• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.119-126
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• 2018

This study intended to exploratively testify human error causing factors for railway traffic controller, using AMOS structural equation model. Through literature survey, fatigue and stress as exogenous variable, errors in information process such as cognitive, memory, storage, and execution error as endogenous variable, and accident and incident(near-miss) as dependent variable were set up. Results based on AMOS using 201 railway traffic controllers' questionnaire showed that a clear causality loop like as 'stress ${\rightarrow}$ memory error ${\rightarrow}$ storage error ${\rightarrow}$ incident(near-miss) ${\rightarrow}$ accident' is formed. This result suggests that for the purpose of mitigation of traffic controller's accident, it is so necessary to reduce memory and execution error in the information processing process based on the effective management of stress, as the precedent of them.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.427-441
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• 2021

Purpose: This study proposes a method for developing a model that predicts the probability of traffic accidents in advance to prevent the most frequent traffic accidents in the military. Method: For this purpose, CRISP-DM (Cross Industry Standard Process for Data Mining) was applied in this study. The CRISP-DM process consists of 6 stages, and each stage is not unidirectional like the Waterfall Model, but improves the level of completeness through feedback between stages. Results: As a result of modeling the same data set as the previously constructed accident investigation data for the entire group, when the classification criterion was 0.5, Significant results were derived from the accuracy, specificity, sensitivity, and AUC of the model for predicting traffic accidents. Conclusion: In the process of designing the prediction model, it was confirmed that it was difficult to obtain a meaningful prediction value due to the lack of data. The methodology for designing a predictive model using the data set was proposed by reorganizing and expanding a data set capable of rational inference to solve the data shortage.

• Journal of Auto-vehicle Safety Association
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• v.11 no.1
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• pp.30-35
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• 2019

KIDAS (Korean In-Depth Accident Study) is a data structure of accident investigation type, vehicle breakage and human injury database. A consortium of research institutes, universities, and medical institutions has been established and operated. KIDAS has the strongest difference from the TAAS (Traffic Accident Analysis System), which is the data of the National Police Agency, that it can grasp the injury information of passengers. In this study, the mean age and weight of the most frequent accident types in the KIDAS accident statistics were calculated to determine the degree of injury according to gender. Through the MADYMO analysis, it is aimed to grasp the difference of dummy injury using commercial dummy models and scaling models are currently used.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.230-235
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• 2003

Accident analysis is special concern to researchers in traffic safety. Accident analysis in product safety, however, is not. The needs of product safety management alter it in the world by all manufacturers. The purpose of this study is to propose a theoretical principles for product safety management through the accident cost analyses. The accident cost is a important factor to prevent product accident and to treat some claims of customers. It is sure that this principles can help all making decisions of manufactures with expected accident cost per a product accident and with total expected accident cost.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.201-213
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• 2018

In recent years, the number of traffic accidents caused by car accidents has been decreasing steadily due to traffic accident prevention activities in Korea. However, the number of accidents in Seoul is higher than that of other regions. Various studies have been conducted to prevent traffic accidents, which are human disasters. In particular, previous studies have performed the spatial analysis of traffic accidents by counting the number of traffic accidents by administrative districts or by estimating the density through kernel density method in order to identify the traffic accident cluster areas. However, since traffic accidents take place along the road, it would be more meaningful to investigate them concentrated on the road network. In this study, traffic accidents were assigned to the nearest road network in two ways and analyzed by hotspot analysis using Getis-Ord Gi* statistics. One of them was investigated with a fixed road link of 10m unit, and the other by computing the average traffic accidents per unit length per road section. As a result by the first method, it was possible to identify the specific road sections where traffic accidents are concentrated. On the other hand, the results by the second method showed that the traffic accident concentrated areas are extensible depending on the characteristic of the road links. The methods proposed here provide different approaches for visualizing the traffic accidents and thus, make it possible to identify those sections clearly that need improvement as for the traffic environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.2
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• pp.1-11
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• 1984

This aims of this study is to analyse the correlationship between traffic accident s and traffic characteristic variables in at-grade intersections of urban area, to build up an accident forecasting model and to propose an evaluation method of hazardous at-grade intersections. The accident forecasting model is formulated by the use of residual indexes that is selected by principal component analysis and its statistical significance is tested by step-wise regression analysis. Effective countermeasures for safety can be established on the basis of identifying high accident intersections, because the validity of this model was examined and found to coincide with real world situations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1297-1308
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• 2015

