Safety Performance Model Research Articles

A Model Proposal for Occupational Health and Safety Performance Measurement in Geothermal Drilling Areas

The energy sources required for general development and maintenance cause environmental pollution due to the carbon emissions released into the atmosphere. For these reasons, countries have turned to renewable energy sources. Energy production methods also cause serious problems in terms of the health and safety of employees. This study aimed to create an occupational health and safety performance model in geothermal energy fields, which generate renewable energy sources, using multi-criteria decision-making methods. A two-stage model was created for OHS performance index measurement. In the first stage, a literature screening was performed, risk analysis criteria were examined, and performance measurement criteria were determined with geophysical engineers and OHS experts. Seven main criteria and forty-seven subcriteria were set. An analytical hierarchy process method (AHP) and a fuzzy analytical hierarchy process (F-AHP) using the main criteria and subcriteria were determined. In the second stage, exposure rates were obtained using the Promethee method in three geothermal wells. The risks in these three wells are listed according to their importance. A performance model was created. The Results section includes conclusions and suggestions. This study, by creating an OHS performance model, can be used by managers and OHS professionals working in geothermal energy production fields to solve problems.

Statistical Safety Performance Models considering Pavement and Roadway Characteristics

Transportation agencies build statistical models and predict the average crash frequency to identify hazardous road sections and make informed decisions to reduce crashes. In this paper, safety performance models (SPFs) were built and evaluated considering various pavement and roadway characteristics, including pavement friction, which is seldom available for analysis. Four count data models—Poisson model, negative binomial (NB) model, hurdle-NB model (HNB), and zero-inflated NB (ZINB) model—were built based on roadway characteristics and crash data provided by the Oklahoma Department of Transportation (ODOT). Pavement friction, roadway geometry, surface condition characteristics, and traffic exposure were considered the contributing factors to traffic crashes. Established models were compared in terms of the goodness-of-fit, zero inflation, and statistical significance of factors. The HNB model exhibited promising fitting performance with a manageable number of influencing variables. Coefficients in the HNB model suggest that adequate pavement friction and the presence of shoulders can significantly reduce the crash frequency and thus improve roadway safety performance. Potential issues of the statistical models, such as unobserved heterogeneity and multicollinearity, were also discussed. The relation between roadway infrastructure characteristics (including pavement friction) and roadway safety revealed in this study could assist in choosing the proper statistical model for better decision-making and selecting appropriate preventive treatments for improved roadway safety.

Factors affecting safety performance in the construction industry: an empirical study using structural equation modelling

The Saudi construction industry is among the largest in the region – and, for workers, among the most dangerous industries. The importance of this study is assisting to reduce hazards, sources of risk and perceptions of safety in the construction sector. Using a quantitative survey measure administered to a small (n = 276) sample of individuals, this study aimed to contribute to empirical understandings of safety performance in this unique context. A multivariate safety performance model was developed to ensure compatibility with the structure of the survey measure. The survey data revealed a strong consensus expressing negative views of every safety dimension and variable tested, with only tiny minorities selecting positively valenced responses. To test the descriptive power of the model as a whole, a structural equation modelling technique was used to assess the correspondence between the relationships constituting the model and their significance relative to empirical data.

Seasonal crash prediction model for urban signalized intersections: Wisconsin southeast region

Objectives Highly aggregated data is conventionally used in transportation safety omitting seasonal variations and leading to important loss of information. States in the northern region of the United States experience significant weather variations with snowfall and ice events. Crash occurrence is the highest during the winter compared to other seasons. Therefore, seasonal safety performance models would enable better safety analysis and decision-making. A new modeling approach is proposed which takes into account seasonal crash prediction. A case study is provided with crashes, operational, and weather data of urban signalized intersections from the southeast region in Wisconsin. Four seasons were considered: winter, spring, summer, and fall. Methodology The modeling approach consisted of the Multivariate Negative Multinomial to account for seasonal variations and severity classification. Functional forms of predictor variables were optimized. Measures of log-likelihood, Overdispersion, Cumulative Residual (CURE) plots, and Akaike Information Criterion (AIC) showed adequate model prediction accuracy. Results Crash estimates were the highest during the winter and the lowest during the spring seasons. Estimates remained below or near the annual average for the summer and fall seasons. Model performance was evaluated and results showed that seasonal model prediction and observed crash rate variations as percentage of annual estimates were similar. Conclusions Seasonal estimates have a significant contribution in safety analysis in regions where snow and ice conditions are regularly experienced. Identifying locations that experience significantly higher number of crashes during the winter can contribute to target snow and ice-related crashes and evaluate the effectiveness of deicing materials, equipment, and practices.

