Using game technologies to improve the safety of construction plant operations

Many accidents occur world-wide in the use of construction plant and equipment, and safety training is considered by many to be one of the best approaches to their prevention. However, current safety training methods/tools are unable to provide trainees with the hands-on practice needed. Game technology-based safety training platforms have the potential to overcome this problem in a virtual environment. One such platform is described in this paper - its characteristics are analysed and its possible contribution to safety training identified. This is developed and tested by means of a case study involving three major pieces of construction plant, which successfully demonstrates that the platform can improve the process and performance of the safety training involved in their operation. This research not only presents a new and useful solution to the safety training of construction operations, but illustrates the potential use of advanced technologies in solving construction industry problems in general.

Accident risk identification and its impact analyses for strategic construction safety management

The study presented in this paper reviewed 9,358 accidents which occurred in the U.S. construction industry between 2002 and 2011, in order to understand the relationships between the risk factors and injury severity (e.g. fatalities, hospitalized injuries, or non-hospitalized injuries) and to develop a strategic prevention plan to reduce the likelihood of fatalities where an accident is unavoidable. The study specifically aims to: (1) verify the relationships among risk factors, accident types, and injury severity, (2) determine significant risk factors associated with each accident type that are highly correlated to injury severity, and (3) analyze the impact of the identified key factors on accident and fatality occurrence. The analysis results explained that safety managers’ roles are critical to reducing human-related risks—particularly misjudgement of hazardous situations—through safety training and education, appropriate use of safety devices and proper safety inspection. However, for environment-related factors, the dominant risk factors were different depending on the different accident types. The outcomes of this study will assist safety managers to understand the nature of construction accidents and plan for strategic risk mitigation by prioritizing high frequency risk factors to effectively control accident occurrence and manage the likelihood of fatal injuries on construction sites.

Eigenvoice modeling for cross likelihood ratio based speaker clustering : a Bayesian approach

This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Bayesian versus frequentist statistical inference for investi gating a one-off cancer cluster reported to a health department

Background The problem of silent multiple comparisons is one of the most difficult statistical problems faced by scientists. It is a particular problem for investigating a one-off cancer cluster reported to a health department because any one of hundreds, or possibly thousands, of neighbourhoods, schools, or workplaces could have reported a cluster, which could have been for any one of several types of cancer or any one of several time periods. Methods This paper contrasts the frequentist approach with a Bayesian approach for dealing with silent multiple comparisons in the context of a one-off cluster reported to a health department. Two published cluster investigations were re-analysed using the Dunn-Sidak method to adjust frequentist p-values and confidence intervals for silent multiple comparisons. Bayesian methods were based on the Gamma distribution. Results Bayesian analysis with non-informative priors produced results similar to the frequentist analysis, and suggested that both clusters represented a statistical excess. In the frequentist framework, the statistical significance of both clusters was extremely sensitive to the number of silent multiple comparisons, which can only ever be a subjective "guesstimate". The Bayesian approach is also subjective: whether there is an apparent statistical excess depends on the specified prior. Conclusion In cluster investigations, the frequentist approach is just as subjective as the Bayesian approach, but the Bayesian approach is less ambitious in that it treats the analysis as a synthesis of data and personal judgements (possibly poor ones), rather than objective reality. Bayesian analysis is (arguably) a useful tool to support complicated decision-making, because it makes the uncertainty associated with silent multiple comparisons explicit.

Fatal motorcycle crashes in north Queensland : characteristics and potential interventions

Aims: The Rural and Remote Road Safety Study (RRRSS) addresses a recognised need for greater research on road trauma in rural and remote Australia, the costs of which are disproportionately high compared with urban areas. The 5-year multi-phase study with whole-of-government support concluded in June 2008. Drawing on RRRSS data, we analysed fatal motorcycle crashes which occurred over 39 months to provide a description of crash characteristics, contributing factors and people involved. The descriptive analysis and discussion may inform development of tailored motorcycle safety interventions. Methods: RRRSS criteria sought vehicle crashes resulting in death or hospitalisation for 24 hours minimum of at least 1 person aged 16 years or over, in the study area defined roughly as the Queensland area north from Bowen in the east and Boulia in the west (excluding Townsville and Cairns urban areas). Fatal motorcycle crashes were selected from the RRRSS dataset. Analysis considered medical data covering injury types and severity, evidence of alcohol, drugs and prior medical conditions, as well as crash descriptions supplied by police to Queensland Transport on contributing circumstances, vehicle types, environmental conditions and people involved. Crash data were plotted in a geographic information system (MapInfo) for spatial analysis. Results: There were 23 deaths from 22 motorcycle crashes on public roads meeting RRRSS criteria. Of these, half were single vehicle crashes and half involved 2 or more vehicles. In contrast to general patterns for driver/rider age distribution in crashes, riders below 25 years of age were represented proportionally within the population. Riders in their thirties comprised 41% of fatalities, with a further 36% accounted for by riders in their fifties. 18 crashes occurred in the Far North Statistical Division (SD), with 2 crashes in both the Northern and North West SDs. Behavioural factors comprised the vast majority of contributing circumstances cited by police, with adverse environmental conditions noted in only 4 cases. Conclusions: Fatal motorcycle crashes were more likely to involve another vehicle and less likely to involve a young rider than non-fatal crashes recorded by the RRRSS. Rider behaviour contributed to the majority of crashes and should be a major focus of research, education and policy development, while other road users’ behaviour and awareness also remains important. With 68% of crashes occurring on major and secondary roads within a 130km radius of Cairns, efforts should focus on this geographic area.

Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in western Africa

Objective We aimed to predict sub-national spatial variation in numbers of people infected with Schistosoma haematobium, and associated uncertainties, in Burkina Faso, Mali and Niger, prior to implementation of national control programmes. Methods We used national field survey datasets covering a contiguous area 2,750 × 850 km, from 26,790 school-aged children (5–14 years) in 418 schools. Bayesian geostatistical models were used to predict prevalence of high and low intensity infections and associated 95% credible intervals (CrI). Numbers infected were determined by multiplying predicted prevalence by numbers of school-aged children in 1 km2 pixels covering the study area. Findings Numbers of school-aged children with low-intensity infections were: 433,268 in Burkina Faso, 872,328 in Mali and 580,286 in Niger. Numbers with high-intensity infections were: 416,009 in Burkina Faso, 511,845 in Mali and 254,150 in Niger. 95% CrIs (indicative of uncertainty) were wide; e.g. the mean number of boys aged 10–14 years infected in Mali was 140,200 (95% CrI 6200, 512,100). Conclusion National aggregate estimates for numbers infected mask important local variation, e.g. most S. haematobium infections in Niger occur in the Niger River valley. Prevalence of high-intensity infections was strongly clustered in foci in western and central Mali, north-eastern and northwestern Burkina Faso and the Niger River valley in Niger. Populations in these foci are likely to carry the bulk of the urinary schistosomiasis burden and should receive priority for schistosomiasis control. Uncertainties in predicted prevalence and numbers infected should be acknowledged and taken into consideration by control programme planners.

The effect of traffic lane widths on the safety of cyclists in urban areas

This literature review examines the relationship between traffic lane widths on the safety of road users. It focuses on the impacts of lane widths on motor vehicle behaviour and cyclists’ safety. The review commenced with a search of available databases. Peer reviewed articles and road authority reports were reviewed, as well as current engineering guidelines. Research shows that traffic lane width influences drivers’ perceived difficulty of the task, risk perception and possibly speed choices. Total roadway width, and the presence of onroad cycling facilities, influence cyclists’ positioning on the road. Lateral displacement between bicycles and vehicles is smallest when a marked bicycle facility is present. Reduced motor vehicle speeds can significantly improve the safety of vulnerable road users, particularly pedestrians and cyclists. It has been shown that if road lane widths on urban roads were reduced, through various mechanisms, it could result in a safety environment for all road users.

The role of personality in predicting hooning-related driving behaviour

‘Hooning’ constitutes a set of illegal and high-risk vehicle related activities typically performed by males aged 17-25, a group that is over-represented in road trauma statistics. This study used an online survey of 422 participants to test the efficacy of the Five Factor Model of Personality in predicting ‘loss of traction’ (LOT) hooning behaviour. Drivers who engaged in LOT behaviour scored significantly lower on the factor of Agreeableness than those who did not. Regression analyses indicated that the Five Factor Model of Personality was a significant predictor of LOT behaviour over and above sex and age, although Agreeableness was the only significant personality factor in the model. The findings may be used to better understand those drivers likely to engage in LOT behaviours. Road safety advertising and educational campaigns can target less socially agreeable drivers, and aim to encourage more agreeable attitudes to driving, particularly for younger male drivers.

The impact of red light cameras on safety in Arizona

Red light cameras (RLCs) have been used in a number of US cities to yield a demonstrable reduction in red light violations; however, evaluating their impact on safety (crashes) has been relatively more difficult. Accurately estimating the safety impacts of RLCs is challenging for several reasons. First, many safety related factors are uncontrolled and/or confounded during the periods of observation. Second, “spillover” effects caused by drivers reacting to non-RLC equipped intersections and approaches can make the selection of comparison sites difficult. Third, sites selected for RLC installation may not be selected randomly, and as a result may suffer from the regression to the mean bias. Finally, crash severity and resulting costs need to be considered in order to fully understand the safety impacts of RLCs. Recognizing these challenges, a study was conducted to estimate the safety impacts of RLCs on traffic crashes at signalized intersections in the cities of Phoenix and Scottsdale, Arizona. Twenty-four RLC equipped intersections in both cities are examined in detail and conclusions are drawn. Four different evaluation methodologies were employed to cope with the technical challenges described in this paper and to assess the sensitivity of results based on analytical assumptions. The evaluation results indicated that both Phoenix and Scottsdale are operating cost-effective installations of RLCs: however, the variability in RLC effectiveness within jurisdictions is larger in Phoenix. Consistent with findings in other regions, angle and left-turn crashes are reduced in general, while rear-end crashes tend to increase as a result of RLCs.

Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

The role of cultural beliefs in contributing to risky road use behaviour in Pakistan

Background Pakistan has the highest population rate of road fatalities in South Asia (25.3 fatalities per 100,000 people: Global Status Report on Road Safety, WHO 2009). Along with road environment and vehicle factors, human factors make a substantial contribution to traffic safety in Pakistan. Beliefs about road crash causation and prevention have been demonstrated to contribute to risky road use behaviour and resistance to preventive measures in a handful of other developing countries, but has not been explored in Pakistan. In particular, fatalism (whether based on religion, other cultural beliefs or experience) has been highlighted as a barrier to achieving changes in attitudes and behaviour. Aims The research reported here aimed (i) to explore perceptions of road crash causation among policy makers, police officers, professional drivers and car drivers in Pakistan; (ii) to identify how cultural and religious beliefs influence road use behaviour in Pakistan; and (iii) to understand how fatalistic beliefs may work as obstacles to road safety interventions. Methods In-depth interviews were conducted by the primary author (mostly in Urdu) in Lahore, Rawalpindi and Islamabad with 12 professional drivers (taxi, bus and truck), 4 car drivers, 6 police officers, 4 policy makers and 2 religious orators. All but two were Muslim, two were female, and they were drawn from a wide range of ages (24 to 60) and educational backgrounds. The interviews were taped and transcribed, then translated into English and analysed for themes related to the aims. Results Fatalism emerged as a pervasive belief utilised to justify risky road use behaviour and to resist messages about preventive measures. There was a strong religious underpinning to the statement of fatalistic beliefs (this reflects popular conceptions of Islam rather than scholarly interpretations), but also an overlap with superstitious beliefs which have longer-standing roots in Pakistani culture. These beliefs were not limited to people of poor educational background or position. A particular issue which was explored in more detail was the way in which these beliefs and their interpretation within Pakistani society contributed to poor police reporting of crashes. Discussion and conclusions The pervasive nature of fatalistic beliefs in Pakistan affects road user behaviour by supporting continued risk taking behaviour on the road, and by interfering with public health messages about behaviours which would reduce the risk of traffic crashes. The widespread influence of these beliefs on the ways that people respond to traffic crashes and the death of family members contribute to low crash reporting rates and to a system which is difficult to change. The promotion of an evidence-based approach to road user behaviour is recommended, along with improved professional education for police and policy makers.

Research initiatives to improve the visibility and hence safety of road workers at night-time

Research has demonstrated the benefits that clothing incorporating retroreflective markers can provide in significantly improving visibility and reducing accidents, especially at night. Adding biomotion markings to standard vests can enhance the night-time conspicuity of roadway workers by capitalizing on perceptual capabilities.

Bicycle safety for children and young people : an analysis of child deaths in Queensland

Bicycle riding can be a positive experience for children and young people that builds confidence, independence and promotes healthy recreation. However, these benefits are dependent upon safe bicycle riding practices. Between 1 January 2004 and 31 December 2011, 12 children and young people under the age of 18 years died in bicycle incidents in Queensland. An additional 1736 bicycle-related injuries requiring emergency department attendance are estimated to have occurred between 2008 and 2009 in Queensland for children and young people under the age of 18 years. Of the twelve bicycle-related deaths between 2004 and 2011 in Queensland, two children were aged between 5-9 years, 5 young people were 10-14 years of age and 5 young people were between 15-17 years. The two children aged 5-9 years were riding their bikes for recreation. Children aged 10-14 years were most likely to have been killed in an incident while riding to school in the morning, with teenagers aged 15-17 years most likely to be killed in incidents occurring after school and in the evening. Bicycle riders are vulnerable road users, particularly children and young people. This is due to several factors that can be grouped into: 1) developmental characteristics such as body size and proportions, perceptional and attentional issues, road safety awareness and risk taking behaviours, and 2) environmental factors such as supervision and shared road use with vehicles. This paper examines safety issues for children and young people who have died in bicycle-related incidents in Queensland, and outlines areas of focus for injury prevention practitioners.

Automated speed enforcement in Australia : recent examples of the influence of public opinion on program sustainability

In Australia, speeding remains a substantial contributor to road trauma. The National Road Safety Strategy (2011-2020) highlighted the need to harness community support for current and future speed management strategies. Australia is known for intensive speed camera programs which are both automated and manual, employing covert and overt methods. Recent developments in the area of automated speed enforcement in Australia help to illustrate the important link between community attitudes to speed enforcement and subsequent speed camera policy developments. A perceived lack of community confidence in camera programs prompted reviews in New South Wales and Victoria in 2011 by the jurisdictional Auditor-General. This paper explores automated speed camera enforcement in Australia with particular reference to the findings of these two reports as they relate to the level of public support for and community attitudes towards automated speed enforcement. It also provides comment on the evolving nature of automated speed enforcement according to previously identified controversies and dilemmas associated with speed camera programs.

Bayesian imputation of non-chosen attribute values in revealed preference surveys

Obtaining attribute values of non-chosen alternatives in a revealed preference context is challenging because non-chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non-chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non-chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non-chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non-chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones.