the model allowing autoregressive lag 1 dependent specification in the error term is the most suitable. Analysis of the results shows the number of lanes at the intersections significantly increases motorcycle crashes largely because of the higher exposure resulting from higher motorcycle accumulation at the stop line. Furthermore, the presence of a wide median at four-legged intersections and an exclusive right-turn lane and an uncontrolled left-turn lane at three-legged intersections exacerbate this potential hazard. Moreover, motorcycle crashes increase on high-speed roadways because of the vulnerability of the motorcyclists. The presence of red light cameras reduces motorcycle crashes significantly on the intersection roadways for both four-legged and three-legged intersections. With the red-light camera, motorcycles are less exposed to conflicts because it is observed that they are more disciplined in queuing at the stop line and less likely to jump start at the start of green.
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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.
Resumo:
Sustainability, smartness and safety are three sole components of a modern transportation system. The objective of this study is to introduce a modern transportation system in the light of a 3‘S’ approach: sustainable, smart and safe. In particular this paper studies the transportation system of Singapore to address how this system is progressing in this three-pronged approach towards a modern transportation system. While sustainability targets environmental justice and social equity without compromising economical efficiency, smartness incorporates qualities like automated sensing, processing and decision making, and action-taking into the transportation system. Since a system cannot be viable without being safe, the safety of the modern transportation system aims minimizing crash risks of all users including motorists, motorcyclists, pedestrians, and bicyclists. Various policy implications and technology applications inside the transportation system of Singapore are discussed to illustrate a modern transportation system within the framework of the 3‘S’ model.
Resumo:
Motorcycles are overrepresented in road traffic crashes and particularly vulnerable at signalized intersections. ‘Motorcycle safety at signalized intersections’ provides an in-depth understanding of hazards of motorcycles at signalized intersections and suggests some targeted countermeasures to alleviate the problem. Motorcycle safety has been examined by establishing innovative statistical models with detailed investigation on specific maneuver behavior of motorcycles at intersections. Results indicate that motorcyclists are over exposed at signalized intersections and the excess exposure is one of main contributors to their vulnerability at intersections. The presence of red light cameras at intersections not only lower motorcycle crashes due to reduced red-light running in the conflicting stream but also decrease their exposure and hence crashes due to a more restrained discharge pattern of motorcycles. Targeted countermeasures should include deployment of red-light cameras, improvement in motorcyclist visibility and increased awareness on motorcyclist vulnerability.
Resumo:
Navigational collisions are one of the major safety concerns for many seaports. Continuing growth of shipping traffic in number and sizes is likely to result in increased number of traffic movements, which consequently could result higher risk of collisions in these restricted waters. This continually increasing safety concern warrants a comprehensive technique for modeling collision risk in port waters, particularly for modeling the probability of collision events and the associated consequences (i.e., injuries and fatalities). A number of techniques have been utilized for modeling the risk qualitatively, semi-quantitatively and quantitatively. These traditional techniques mostly rely on historical collision data, often in conjunction with expert judgments. However, these techniques are hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of collision counts 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 (NTCT), which uses traffic conflicts as an alternative to the collisions for modeling the probability of collision events quantitatively. This article explores the existing techniques for modeling collision risk in port waters. In particular, it identifies the advantages and limitations of the traditional techniques and highlights the potentials of the NTCT in overcoming the limitations. In view of the principles of the NTCT, a structured method for managing collision risk is proposed. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which consequently has great potential for managing collision risk in a fast, reliable and efficient manner.
Resumo:
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.
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In this groundbreaking book, acclaimed sociologist and Pulitzer Prize finalist Elliott Currie draws on years of interviews to offer a profound investigation of what has gone wrong for so many “mainstream” American adolescents. Rejecting such predictable answers as TV violence, permissiveness, and inherent evil, Currie links this crisis to a pervasive “culture of exclusion” fostered by a society in which medications trump guidance and a punitive “zero tolerance” approach to adolescent misbehavior has become the norm. Broadening his inquiry, he dissects the changes in middle-class life that stratify the world into "winners" and "losers," imposing an extraordinarily harsh culture—and not just on kids. Vivid, compelling, and deeply empathetic, The Road to Whatever is a stark indictment of a society that has lost the will—or the capacity—to care.
Resumo:
Aim: The aim of this pilot study is to describe the use of an Emergency Department (ED) at a large metropolitan teaching hospital by patients who speak English or other languages at home. Methods: All data were retrieved from the Emergency Department Information System (EDIS) of this tertiary teaching hospital in Brisbane. Patients were divided into two groups based on the language spoken at home: patients who speak English only at home (SEO) and patients who do not speak English only or speak other language at home (NSEO). Modes of arrival, length of ED stay and the proportion of hospital admission were compared among the two groups of patients by using SPSS V18 software. Results: A total of 69,494 patients visited this hospital ED in 2009 with 67,727 (97.5%) being in the SEO group and 1,281 (1.80%) in the NSEO group. The proportion of ambulance utilisation in arrival mode was significantly higher among SEO 23,172 (34.2%) than NSEO 397 (31.0%), p <0.05. The NSEO patients had longer length of stay in the ED (M = 337.21, SD = 285.9) compared to SEO patients (M= 290.9, SD = 266.8), with 46.3 minutes (95%CI 62.1, 30.5, p <0.001) difference. The admission to the hospital among NSEO was 402 (31.9%) higher than SEO 17,652 (26.6%), p <0.001. Conclusion: The lower utilisation rates of ambulance services, longer length of ED stay and higher hospital admission rates in NSEO patients compared to SEO patients are consistent with other international studies and may be due to the language barriers.
Resumo:
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.
Resumo:
This paper reports safety leaders’ perceptions of safety culture in one of Australasia’s largest construction organisations. A modified Delphi method was used including two rounds of data collection. The first round involved 41 semi-structured interviews with safety leaders within the organisation. The second round involved an online quantitative perception survey, with the same sample, aimed at confirming the key themes identified in the interviews. Participants included Senior Executives, Corporate Managers, Project Managers, Safety Managers and Site Supervisors. Interview data was analysed using qualitative thematic analysis, and the survey data was analysed using descriptive statistics. Leaders’ definitions and descriptions of safety culture were primarily action-oriented and some confusion was evident due to the sometimes implicit nature of culture in organisations. Leadership was identified as a key factor for positive safety culture in the organisation, and there was an emphasis on leaders demonstrating commitment to safety, and being visible to the project-based workforce. Barriers to safety culture improvement were also identified, including the subcontractor management issues, pace of change, and reporting requirements. The survey data provided a quantitative confirmation of the interview themes, with some minor discrepancies. The findings highlight that safety culture is a complex construct, which is difficult to define, even for experts in the organisation. Findings on the key factors indicated consistency with the current literature; however the perceptions of barriers to safety culture offer a new understanding in to how safety culture operates in practice.
Resumo:
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.