Safety performance and failure prediction model of cylindrical lithium-ion battery

In this paper, the safety performance model of cylindrical lithium-ion batteries, which is based on a second-order oscillation feature that is subjected to mechanical abuse is proposed via a discrete Fourier transformation of experimental data. Combined with the safety performance model and Crushable-Foam material model, the simulation results show that the average predictive error of the force-displacement and failure displacement is less than 8.8% and 4.0%, respectively. A battery fracture angle model is proposed, the fracture angle is only related to the load property, and the state-of-charge has minimal influence under the same load conditions. Furthermore, the failure prediction model of the soft short-circuit and the failure warning verification system are proposed. The experimental results show that the failure prediction model can warn the soft short-circuit in time with a certain safety margin. With further research, the safety performance model and the failure prediction model, which is based on mechanical penetration displacement, can be combined with other failure signals to provide more reliable information about battery safety. The failure warning device has the advantages of low cost and simple structure.

Personality and safety citizenship: the role of safety motivation and safety knowledge

Safety citizenship behaviors (SCB) have never been classified following the intended beneficiary of these behaviors. The first aim of this study was to examine Hofmann et al. (2003)'s SCB items in an attempt to identify two dimensions: SCB oriented towards individuals (SCB-I) and SCB oriented towards the organization (SCB-O). Further, by drawing on Christian et al. (2009)'s model of safety performance, we examined how distal (i.e. personality) and proximal (i.e. safety motivation and knowledge) person-related factors are associated with these behaviors. Structural equation modelling realized on a sample of 290 workers from a Belgian pharmaceutical company showed that the broader conscientiousness trait was related to both SCB-I and SCB-O, indirectly through safety motivation and knowledge, as would be predicted by Christian et al. In contrast, the altruism facet was directly related to SCB-I only. Results are discussed and practical implications considered.

A multilevel model of autonomous safety motivation and safety performance

A multilevel model of autonomous safety motivation and safety performance

Using horizontal curve speed reduction extracted from the naturalistic driving study to predict curve collision frequency

Many models have been developed to predict collision frequency and evaluate safety performance on horizontal curves. The approach used in data collection or some assumptions made in the analysis methodology might lead to inaccurate results. For example, manual data collection, equipment limitations, and field experiments involving monitoring driving behavior for a specific region for a short-term are potential sources of errors in data collection. This paper aims at overcoming some of these issues in developing models to evaluate safety performance of horizontal curves and predict the curve collision frequency. The developed models relate expected collision frequency on horizontal curves to the speed reduction from the approach tangent to the curve, which is commonly used as a major geometric design consistency measure. The methodology to achieve this objective included three tasks; data collection, evaluating and modeling the viable speed reduction parameters, and developing safety performance models to estimate collision frequency on horizontal curves. Individual drivers’ trips on 49 horizontal curves on rural two-lane highways in rolling and mountainous terrains in Washington State were extracted from the Naturalistic Driving Study (NDS) database. Models were developed to relate different speed reduction parameters to curve characteristics. These models were then applied to 1430 horizontal curves in Washington State to estimate the speed reduction parameters and relate them to collision frequency. Several safety performance models were developed which show that speed reduction, as a design consistency measure, is directly related to collision frequency on horizontal curves. Furthermore, the speed reduction parameters are more significant variables in predicting collision frequency than all curve geometric parameters.

Research on the Relationship of Safety Climate and Safety Performance in Airlines

For the sake of exploring influences of safety climate on safety performance, and improving the level of safety performance, the connotation indicators of safety climate and safety performance in Airlines were set up, and the hypothesis model of safety climate and safety performance was proposed. 200 workers in 10 Airlines in China were enquired by means of questionnaires and the structural equation model (SEM) was used to verify the hypothesis. Results showed that there is a positive correlation of safety climate with safety performance. The manager’s concern on safety is significantly positively related to safety behaviors and safety results, and the risk perception is significantly positively related to safety results. There is a positive correlation of safety attitude and safety perception with safety behaviors. And also the safety promotion is positively related to safety results. In safety management, the Airlines can improve their safety climate, especially manager’s concern on safety and risk perception of employees, to achieve high safety performance.

Development of a safety performance index assessment tool by using a fuzzy structural equation model for construction sites

Abstract The main goal of this study is to propose a safety performance index assessment tool to improve the construction safety. Formulation of the safety performance index of construction sites is achieved upon a validated multidimensional safety performance model. The contribution of this study could be summarized as incorporation of fuzzy set theory into structural equation modeling to develop a safety performance index assessment software tool. Case studies were conducted at 11 international construction sites and the results of their site safety performance indices were benchmarked. A short (simple) safety performance model was developed as an alternative to the full model (proposed model) to assess safety performance of construction sites. Results showed that short model predicts the safety performance with an acceptable accuracy and requires less time to complete. Finally, a safety performance index assessment software tool for construction sites was proposed by developing a site safety performance (SSP) application for mobile devices based on the validated multidimensional safety performance model. The paper attempts to numerically validate the influencing factors of construction safety with the help of a mobile device application. The paper also develops a mobile application tool to measure safety performance at any construction site.

