• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.89-100
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• 2008

The purpose of this paper is to analyze the differences between the severity of punishments for traffic laws related offenders and the choice of policy measures with a view to reducing traffic accidents. To this end, government data on the drivers given a sentence of license suspension or revocation were collected and analyzed in terms of sex, age, type of driver's license, driving career, number of traffic laws violations, and number of traffic accidents generated. The statistics of analysis of covariance and tests of significance were used and conducted to compare the effectiveness of punishment for the penalty and the incentive groups. The results showed that the incentive policy measure on the drivers who violate traffic regulations repeatedly is more effective to reduce the number of traffic offenders and traffic accidents.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.47-54
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• 2006

In order to reduce traffic accidents, many researchers studied a traffic accident model. The Cause of traffic accidents is usually the mis calculation of traffic signals or bad traffic intersection design. Therefore, to analyse the cause of traffic accidents, it takes effort. This paper, it calculates the optimal safe car speed considering intersection conditions and weather conditions. It will recommend calculation of 1/3 in vehicle speed when there are rainy days and snow days. But the problem is that it will always display the same speed limit when whether conditions change. In order to solve these problems, in this paper, it is proposed the calculation of optimal safety speed algorithm uses weather conditions and road conditions. Computer simulations is prove that it computes the traffic speed limit correctly, which proposed considering intelligent traffic accident prediction algorithms.

• 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 Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.41-51
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• 2006

In this paper, a fundamental study on the characteristics of traffic accidents according to the alignment and traffic conditions on the ramp of freeway is addressed. The macro-and-micro scope analysis of characteristics about traffic accidents on the trumpet-IC ramps is conducted depending on the entering and exit ramp types under the various conditions of traffic volume and alignment And it is turned out that the conditions of alignment. such as radius, differences of curvatures, and main road grade, and traffic volume relate to the ramp accidents of trumpet IC according to ramp types, such as direction, semi-direction, and loop. Macroscopically, AR (Accident Rate) according to trumpet IC types, A and B, is analyzed nearly equal, but Number of accidents occurred in IC type B shows about 1.5 times higher than type A. And AR of exit ramps shows three times more than entrance ramps. Microscopically, ARs for each exit-ramp type, according to the increment of traffic volume, the difference of curvatures. and the first radius, exponentially decrease respectively. But relationships between AR and the second radius or exit ramp shows inverted U-shaped. AR according to main-road grade Peaks between -1.5% and -0.5%. It is expected that the developed models not only are employed to make design of trumpet-IC ramp more cost-efficiently and safely, but also contribute to making alternatives to the reduction of traffic accidents on trumpet IC ramps under the conditions of high traffic accident rate.

• Journal of Preventive Medicine and Public Health
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• v.22 no.3 s.27
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• pp.313-322
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• 1989

The present status of the traffic accident rate in Korea shows that it is the highest in the world with a continuously increasing trend. Human factors account for 90% of the causes of traffic accidents. Therefore, the purpose of this study was to determine some human factors related to traffic accidents by studying the relationship between health status and traffic accidents. To accomplish this purpose, all taxi companies located in the Seoul area were divided in three groups according to the number of taxi possessed, then some companies in each ?roup were randomly selected for study, and a total of 222 drivers in those selected companies were questioned and examined from April 15 to April 22, 1989. Seventy drivers among 222 had experienced a traffic accident. A $x^2$-test was performed on the data, then, factor analysis and discrminant analysis were executed with the following results: 1. The drivers complaining of gastroenteric symptoms numbered 110(49.5%), which was the major symptom among all drivers complaining of poor health. 2. In the primary analysis, variables related to traffic accidents were divided into general, occupational, and health characteristics. Drivers having no traffic accident experience and drivers having that experience were subjected to question about age, educational level, residential status, monthly average income, working hours and days, degree of satisfaction with their profession and homelife, degree of worry about health. degree of fatigue, medication, drunken driving, and illness, but there were no statistical significances. 3. In the factor analysis, the 8 health variables which cause traffic accidents were classified into 3 common factors which were perceived health factor, sleeping and drunken driving, and visual acuity and smoking factor. Perceived health was the factor which contributed most to explaining accidents. 4. In the discriminant analysis, a correct prediction rate of 68.0% was obtained in the factors of all the characteristics. 5. Degree of sttisfaction with their homelife and educational and economic factor in the general characteristics, degree of satisfaction with their profession in the occupational characteristics, and sleeping and drunken driving in the health characteristics were selected as statistically significant factors to discriminant the traffic accident. 6. Among the factors of the general, occupational, and health characteristics, degree of satisfaction with their homelife, driving experience, family factor, perceived factor were selected as the statistically significant factors.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.67-77
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• 2007

This study deals with the traffic accidents at the unsignalized intersections in Cheongju. The purpose is to analyze the characters and the relations between road environmental factors and traffic accidents. The correlation analyses among the above factors show that the accidents are strongly related to traffic volumes and sight distances in 3-legged, and the cross angles, maximum vertical grades and sight distances in 4-legged unsignalized intersections. Also the multiple linear and nonlinear regression analyses represent that the accidents in the 3-legged increase as the traffic volume and the number of double stop-lines increase, and that the accidents in the 4-legged increase as the cross angle approaches to the 90 degree and decrease as the maximum vertical grade increases. It could be expected that this results give the good implications to the future intersection improvement projects in Cheongju.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.49-56
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• 2021

The purpose of this study is to develop a methodology to select a cluster of night traffic accidents using CRP (Continuous Risk Profile) analysis. the other purpose of this study is to present the characteristics of the traffic accident cluster section selected at night using CRP analysis. The CRP analysis was performed considering traffic volume of target routes through traffic accident data. In addition, variables were set according to the freeway sections. the method of subtracting the daytime CRP from the nighttime CRP was used to analyze the nighttime traffic accident. As a result, Using the CRP analysis, the sections of hotspot were identified and plotted based on traffic accidents. Also, the sections where traffic accidents are frequent were those where IC or Tunnels were installed, and there was a deviation from the general section. In conclusion, CRP analysis could be used to calculate the frequent section of specialized traffic accidents at night, and it was selected as a point in need of improvement due to the frequent occurrence of specialized traffic accidents at night in the section where IC or tunnel facilities are installed. In addition, it is inferred that the number of specialized traffic accidents at night in the section where IC or tunnel facilities are installed is a factor in the problem of night visibility due to lighting facilities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.20-37
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• 2023

Although traffic signal installations are continuously expanding, the effect of preventing traffic accidents remains unverified. Totally, 7,045 traffic accident data (such as signal violations) registered with TCS were manually searched for a 7-year period from 2013 to 2019 for 1,602 traffic signals in Daejeon Metropolitan City. The top 20 traffic accident intersections were identified, the traffic accident investigation records and field maps were viewed to compare the driving direction and signal phase of the violated vehicle, and the cause of the traffic accident was divided into insufficient signal operation design (operation) and driver negligence (intentional). Results of the analysis revealed that 75% of traffic accidents occurred in thru-left-turn traffic signals and overlap; moreover, extending the yellow time or operating all red signals due to countermeasures against traffic accidents occurring in yellow signals resulted in reduced traffic accidents. Data indicated that Permissive Left Turn requires improvement with the signal operation. In addition, since The Korean National Police Agency is not computerized for traffic accident sites and signal-related data, the lack of manpower necessitates improvement and utilization of TCS when establishing traffic accident prevention measures. It is believed that it will contribute to signal operation by analyzing vast amounts of data collected in the field and presenting improvement measures.