• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.354-362
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• 2000

Increasing amount of road tragic in 90's has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving conditions based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we apply several data fusion, ensemble and clustering algorithms in an effort to increase the accuracy of individual classifiers for the accident severity. An empirical study results indicated that clustering works best for road traffic accident classification in Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.20-29
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• 2022

This study intends to present a traffic node-based and link-based accident prediction models using XGBoost which is very excellent in performance among machine learning models, and to develop those models with sustainability and scalability. Also, we intend to present those models which predict the number of annual traffic accidents based on road types, weather conditions, and traffic information using XGBoost. To this end, data sets were constructed by collecting and preprocessing traffic accident information, road information, weather information, and traffic information. The SHAP method was used to identify the variables affecting the number of traffic accidents. The five main variables of the traffic node-based accident prediction model were snow cover, precipitation, the number of entering lanes and connected links, and slow speed. Otherwise, those of the traffic link-based accident prediction model were snow cover, precipitation, the number of lanes, road length, and slow speed. As the evaluation results of those models, the RMSE values of those models were each 0.2035 and 0.2107. In this study, only data from Sejong City were used to our models, but ours can be applied to all regions where traffic nodes and links are constructed. Therefore, our prediction models can be extended to a wider range.

• 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.

• Journal of the Korean Society of Safety
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• v.32 no.4
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• pp.107-113
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• 2017

This paper deals with the traffic factors related to the collisions of circular intersections. The purpose of this study is to develop traffic accident models by type of collision based on land use. In pursuing the above, the traffic accident data from 2010 to 2014 were collected from the "Traffic Accident Analysis System (TAAS)" data set of the Road Traffic Authority. A multiple regression model was utilized in this study to develop the traffic accident models by type of collision. 17 explanatory variables such as geometry and traffic volume factors were used. The main results are as follows. First, the null hypothesis that the type of land use does not affect the number of accidents by type of collision is rejected. Second, 10 accident models by type of collision based on land use are developed, which are all statistically significant. Finally, the ADT, inscribed circle diameter, bicycle lane, area of central island, number of speed hump, circulatory roadway width, splitter island, area of circulatory roadway, mean number of entry lane and mean width of entry lane are analyzed to see how they affect accident by type of accident based on land use.

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.123-129
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• 2017

This study deals with the traffic accident of truck at circular intersection. The purpose of this study is to develop the truck accident models based on type of accident and conflict. In pursuing the above, the study gives particular attentions to selecting the appropriate models among Poisson and Negative binomial models using statistical program LIMDEP 8.0. The traffic accident data from 2007 to 2014 are collected from TAAS data set of Road Traffic Authority. Such the dependent variable as number of truck accidents and the 24 independent variables as geometry, traffic volume and others are used. The main results are as follows. First, 5 Poisson models (${\rho}^2$ of 0.164~0.351) which are all statistically significant are selected. Second, the common variable based on type of accident and conflict is analyzed to be truck apron width. The specific variables are, however, evaluated to splitter island, area of splitter island, speed limit sign, truck apron, number approach road, circular intersection sign, speed hump and traffic volume. Finally, widening the truck apron width and improving the above specific variables are analyzed to be important for truck accident reduction at circular intersections.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.120-126
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• 2011

Under the current law or system, the range of traffic accident on the crosswalk does not reflect the characteristics of traffic accident and the pedestrian's walking pattern. Thus, this study conducted a video recording survey on the 250 spots which are high to traffic accident rate of pedestrian-vehicle to reset the range of traffic accident on or near the crosswalk considering the characteristics of traffic accident and the pedestrian's walking pattern. Based on the collected data through a video recording survey, this study analyzed the pattern of pedestrians and extracted the variables influenced in the pedestrian's walking pattern. After conducting the regression analysis, this study made the model of measuring the range of traffic accident on the crosswalk. Through all processes these, this study reset the range of traffic accident on the crosswalk which could minimize the disadvantages of pedestrian when they have an accident on the crosswalk and ensure the right of way of pedestrian.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1003-1010
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• 2006

This study developed a traffic accident information management system based on WebGIS that can process a lot of data for giving effectively diagnosis of traffic accidents in serious damage circumstances by traffic accident. Also, this study presents a way to compose and to convey traffic accident information. In addition, non-spatial attributes as well as spatial attributes about traffic accidents information be integrated and managed by the system. To provide Web service, we developed modules that can supply visually spatial information and traffic accidents data through ASP, Javascript, ArcIMS based on Web and constructed a server. And constructed system include a function that offer the now situation of traffic accident in real time, which supply the statistical data of traffic accident through Web as soon as user entry data in comparison with previous way that preparatory period until traffic accidents data is supplied to peoples had been long. Traffic accidents are analyzed with only nonspatial attribute by simply collecting in the past. However, system constructed by this study offer new function that can grasp visually accident spot circumstance and use detailed content and accurate location data as well as statistical data of traffic accidents. Also, it offer interface that can connect directly with accident charge policeman.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.91-98
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• 2011

We develop a model to predict traffic accidents in Korea. In contrast to the classical approach that mainly uses regression analysis, Bayesian approach is adopted. A dependent model that incorporates the data from different kinds of accidents is introduced. The rate of severe accident can be updated even with no data of the same kind. The data of minor accident that can be obtained frequently is efficiently used to predict the severe accident.