• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.87-94
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• 2017

Many industrial accidents have occurred continuously in the manufacturing industries, construction industries, and service industries of Korea. Fatal accidents have occurred most frequently in the construction industries of Korea. Especially, the trend analysis of the accident rate and fatal accident rate is very important in order to prevent industrial accidents in the construction industries systematically. This paper considers forecasting of the accident rate and fatal accident rate with static and dynamic time series analysis methods in the construction industries. Therefore, this paper describes the optimal accident rate and fatal accident rate by minimization of the sum of square errors (SSE) among regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, proposed analytic function model (PAFM), and kalman filtering model (KFM) with existing accident data in construction industries. In this paper, microsoft foundation class (MFC) soft of Visual Studio 2008 was used to predict the accident rate and fatal accident rate. Zero Accident Program developed in this paper is defined as the predicted accident rate and fatal accident rate, the zero accident target time, and the zero accident time based on the achievement probability calculated rationally and practically. The minimum value for minimizing SSE in the construction industries was found in 0.1666 and 1.4579 in the accident rate and fatal accident rate, respectively. Accordingly, RAM and ARIMA model are ideally applied in the accident rate and fatal accident rate, respectively. Finally, the trend analysis of this paper provides decisive information in order to prevent industrial accidents in construction industries very systematically.

• Journal of the Korean Society of Safety
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• v.25 no.4
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• pp.90-95
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• 2010

This study deals with the accident model of arterial link section in Cheongju. The objective is to develop the accident model of arterial link section using the logistic regression. In pursuing the above, the study uses the 258 accident data occurred at the 322 arterial link section. The main results are as follows. First, Nagellerke $R^2$ of developed accident model is analyzed to be 0.309 and t-values of variable that explains goodness of fit are evaluated to be significant. Second, the variables adopted in the model are AADT, the number of exit and entry. These variables are all analyzed to be statistically significant. Finally, the analysis of correct classification rate shows that the total accident of correct classification rate is analyzed to be 72.7% at the arterial link section.

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.47-52
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• 2010

Many industrial accidents have occurred over the years in the manufacturing and construction industries in Korea. However, as the service industry has increased continuously, the share of the accident rate in the service industry was 39.07% in 2009, while the manufacturing industry share was 33.73%. The service industry share overtook the manufacturing industry share for the first time. Therefore, this research considers prevention of industrial accidents in the service industry as well as manufacturing and construction industries. This paper describes a procedure and a method to estimate efficient accident rate forecasting and estimated zero accident time in the service industry in order to prevent industrial accidents in the transportation, storage, and telecommunication divisions. This paper proposes a model using an analytical function for the sake of very efficient accident rate forecasting. Accordingly, this paper has develops a program for accident rate forecasting, zero accident time estimating, and calculation of achievement probability through MFC (Microsoft Foundation Class) software Visual Studio 2008 in the transportation, storage, and telecommunication divisions. In results of this paper, ARIMA (Auto Regressive Integrating Moving Average) is regarded as a very efficient forecasting model for the transportation, storage, and telecommunication division. In testing this model, value minimizing the Sum of Square Errors (SSE) was calculated as 0.2532. Finally the results of this paper are sure to help establish easy accident rate forecasting and strategy or method of zero accident time in the service industry for prevention of industrial accidents.

• Journal of the Society of Disaster Information
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• v.13 no.4
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• pp.570-576
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• 2017

Trucks take up more portions than cars on highways. Due to this, road use relatively diminish and it serves locally as a threatening factor to nearby drivers. Baggage car accident has distinct characteristics so that it needs the application of different analysis opposed to ordinary accidents. Accident prediction model, one of accident analyses, is used to predict the numbers of accident in certain parts, establish traffic plans as well as accident prevention methods, and diagnose the danger of roads. Thus, this study aims to apply the accident rate of baggage car on highways and calculate the correction factor to be put in the accident prediction models. Accident data based on highway was collected and traffic amounts and accident documents between 2014 and 2016 were utilized. The author developed an accident prediction model based on numbers of annual accidents and set mean annual and daily traffic amounts. This study intends to identify the practical accident prediction model on highway and present an appropriate solution by comparing the prediction model in accords with the accident rate between baggage cars.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.4
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• pp.285-291
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• 2006