Geographically weighted negative binomial regression applied to zonal level safety performance models

Generalized Linear Models (GLM) with negative binomial distribution for errors, have been widely used to estimate safety at the level of transportation planning. The limited ability of this technique to take spatial effects into account can be overcome through the use of local models from spatial regression techniques, such as Geographically Weighted Poisson Regression (GWPR). Although GWPR is a system that deals with spatial dependency and heterogeneity and has already been used in some road safety studies at the planning level, it fails to account for the possible overdispersion that can be found in the observations on road-traffic crashes. Two approaches were adopted for the Geographically Weighted Negative Binomial Regression (GWNBR) model to allow discrete data to be modeled in a non-stationary form and to take note of the overdispersion of the data: the first examines the constant overdispersion for all the traffic zones and the second includes the variable for each spatial unit. This research conducts a comparative analysis between non-spatial global crash prediction models and spatial local GWPR and GWNBR at the level of traffic zones in Fortaleza/Brazil. A geographic database of 126 traffic zones was compiled from the available data on exposure, network characteristics, socioeconomic factors and land use. The models were calibrated by using the frequency of injury crashes as a dependent variable and the results showed that GWPR and GWNBR achieved a better performance than GLM for the average residuals and likelihood as well as reducing the spatial autocorrelation of the residuals, and the GWNBR model was more able to capture the spatial heterogeneity of the crash frequency.

Identifying factors affecting the safety of mid-block bicycle lanes considering mixed 2-wheeled traffic flow

ABSTRACTObjective: Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs).Methods: Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes.Results: The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%.Conclusions: The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The safety performance model can help better understand the causes of crash occurrences in mid-block bike lanes.

Modeling the Relationship between Safety Climate and Safety Performance in a Developing Construction Industry: A Cross-Cultural Validation Study.

This study attempts to validate a safety performance (SP) measurement model in the cross-cultural setting of a developing country. In addition, it highlights the variations in investigating the relationship between safety climate (SC) factors and SP indicators. The data were collected from forty under-construction multi-storey building projects in Pakistan. Based on the results of exploratory factor analysis, a SP measurement model was hypothesized. It was tested and validated by conducting confirmatory factor analysis on calibration and validation sub-samples respectively. The study confirmed the significant positive impact of SC on safety compliance and safety participation, and negative impact on number of self-reported accidents/injuries. However, number of near-misses could not be retained in the final SP model because it attained a lower standardized path coefficient value. Moreover, instead of safety participation, safety compliance established a stronger impact on SP. The study uncovered safety enforcement and promotion as a novel SC factor, whereas safety rules and work practices was identified as the most neglected factor. The study contributed to the body of knowledge by unveiling the deviations in existing dimensions of SC and SP. The refined model is expected to concisely measure the SP in the Pakistani construction industry, however, caution must be exercised while generalizing the study results to other developing countries.

Road safety performance measures and AADT uncertainty from short-term counts

ObjectiveThe objective of this paper is to enable better risk analysis of road safety performance measures by creating the first knowledge base on uncertainty surrounding annual average daily traffic (AADT) estimates when the estimates are derived by expanding short-term counts with the individual permanent counter method. BackgroundMany road safety performance measures and performance models use AADT as an input. While there is an awareness that the input suffers from uncertainty, the uncertainty is not well known or accounted for. MethodThe paper samples data from a set of 69 permanent automatic traffic recorders in Manitoba, Canada, to simulate almost 2 million short-term counts over a five year period. These short-term counts are expanded to AADT estimates by transferring temporal information from a directly linked nearby permanent count control station, and the resulting AADT values are compared to a known reference AADT to compute errors. The impacts of five factors on AADT error are considered: length of short-term count, number of short-term counts, use of weekday versus weekend counts, distance from a count to its expansion control station, and the AADT at the count site. ResultsThe mean absolute transfer error for expanded AADT estimates is 6.7%, and this value varied by traffic pattern group from 5% to 10.5%. Reference percentiles of the error distribution show that almost all errors are between −20% and +30%. Error decreases substantially by using a 48-h count instead of a 24-h count, and only slightly by using two counts instead of one. Weekday counts are superior to weekend counts, especially if the count is only 24h. Mean absolute transfer error increases with distance to control station (elasticity 0.121, p=0.001), and increases with AADT (elasticity 0.857, p<0.001). ImplicationsThese results can support evidence-based risk analysis of road safety performance measures that use AADT as inputs. Analytical frameworks for such analysis exist but are infrequently used in road safety because the evidence base on AADT uncertainty is not well developed.

