• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.129-134
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• 2017

This study aims to develop the traffic accident models by circular intersection type using count data model. The number of accident, the number of fatal and injured persons(FSI), and EPDO are calculated from the traffic accident data of TAAS. The circular intersection accident models are developed through Poisson and negative binomial regression analysis. The main results of this study are as follows. First, the null hypotheses that there are differences in the number of traffic accidents, FSI and EPDO by type of circular intersections are rejected. Second, the scale of intersection(median, large), number of approach road, mean width and length of exit road, area of the circulating roadway and central island are selected as factors influencing the number of traffic accidents, FSI and EPDO in rotary. Third, the scale of intersection(median), guide signs(limited speed, direction, roundabout), number of approach road, entry angle, area of the intersection and central island are adopted as factors influencing the number of traffic accidents, FSI and EPDO in roundabout. Finally, transferring from rotary to roundabout could be expected to make the accident decrease.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.501-509
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• 2004

The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.291-303
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• 2016

The number of traffic accidents at intersections has been increased over the past decade, and in 2014, accounted for 44% of the total traffic accidents. In addition, since most of road accident black spots include signalized intersections, the improvement of safety on signalized intersection is top priority for national road safety program in Korea. For the decision of most effective action plan for the safety of signalized intersection, this study conducted meta-analyses to assess the effects of various road safety facilities at signalized intersection on traffic accidents. We selected 19 articles regarding the prediction of traffic accidents at signalized intersection and calculated 34 individual effect sizes on 8 variables included in the articles. The results found that there was a statistically significant negative relationship between the occurrence of traffic accident and the presence of all of road safety facilities except an exclusive left turn bay. It shows that most of the road safety facilities could prevent traffic accidents, and intersection channelization has the most effective on the reduction of traffic accidents followed by left-turn acceleration lane, lightning, crosswalk, exclusive right-turn lane and median barrier.

• Journal of the Korean Society of Safety
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• v.23 no.2
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• pp.65-71
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• 2008

As the interest in traffic safety has been increasing recently, social movement is being made to reduce the number of traffic accidents and the view on improving the mobility of the existing roads is being converted into on establishing traffic safety as a priority. The increase of traffic accidents related to an intersection in a state that traffic accidents are decreasing overall may suggests the necessity to investigate the specific causes. In addition, we have to consider them when establishing the measures against traffic accidents in a intersection by investigating and analyzing the influences and factors that may affect traffic accidents. To induce the accident severity model, we collected the factors that affect accidents and then applied the Poisson Regression Model among nonlinear regression analysis by verifying the distribution of variables. As a result of the analysis, it turned out that the volume of traffic on main roads, the right turn ratio on sub-roads, the number of ways out on sub-roads, the number of exclusive roads for a left turn, the signals for a right turn on main roads, and an intersect angle were the factors that affect the accident severity.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.63-72
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• 2007

The purpose of this study is to develop a traffic characteristic analysis, a correlation analysis with the variables of traffic characteristics, and accident estimation models while recognizing the seriousness of the traffic accidents. The analyses deal with the 181 4-legged signalized intersections that accounted for 1,183 out of 3,115 accidents in Cheongju in 2004. After measuring ADT, intersection area, average lane width, elevation, and other items as independent variables and the number of traffic accidents, the traffic accident rate (accidents per million entering vehicles) and equivalent property damage only (EPDO) figures as dependent variables which are estimated as influencing signalized intersection accidents, the estimation models are developed using correlation analysis and multiple regression analysis. In the analysis of the number of traffic accidents, the model indicates an $R^2$ of 0.612, and five independent variables are taken as significant factors. In the analysis of traffic accident rates, the model indicates an $R^2$ of 0.304 and five significant factors, including intersection area and ADT. Also, for the analysis or the EPDO numbers, which coincides with understanding the seriousness of the traffic accidents and the traffic characteristic analysis, the model indicates an $R^2$ of 0.559, and four independent variables (ADT, main street average lane width, elevation, and speed limit) as significant factors.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.107-115
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• 2009

Traffic islands were introduced for drivers and pedestrians to use the road in a safe and orderly way and were also a specified zone between traffic lanes to divide conflicting traffic flows and to provide pedestrian refuge. However, existing research and relevant standards described its purpose and effects only but not a safety standard to decide whether the traffic island warranted. This study was to introduce a parameter which had a high relationship with accidents by analyzing road and traffic conditions and traffic accident data at urban intersections. Based on the relationship between the parameter and the traffic accidents at the intersection, a pedestrian accident probability model was made by using a logit model. In addition, the study reviewed a pedestrian accident probability corresponding to traffic volume and size of the intersection during design of the intersection and then suggested the effectiveness of the traffic island in terms of traffic safety. In conclusion, when a large-scale intersection has significant traffic volumes, a high probability of traffic island-induced pedestrian accidents appears, while in the case of small volumes, the probability is low. Targeted design and operations of a traffic islands is necessary, because its introduction itself does not enhance pedestrian safety in all cases at all intersections. This study can be a useful reference for further development to set up a scheme of the traffic islands in terms of traffic safety.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.61-74
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• 2009

Traffic accident risk index Computation model's development apply traffic level of significance about area of road user group, road and street network area, population group etc.. through numerical formula or model by countermeasure to reduce the occurrence rate of traffic accidents. Is real condition that is taking advantage of risk by tangent section through estimation model and by method to choose improvement way to intersection from outside the country, and is utilizing being applied in part business in domestic. However, question is brought in the accuracy being utilizing changing some to take external model in domestic real condition than individual development of model. Therefore, selection intersection estimation element through traffic accidents occurrence present condition, geometry structure, control way, traffic volume, turning traffic volume etc. in 96 intersections in this research, and select final variable through correlation analysis of abstracted estimation elements. Developed intersection design model taking advantage of signal type, numeric of lane, intersection type, analysis of variance techniques through ANOVA analysis of three variables of intersection form with selected variable lastly, in signal crossing through three class intersection, distinction variable choice risk in model, no-signal crossing risk distinction analysis model and so on develop.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.137-145
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• 2012

According to the National Police Agency, the total number of traffic accidents which occurred in 2010 was 226,878. Intersection accidents accounts for 44.8%, the largest portion of the entire traffic accidents. An research on the signalized intersection is constantly made, while an research on the unsignalized intersection is yet insufficient. This study selected traffic volume, road width, and sight distance as the input variables which affect unsignalized intersection accidents, and number of accidents as the output variable to build a model using ANFIS(Adaptive Neuro-Fuzzy Inference System). The forecast performance of this model is evaluated by comparing the actual measurement value with the forecasted value. The compatibility is evaluated by R2, the coefficient of determination, along with Mean Absolute Error (MAE) and Mean Square Error (MSE), the indicators which represent the degree of error and distribution. The result shows that the $R^2$ is 0.9817, while MAE and MSE are 0.4773 and 0.3037 respectively, which means that the explanatory power of the model is quite decent. This study is expected to provide the basic data for establishment of safety measure for unsignalized intersection and the improvement of 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.