• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.661-668
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• 2015

Them traffic accidents have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. The carelessness of drivers, many road weather factors have a great influence on the traffic accidents. Especially, the number of traffic accident is governed by precipitation, visibility, humidity, cloud amounts and temperature. The purpose of this paper is to analyse the effect of road weather factors on traffic accident. We use the data of traffic accident, AWS weather factors (precipitation, existence of rainfall, temperature, wind speed), time zone and day of the week in 2013. We did statistical analysis using logistic regression analysis and decision tree analysis. These prediction models may be used to predict the traffic accident according to the weather condition.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.135-148
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• 2007

Understanding the relation between characteristics of an accident and its duration is crucial for the efficient response of accidents and the reduction of total delay caused by accidents. Thus the objective of this study is to model accident duration using an AFT metric model. Although the log-logistic and log-normal AFT models were selected based on the previous studies and statistical theory, the log-logistic model was better fitted. Since the AFT model is commonly used for the purpose of prediction, the estimated model can be also used for the prediction of duration on freeways as soon as the base accident information is reported. Therefore, the predicted information will be directly useful to make some decisions regarding the resources needed to clear accident and dispatch crews as well as will lead to less traffic congestion and much saving the injured.

• Journal of the Korean Society of Safety
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• v.26 no.6
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• pp.130-136
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• 2011

Since out of a lot of traffic problems traffic accidents cause damage to life and properties of people, it stands out as one of traffic problems which needs improvement, and the loss due to traffic accident negatively affects not only the parties to the accident but also the national economy. Thus, continual concern of the government toward traffic safety is getting bigger and lately each local government is preparing a basic plan for traffic safety and vitalizing traffic safety policies. As expanding the responsibility and role of local governments for traffic safety, traffic safety measures which are based on the characteristics of each local government should be studied. Most of analytical methods in the existing traffic accidents prediction models with macroscopic vision focus on socioeconomic variables such as local population and the number of registered vehicles, and present a great deal of prediction error when they are applied in practice. In this context, this study proposed a traffic accident prediction model in respect of macroscopic level for autonomous districts (administrative districts) of Seoul City. The model development was not based on the entire city but on the type of local land usage (development density) whose relationship with traffic accident frequency was analyzed.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.579-588
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• 2022

In order to meet the needs of domestic reactor severe accident analysis program, a MIDAC (Module Invessel Degraded severe accident Analysis Code) is developed and maintained by Xi'an Jiaotong University. As the accuracy of the calculation results of the analysis program is of great significance for the formulation of severe accident mitigation measures, the article select three experiments to evaluate the updated severe accident models of MIDAC. Among them, QUENCH-06 is the international standard No.45, QUENCH-16 is a test for the analysis of air oxidation, and FROMA is an out-of-pile fuel rod melting experiment recently carried out by Xi'an Jiaotong University. The heating and melting model with lumped parameter method and the steam oxidation model with Cathcart-Pawel and Volchek-Zvonarev correlations combination in MIDAC could better meet the needs of severe accident analysis. Although the influence of nitrogen still need to be further improved, the air oxidation model with NUREG still has the ability to provide guiding significance for engineering practice.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.21-27
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• 1999

The objective of this study is to clarify the relationship between accident rate and V/C for freeway facility. The relationship can be used as a basic reference to predict and prevent traffic accident. The traffic volume and the number of accidents from 1992 to 1997 on Shingal-Ansan Freeway were analyzed in this study to clarify the relationship. Hourly accident rate and V/C were calculated for each facility sections : basic freeway section, tunnel section and toll gate section. The accident rate models consisting of an independent variable of V/C were established by repression analysis and compared with each other. The relationship between accident rates and V/C ratios represented U-shaped pattern for all sections. The result of this study indicates that accident rates are highest in the low hourly V/C range, decrease with increasing V/C ratio, and then increase as the V/C ratio increases. The accident rate of toll gate section is in general higher than that of other sections. Although the accident rate of tunnel section is higher than that of basic freeway section when V/C is above 0.67, there is no significant difference of accident rate between basic freeway and tunnel section when V/C is between 0.5 and 0.8. Basic freeway tunnel and toll gate section have the minimum accident rate when V/C is 0.78, 0.75 and 0.57 respectively.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.7-16
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• 2000

This paper is focused on verifying time-space repetition of the highway accident and finding the their causes and deterrents. We classify all months into several seasonal groups, develop the model for each seasonal group and analyze the results of these models for Joong-bu highway. The existence of seasonal effect is verified by the analysis or self-organizing map and the accident indices. Agglomerative hierarchical cluster analysis which is used to decide the seasonal groups in accordance with accident patterns, winter group, spring-fall group. and summer group. The accident features of winter group are that the accident rate is high but the severity rate is low. while those of summer group are that the accident rate is low but the severity rate is high. Also, the regression model which is developed to identify the accident Pattern or each seasonal group represents that the season-related factors, such as the amount of rainfall, the amount of snowfall, days of rainfall, days of snowfall etc. are strongly related to the accident pattern of evert seasonal group and among these factors the traffic volume, amount of rainfall. the amount of snowfall and days of freezing importantly affect the local accident Pattern. So, seasonal effect should be considered to the identification of high-risk road section. the development of descriptive and Predictive accident model, the resource allocation model of accident in order to make safety management plan efficient.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.348-356
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• 2007

• Proceedings of the KOR-KST Conference
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• 2007.05a
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• pp.218-226
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• 2007

• Proceedings of the KOR-KST Conference
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• 2007.05a
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• pp.171-178
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• 2007

• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.554-563
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• 2015

This study dealt with developing an accident model for rural signalized intersections with random parameter negative binomial method. The limitation of previous count models(especially, Poisson/Negative Binomial model) is not to explain the integrated variations in terms of time and the distinctive characters a specific point/segment has. This drawback of the traditional count models results in the underestimation of the standard error(t-value inflation) of the derived coefficient and finally affects the low-reliability of the whole model. To solve this problem, this study improves the limitation of traditional count models by suggesting the use of random parameter which takes account of heterogeneity of each point/segment. Through the analyses, it was found that the increase of traffic flow and pedestrian facilities on minor streets had positive effects on the increase of traffic accidents. Left turning lanes and median on major streets reduced the number of accidents. The analysis results show that the random parameter modeling is an effective method for investigating the influence on traffic accident from road geometries. However, this study could not analyze the effects of sequential changes of driving conditions including geometries and safety facilities.