• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.59-60
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• 2018

The purpose of this study is to predict and classify the accident types based on the KOSHA (Korea Occupational Safety & Health Agency) and weather data. We also have an effort to suggest an important management method according to accident types by deriving feature importance. We designed two models based on accident data and weather data (model(a)) and only weather data (model(b)). As a result of random forest method, the model(b) showed a lack of accuracy in prediction. However, the model(a) presented more accurate prediction results than the model(b). Thus we presented safety management plan based on the results. In the future, this study will continue to carry out real time prediction to occurrence types to prevent safety accidents by supplementing the real time accident data and weather data.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.63-82
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• 1995

This paper deals with the forecasting model for traffic accident. Its objective is to develop the appropriate model to project the accident of Chung-Chong Region. Two types of models between motorization (M) and personal hazard (P) are tested : One is inverted-U (bell type) curve and the other is increasing (or decreasing) curve. The statiscal and sensitivity analyses show that exponential model (type III) and multiplicative model (type II) are well fit to the given cross-sectional and time-series accident data. The model projects that the fatality per 100, 000 persons of Chung-Chong region, when the motorization level (M) is 0.2, would be in the range between 18 and 77 persons. The paper concludes that the accident level is the function of motorization and the result of implementing the safety policy of a region.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.65-73
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• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.25-31
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• 2006

In this paper, a fatality model of car accident using data mining is proposed with the goal of reducing fatality of traffic accident. The analysis results with a proposed fatality model are utilized to improve a technology and environment for driving. For this, traffic accident data are collected, a data mining algorithm is applied to this data, and then, a fatality model of car accident is developed based on the analysis. The training data as well as test data are utilized to develop the fatality model. The important factors to cause fatality in traffic accidents can be investigated using the model. If these factors are taken into account in traffic policies and driving environment, it is expected that the fatality rate of traffic accident can be reduced hereafter.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.83-91
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• 2012

PURPOSES : This study deals with Rotary by Accident Occurrence Location. The purpose of this study is to develop the accident models of rotary by location. METHODS : In pursuing the above, this study gives particular attentions to developing the appropriate models using multiple linear, Poisson and negative binomial regression models and statistical analysis tools. RESULTS : First, four multiple linear regression models which are statistically significant(their $R^2$ values are 0.781, 0.300, 0.784 and 0.644 respectively) are developed, and four Poisson regression models which are statistically significant(their ${\rho}^2$ values are 0.407, 0.306, 0.378 and 0.366 respectively) are developed. Second, the test results of fitness using RMSE, %RMSE, MPB and MAD show that Poisson regression model in the case of circulatory roadway, pedestrian crossing and others and multiple linear regression model in the case of entry/exit sections are appropriate to the given data. Finally, the common variable that affects to the accident is adopted to be traffic volume. CONCLUSIONS : 8 models which are all statistically significant are developed, and the common and specific variables that are related to the models are derived.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.221-230
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• 2017

Objective: The purpose of this study is to draw the accident prevention model using the signal detection theory, and to implement accident prevention program, based on a health promotion and support activities in a shipbuilding company. Background: Workers' health management is perceived important from the human resource management perspective, as well as from the personal perspective. Method: This study developed an accident prevention model by analyzing the correlation between 704 workers' health examination variables, and reviewed the verification of the model through a follow-up survey on the control variables and status of hazards targeting 650 workers for four years from 2007 to 2010. Also, a health promotion program was implemented targeting a production division to improve alcohol habits, smoking, musculoskeletal pain complaints and hearing control indices, which are the control variables of the model. Results: As a result of four years' implementation, the following effects were obtained: the days away from work fell 87.5%, and accident rate dropped 71.5% in 2010, respectively, compared to 2006, before the activity was implemented. Conclusion: This study shows that the accident prevention activities based on workers' health promotion activities are effective to prevent industrial accidents and injuries. Application: The research findings will serve as a practical guideline for establishing preventive measures in the shipbuilding company.

