Intrusion warning and assessment method for site safety enhancement

Intrusion (unauthorized stepping-into/staying-in a hazardous area), as a common type of near-miss, is the prime cause of the majority of incidents on construction sites including fall from heights, and striking against or being struck by moving objects. Accidents often occur because workers take shortcuts moving about the site without fully perceiving the potential dangers. A number of researches have been devoted to developing methods to prevent such behaviors mainly based on the theory of Behavior-Based Safety (BBS), which aims to cultivate safety behaviors among workers in accordance with safety regulations. In current BBS practice, trained observers and safety supervisors are responsible for safety behavior inspections following safety plans and operation regulations. The observation process is time-consuming and its effectiveness depends largely on the observer’s safety knowledge and experience, which often results in omissions or bias. This paper presents a reformed safety behavior modification approach by integrating a location-based technology with BBS. Firstly, a detailed background is provided, covering current intrusion problems on site, existing use of BBS for behavior improvement, difficulties in achieving widespread adoption and potential technologies for location tracking and in-time feedback. Then, a conceptual framework of positioning technology-enhanced BBS is developed, followed by details of the corresponding on-line supporting system, Real Time Location System (RTLS) and Virtual Construction System (VCS). The application of the system is then demonstrated and tested in a construction site in Hong Kong. Final comments are made concerning further research direction and prospects for wider adoption.

An incident database for improving metro safety: The case of shanghai

Large cities depend heavily on their metro systems to reduce traffic congestion, which is particularly the case with Shanghai, the largest and most developed city in China. For the purposes of enhancing the possibility in quantitative risk assessment and promoting the safety management level in Shanghai metro, an adaptable metro operation incident database (MOID) is therefore presented for containing details of all incidents that have occurred in metro operation. Taking compatibility and simplicity into consideration, Microsoft Access 2010 software is used for the comprehensive and thorough design of the MOID. Based on MOID, statistical characteristics of incident, such as types, causes, time, and severity, are discovered and 24 accident precursors are identified in Shanghai metro. The processes are demonstrated to show how the MOID can be used to identify trends in the incidents that have occurred and to anticipate and prevent future accidents. In order to promote the application of MOID, an organizational structure is proposed from the four aspects of supervision, research, implementation, and manufacturer. This research would be conducive to safety risk analysis in identifying relevant precursors in safety management and assessing safety level as a qualitative tool.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Using Big Data to manage safety-related risk in the upstream oil and gas industry: A research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Strategies for improving safety and health of ethnic minority construction workers

The construction industries of developed countries are faced with an aging workforce and a shortage of recruits. It is common for migrant workers/ethnic minorities (EMs) who are already part of the society to join the construction industry. With increasing involvement of EMs in the construction industry, effective strategies for improving their safety and health are urgently needed. The existing body of knowledge is mainly derived from research conducted in English-speaking countries with Western cultures. Research on safety of migrant/EM construction workers in multidialect Asian countries with Eastern cultures has been lacking. This study aimed to identify various strategies for improving the safety and health of EM construction workers from the Asian perspective. Twenty-two face-to-face semistructured interviews were performed with safety professionals in Hong Kong followed by two rounds of Delphi survey with 18 safety experts to verify the interview findings and rank the relative importance of the strategies. The study unveiled 14 strategies for improving the safety performance of EM workers. The three most important ones identified were: (1) to provide safety training in EM native languages; (2) that government and industry associations should play an active role in promoting health and safety awareness of EM workers, and; (3) to encourage EM workers to learn the local language. This study contributes to filling the research gap by evaluating the strategies for improving safety of migrant/EM construction workers in Asian countries with Eastern cultures in which English is not the first language. Research findings would assist occupational health and safety experts and relevant stakeholders in designing strategies for improving the safety and health of EM workers, which will ultimately improve overall safety performance of the construction industry.

Safety of Repair, Maintenance, Minor Alteration, and Addition (RMAA) Works: A New Focus of Construction Safety

"Safety of RMAA works is an almost uncharted topic of rising importance internationally. Small construction contractors are particularly dependant on RMAA work, especially during times of recession, and they undertake more risks on these jobs than large companies do. This book is based on unique international research and consultancy projects which detail, investigate, and suggest solutions to the specific challenges of safety in RMAA works, based on case studies. Starting with an overview of safety in the wider construction industries of developed countries, the first half of this book also provides a comprehensive summary of relevant rules, regulations, and the resulting safety performances. The systems in the UK, US and Hong Kong are described and contrasted, giving the reader an understanding of how different regulatory approaches have yielded a variety of results. From this solid introduction, specific problems observed in RMAA work are examined through case studies, with reference to the underlying cultural and demographic factors, and a variety of practical engineering and management solutions are explored. This important and practical international work is essential reading for postgraduate students of health and safety in construction, construction project management, or construction in developing countries, as well as policy-makers and construction project managers."--Publisher website

A Best Practice Process for Fleet Safety Training

This paper outlines a process for fleet safety training based on research and management development programmes undertaken at the University of Huddersfield in the UK (www.hud.ac.uk/sas/trans/transnews.htm) and CARRS-Q in Australia (www.carrsq.qut.edu.au/staff/Murray.jsp) over the past 10 years.