"A Moderated Mediation Model of Safety Knowledge, Safety Attitude, and Safety Performance"

The thousands of deaths and disabilities due to workplace accidents and injuries in the United States each year make occupational safety a significant issue. Occupational safety research has contri...

지능형 영상분석 시스템이 작업자 안전의식 및 행동에 미치는 영향

Abstract The study examined the relationship between workers’safety aw areness, safety performance and the components of the intelligent image analysis system in accordance with preventing the workers from safety hazard in dangerous working area. Based on the safety pe rformance model, we include safety knowledge, safety motivation, safety compliance and safety part icipation, and we also define three additional factors of the intelligent image analysis system suc h as functional feature, penalty and incentive by using factor analysis. SEM(Structural Equation Mod eling) analyses on the data from the total of 73 workers showed that functional feature of intellige nt analysis system and incentive were positively related to safety knowledge and safety motivation. A nd mediation effects of the relationship were verified to safety compliance and safety participation thr ough safety knowledge as well.Keywords : Safety Performance, Safety Knowledge, Safety Motivat ion, Safety Compliance, Safety Participant, Intelligent Image Analysis System

Safety performance models for urban intersections in Brazil

This paper presents a modeling effort for developing safety performance models (SPM) for urban intersections for three major Brazilian cities. The proposed methodology for calibrating SPM has been divided into the following steps: defining the safety study objective, choosing predictive variables and sample size, data acquisition, defining model expression and model parameters and model evaluation. Among the predictive variables explored in the calibration phase were exposure variables (AADT), number of lanes, number of approaches and central median status. SPMs were obtained for three cities: Fortaleza, Belo Horizonte and Brasília. The SPM developed for signalized intersections in Fortaleza and Belo Horizonte had the same structure and the most significant independent variables, which were AADT entering the intersection and number of lanes, and in addition, the coefficient of the best models were in the same range of values. For Brasília, because of the sample size, the signalized and unsignalized intersections were grouped, and the AADT was split in minor and major approaches, which were the most significant variables. This paper also evaluated SPM transferability to other jurisdiction. The SPM for signalized intersections from Fortaleza and Belo Horizonte have been recalibrated (in terms of the Cx) to the city of Porto Alegre. The models were adjusted following the Highway Safety Manual (HSM) calibration procedure and yielded Cx of 0.65 and 2.06 for Fortaleza and Belo Horizonte SPM respectively. This paper showed the experience and future challenges toward the initiatives on development of SPMs in Brazil, that can serve as a guide for other countries that are in the same stage in this subject.

Research on Evaluation Model of Aviation Ordnance Safety Performance

Security is the main direction of ammunition for future development. Depending on the security level that ammunition relative to its life process may suffer major environmental stimuli factors, raising ammunition’s safety criterion, introducing safety parameters, establishing a theoretical model of ammunition safety performance evaluation. In the model, based on the value of the safety of ammunition, we divides the security level of ammunition. Based on this evaluation model to calculate the conventional bomb safety performance of the changing Mk-82’s insensitivity. We analyzed the influence of unexploded ordnance (UXO) on the overall safety performance of ammunition from the failure of the design. The results show that the end of unexploded failure design can significantly improve the safety level of ammunition. This model better reflects the inherent safety performance of ammunition, can provide theoretical guidance for the safety design of ammunition and safety performance evaluation.

Scene‐based pedestrian safety performance model in mixed traffic situation

Compared to vehicle-only collisions, traffic collisions with pedestrians are studied less because of insufficient data. However, with the development of image processing technology, a growing number of road user behavioural analyses have been conducted using video data. This study tries to extract road users' movements from video data in order to analyse the conflict between pedestrian and vehicle and to evaluate pedestrian safety performance during conflicts. The time difference to collision (TDTC) parameter is used to fit the safety analysis on pedestrian-involved conflicts. Scene-based analysis, which evaluates the safety performance of traffic intersections and segments where several pedestrian-vehicle conflicts may happen together, is conducted using 91 groups of scene data. The parameters most related to pedestrian safety are located using a sensitivity test, a quantitative definition of pedestrian-vehicle conflict is then defined, and a scene-based pedestrian safety performance evaluation model is built. The model can correctly detect nearly 94.4% of possibly dangerous traffic scenes. Other kinds of mixed traffic scenes can also be studied based on this research.

Study of Business Safety Performance by Structural Equations Model

Internal safety performance which is increasing in recent years is topic of many researches. However, researches about application of Structural Equations Model (SEM) are rarely related to arrangement of systematic safety performance model. This research is aimed to evaluate safety performance by means of private food and chemicals enterprises in Taiwan and to provide strategy and development by safety performance. So, it is possible to achieve the best model for safety performance. AMOS 17.0 was applied for construction of competitive models of SEM (study of time structure 17.0).