A traffic accident is occurred by unbalance of reciprocal action of driver, vehicle and road conditions. To prevent the traffic accident, rapid and perfect road improvement is needed. But most of road improvement plans have insufficient budget. So decision maker has to determine the priority to invest. A model in this study, analyzing the effect of road conditions to the traffic accident, helps to decide the priority in road improvement. This study considered five danger indices ; 1) traffic volume, 2) speed variance, 3) vehicle mixing rate, 4) curved line radius, and 5) difference between design speed and running speed. Danger rate composed by five indices can be a scale of priority of improvement. The model in this study didn't consider all of factors about traffic accident. But this study can propose the methodology for traffic safety policy. For deriving the model, this study used data from highways in Korea and United States. Therefore the model has to apply the highways only.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.177-183
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• 2011

Korea has performed strategies for the third industrial accident prevention in order to minimize industrial accident. However, the occupational fatality rate and industrial accident rate appears to be stagnated for 11 years. Therefore, this paper forecasts the occupational fatality rate and industrial accident rate for 10 years. Also, this paper applies regression method (RA), exponential smoothing method (ESM), double exponential smoothing method (DESM), autoregressive integrated moving average (ARIMA) model and proposed analytical function method (PAFM) for trend of industrial accident. Finally, this paper suggests fundamental strategies for industrial accident prevention by forecasting of industrial accident rate in the long term.

• Journal of the Korean Society of Safety
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• v.7 no.2
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• pp.5-13
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• 1992

If zero-accident movement is to be successful, the objective goal period should be surely obtainable, and much more in our country where frequency rate of injury are remarkably fluc-tuating. However In our country, as far as we know, no method to establish a reasonable zero-accident goal period is guaranteed. In thls paper, a new establishing-method of reasonable goal period for individual industry with considering recent accident trend is presented. A mathematical model for industrial accidents generation was analyzed, and a stochastic process model for the accident generation inteual was formulated. This model could tell the accident generation rate in future by understanding the accident tendency through the time-series analysis and search for the distribution of numbers of accidents and accident interval. On the basis of this, the forecasting method of goal achievement probability by the size and the establishment method of reasonable goal period were developed.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.75-85
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• 2018

PURPOSES : This study aimed to analyze traffic accidents at circular intersections, and discuss accident reduction strategies based on land use and vehicle type. METHODS : Traffic accident data from 2010 to 2014 were collected from the "traffic accident analysis system" (TAAS) data set of the Road Traffic Authority. To develop the accident rate model, a multiple linear regression model was used. Explanatory variables such as geometry and traffic volume were used to develop the models. RESULTS : The main results of the study are as follows. First, it was found that the null hypotheses that land use and vehicle type do not affect the accident rate should be rejected. Second, 16 accident rate models, which are statistically significant (with high $R^2$ values), were developed. Finally, the area of the central island, number of speed humps, entry lane width, circulatory roadway width, bus stops, and pedestrian crossings were analyzed to determine their effect on accidents according to the type of land use and vehicle. CONCLUSIONS : Through the developed accident rate models, it was revealed that the accident factors at circular intersections changed depending on land use and vehicle type. Thus, selecting the appropriate location of bus stops for trucks, widening entry lanes for cars, and installing splitter islands and optimal lighting for motorcycles were determined to be important for reducing the accident rate. Additionally, the evaluation showed that commercial and mixed land use had a weaker effect on accidents than residential land use.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.6-11
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• 2013

In this study, the effect of damping and elastic nature on the control performance of a safety budget-industrial accident rate model in Korea is examined first. The effectiveness of such dynamic model in establishing safety policies is shown with a simple proportional-integral(PI) feedback control mechanism. Control performance of the safety system model is explained in view of maximizing the effect of IAPF and minimizing the absolute amount of IAFP. Control performance is then evaluated and proved to be effective to prevent and reduce the industrial accidents. Implications in feedback control of a safety system model suggested to optimization of safety policies are also explored. Without proper restructuring of the safety system, it would not be possible to hit the target industrial accident rate. Even if the control objective is met, the amount of industrial accident prevention fund required to reduce the industrial accident rate from the current level to the target level would be far beyond the social consensus.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.1-5
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• 2007

We construct the procedure to predict safety accidents following Bayesian approach. We make a model that can utilize the data to predict other levels of accidents. An event tree model which is a frequently used graphical tool in describing accident initiation and escalation to more severe accident is transformed into an influence diagram model. Prior distributions for accident occurrence rate and probabilities to escalating to more severe accidents are assumed and likelihood of number of accidents in a given period of time is assessed. And then posterior distributions are obtained based on observed data. We also points out the advantages of the bayesian approach that estimates the whole distribution of accident rate over the classical point estimation.