In Korea, the local traffic safety master plan has been established and implemented according to the Traffic Safety Act. Each local government is required to establish a customized traffic safety policy and share roles for improvement of traffic safety and this means that local governments lead and promote effective local traffic safety policies fit for local circumstances in substance. For implementing efficient traffic safety policies, which accord with many-sided characteristics of local governments, the prediction of community-based traffic accidents, which considers local characteristics and the analysis of accident influence factors must be preceded, but there is a shortage of research on this. Most of existing studies on the community-based traffic accident prediction used social and economic variables related to accident exposure environments in countries or cities due to the limit of collected data. For this reason, there was a limit in applying the developed models to the actual reduction of traffic accidents. Thus, this study developed a local traffic accident prediction model, based on smaller regional units, administrative districts, which were not omitted in existing studies and suggested a method to reflect traffic safety facility and policy variables that traffic safety policy makers can control, in addition to social and economic variables related to accident exposure environments, in the model and apply them to the development of local traffic safety policies. The model development result showed that in terms of accident exposure environments, road extension, gross floor area of buildings, the ratio of bus lane installation and the number of crossroads and crosswalks had a positive relation with accidents and the ratio of crosswalk sign installation, the number of speed bumps and the results of clampdown by police force had a negative relation with accidents.

• International Journal of Highway Engineering
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• v.16 no.6
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• pp.149-158
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• 2014

PURPOSES : The bridge section of the expressway has a worse driving environment than the general section. However, traffic safety countermeasures are focused only on the bridge section. Traffic safety countermeasures on the section before entry to the bridge and the section after exit from the bridge are applied only when the bridge has a long-span section. Accordingly, this study will verify the necessity of extending the application of traffic safety countermeasures to areas that are affected by the bridge. METHODS : This study determines the areas that are affected by the bridge as well as the areas that are affected by locations with frequent traffic accidents and suggests the risk factors by affected areas through canonical discriminant analysis. For the analysis, traffic accident data for 3 years, which occurred on bridge sections in six major expressway lines, were used. RESULTS : The numbers of traffic accidents were 469 before the bridge, 281 on the bridge, and 468 after the bridge. The variables that have impact on the seriousness of accidents are as follows: speeding, excess manipulation of the steering wheel, and failure to secure safety distance for accidents that occurred before the bridge section; speeding, excess manipulation of the steering wheel, and dozing off for accidents that occurred on the bridge; and speeding and failure to secure safety distance for accidents that occurred after the bridge section. CONCLUSIONS : Areas affected by the bridge show higher accident rates than the bridge section; therefore, imposing traffic safety countermeasures on the integrated section of the bridge and the affected areas is required. It is believed that the results suggested in this study could be effectively used in the prevention of traffic accidents by imposing custom-made safety countermeasures for each section.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.107-112
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• 2013

Base on insurance vehicle collision and bodily injury claim reports, 23,655 cases of vehicle to vehicle accidents occurred in Korea 2010 are investigated in order to understand vehicle damage severities, repair costs and occupant injury types. The results of our statistical analysis reveal that minor damages with small dent or scratches on vehicle body panels which is assumed to imply during very low speed crashes are major portion of accident severities types. The most vulnerable body regions due to the real-world accident are neck. The 86.3% of total injured driver in minor rear damaged vehicles has reported neck pains and they are followed by whole bodies and head but with much lower occurrence rates.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.123-135
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• 2007

The objective of this study is to analyze the relationship between traffic accidents occurring at trumpet interchange ramps according to accident type as well as the relevant factors that led to the traffic accidents, such as geometric design elements and traffic volumes. In the process of analysis of the distribution of traffic accidents, negative binomial distribution was selected as the most appropriate model. Negative binomial regression models were developed for total trumpet interchange ramps, direct ramps, loop ramps and semi-direct ramps based on the negative binomial distribution. Based upon several statistical diagnostics of the difference between observed accidents and predicted accidents with four previously developed models, the fit proved to be reasonable. Understanding of statistically significant variables in the developed model will enable designers to increase efficiency in terms of road operations and the development of traffic accident prevention policies in accordance with road design features.