• Journal of the Korean Society of Safety
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• v.33 no.4
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• pp.98-104
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• 2018

Macroscopic accident analyses have been conducted to incorporate transportation safety into long-term transportation planning. In macro-level accident prediction model, exposure variable(e.g. a settled population) have been used as fundamental explanatory variable under the concept that each trip will be subjected to a probable risk of accident. However, a settled population may be embedded error by exclusion of active population concept. The objective of this research study is to develop macro-level accident prediction model using floating population variable(concept of including a settled population and active population) collected from mobile phone data. The concept of accident prediction models is introduced utilizing exposure variable as explanatory variable in a generalized linear regression with assumption of a negative binomial error structure. The goodness of fit of model using floating population variable is compared with that of the each models using population and the number of household variables. Also, log transformation models are additionally developed to improve the goodness of fit. The results show that the log transformation model using floating population variable is useful for capturing the relationships between accident and exposure variable and generally perform better than the models using other existing exposure variables. The developed model using floating population variable can be used to guide transportation safety policy decision makers to allocate resources more efficiently for the regions(or zones) with higher risk and improve urban transportation safety in transportation planning step.

• Journal of the Korean Regional Science Association
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• v.11 no.1
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• pp.21-30
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• 1995

This paper deals with the forecasting models for traffic accident by region. Its objectives are to develop the appropriate model for projecting the accident and to analyze the regional characteristics of the accident model. The main results are as follow. First, the literature review, statistical tests and sensitivity analyses show that the joint model combined both PTM and Exponential functions is appropriate to project the traffic accidents by region. Second, the statistical analyses by region. Second, the statistical analyses on the regional accident models indicate that the levels of significance in terms of t-value, $R^2$ and F-value are very high. Finally, the comparative analyses among regions show that the regional differences on the accident patterns can be explained by the joint models and the accident indices (parameters, $P_{max}$, 1/b, $\eta$ etc.) of each region.

• The Journal of Sustainable Design and Educational Environment Research
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• v.12 no.2
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• pp.19-30
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• 2013

Low birthrate is causing a reduction in the number of students at kindergartens, elementary schools, middle schools and high schools nationwide and yet, school safety accidents are on a constant rise, which was reported to be 237 accidents a day on average in 2011. Such phenomenon is proving how the school safety policy is not doing what it was supposed to do. In order to decrease the school safety accidents, first, causes of the accidents should be analyzed and then, prevention measures should be designed. For that reason, the study looked into the present condition of the school safety accidents and safety accident theories and based on the results, "School Safety Accident Analysis Matrix Model" was proposed. With a matrix method of the accident types (17 of them) and hazard factors (9 of them) applied, the concerned model analyzed a total of 153 accident causes. In consideration of the results from the analysis, the study suggested that the education authority should open a safety organization and design a school safety policy that would systematically deal with safety education, prevention measures practice, accident investigation and analysis, and countermeasures practice as well.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.43-49
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• 2010

This study deals with the traffic accident of the Cheongju arterial link sections. The purpose of the study is to develop the traffic accident model. In pursuing the above, this study gives particular attentions to developing the ZAM(zero-altered model) model using the accident data of arterial roads devided by 322 small link sections. The main results analyzed by ZIP(zero inflated Poisson model) and ZINB(zero inflated negative binomial model) which are the methods of ZAM, are as follows. First, the evaluation of various developed models by the Vuong statistic and t statistic for overdispersion parameter ${\alpha}$ shows that ZINB is analyzed to be optimal among Poisson, NB, ZIP(zero-inflated Poisson) and ZINB regression models. Second, ZINB is evaluated to be statistically significant in view of t, ${\rho}$ and ${\rho}^2$ (0.63) values compared to other models. Finally, the accident factors of ZINB models are developed to be the traffic volume(ADT), number of entry/exit and length of median. The traffic volume(ADT) and the number of entry/exit are evaluated to be the '+' factors and the length of median to be '-' factor of the accident.