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The number of deaths due to road accident is increasing day by day and has become an alarming global problem over the decades. India, with her rising motorization is no stranger to this global catastrophe. In this paper two relatively simple yet powerful and versatile techniques for forecasting time series data, autoregressive integrated moving average method (ARIMA) and exponential smoothing method are used to forecast the number of deaths due to road accidents in India from the year 2022-- 2031. The results based on the two methods are compared and it is found that they are in sync with each other and pre-existing literature. Furthermore, this is a unique attempt to use two time series analysis techniques on the same data and carry out a comparative analysis. The data was collected from the annual report of Ministry of Road Transport and Highways, India (2020) and Accidental Deaths & Suicides in India (ADSI) Report of National Crime Record Bureau (2021). After examining all the probable models, it is observed that ARIMA (2, 2, 2) model and exponential smoothing (M, A, N) model are suitable for the given data. Amongst the two, ARIMA (2, 2, 2) model has a lower AIC and BIC value. Thus, this comes out to be the best model as per our model selection criterion. Further, the study also reveals an upward trend of number of road accidental deaths for the upcoming 10 years in India. [ABSTRACT FROM AUTHOR]

This study focuses on the safety part of the passing manoeuvre. Passing is considered as one of the most complex, unavoidable and challenging manoeuvres on two lane roads. A binary logistic regression model was developed to determine the probability of passing or aborting based on field data. The result shows that the probability of passing is affected by the factors such as speed of passing vehicle, speed of overtaken vehicle, speed of opposing vehicle, clearance time, and the total passing time. Risk assessment is an important aspect which should be addressed while assessing the passing operations. In the present study, a risk chart was developed based on clearance time and vehicle interaction. An overall risk table was developed for all possible combinations of risk. The study revealed that the selected road stretch along NH-66 in Kerala, India is more susceptible to passing crashes due to insufficient clearance time. This paper brings out a rational methodology for calculating a safety measure in terms of risk index factor which could be used in simulation softwares for adequate passing sight distance operational analysis. [ABSTRACT FROM AUTHOR]

This paper presents a unique hierarchical structure on various occupational health hazards including physical, chemical, biological, ergonomic and psychosocial hazards, and associated adverse consequences in relation to an underground coal mine. The study proposes a systematic health hazard risk assessment methodology for estimating extent of hazard risk using three important measuring parameters: consequence of exposure, period of exposure and probability of exposure. An improved decision making method using fuzzy set theory has been attempted herein for converting linguistic data into numeric risk ratings. The concept of ‘centre of area’ method for generalized triangular fuzzy numbers has been explored to quantify the ‘degree of hazard risk’ in terms of crisp ratings. Finally, a logical framework for categorizing health hazards into different risk levels has been constructed on the basis of distinguished ranges of evaluated risk ratings (crisp). Subsequently, an action requirement plan has been suggested, which could provide guideline to the managers for successfully managing health hazard risks in the context of underground coal mining exercise. [ABSTRACT FROM PUBLISHER]

Considering the high burden of injuries, the Health Authority - Abu Dhabi developed a draft electronic and paper-based injury and poisoning notification system (IPNS) to generate better data on the nature and severity of injuries. The pilot testing and evaluation of IPNS was conducted with the specific objectives to (1) identify the characteristics of injury cases, (2) explore potential risk factors, (3) illustrate the nature and type of data, and (4) the working mechanism of data collection. Data were collected from selected hospitals on patient demographics, injury information and clinical assessment. Descriptive, bivariate and multivariate analyses were conducted. Of 4226 injury cases, nearly three-fourths were male, majority were non-UAE nationals, and the mean age was 21.9. Multivariate findings suggested that compared to UAE nationals, non-UAE nationals were 27% more likely to experience fatal, severe or moderate injuries (p= 0.01). Individuals with health insurance were 31% less likely to suffer a fatal, severe or moderate injury compared to those having no health insurance (p< 0.001). This is the first systematically standardised collection of injury data across three facilities in Abu Dhabi, and provides initial information on characteristics and injury risk factors that will help identify the need for evidence-based intervention for injury prevention and control. [ABSTRACT FROM PUBLISHER]

This paper presents the analysis of large mining machinery related accidents in Indian opencast coal mines. The trends of coal production, share of mining methods in production, machinery deployment in open cast mines, size and population of machinery, accidents due to machinery, types and causes of accidents have been analysed from the year 1995 to 2008. The scrutiny of accidents during this period reveals that most of the responsible factors are machine reversal, haul road design, human fault, operator's fault, machine fault, visibility and dump design. Considering the types of machines, namely, dumpers, excavators, dozers and loaders together the maximum number of fatal accidents has been caused by operator's faults and human faults jointly during the period from 1995 to 2008. The novel finding of this analysis is that large machines with state-of-the-art safety system did not reduce the fatal accidents in Indian opencast coal mines. [ABSTRACT FROM AUTHOR]