• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.584-590
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• 2000

Urban traffic situations are extremely complex and highly interactive. The multi-agent systems approach can provide a new desirable solution. Currently, a traffic simulator is needed to understand and explore the difficulties in an agent-oriented traffic control. This paper presents an agent-oriented fuzzy logic controller for multiple crossroads simulation. A fuzzy logic control simulation with variables of arrival, queue, and traffic volume could alleviate traffic congestion. We developed an agent-oriented simulator suitable for traffic junctions with η$\times$η intersections in Visual C++. The proposed method adaptively controls the cycle of traffic signals even though the traffic volume varies. The effectiveness of this method was shown through simulation of multiple intersections.

• International Journal of Highway Engineering
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• v.19 no.5
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• pp.143-151
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• 2017

PURPOSES : The purpose of this study is to develop models of accidents occurring at circular intersections related to the time of day and night and driver gender, and to provide countermeasures for safer circular intersections. METHODS : Seventy intersections built before 2008 were surveyed for inclusion in the modeling. Traffic accident data from 2008 to 2014 were collected from the TAAS data set of the Road Traffic Authority. Sixteen variables explaining the accidents including geometry and traffic volume were selected from the literature and seven multiple linear regression models were developed using SPSS 20.0. RESULTS : First, the null hypotheses, that the number of traffic accidents are not related to driver gender or time of day, were rejected at a 5% level of significance. Second, seven statistically significant accident models with $R^2$ value of 0.643-0.890 were developed. Third, in daytime models by gender, when the right-turn-only lane was selected as the common variable, the number of lanes, presence of driveways and speed humps, diagrammatic exit destination sign, and total entering traffic volume were evaluated as specific variables. Finally, in nighttime models by gender, when the diagrammatic exit destination sign was selected as the common variable, total entering traffic volume, presence of right-turn-only lanes, number of circulatory road way lanes, and presence of splitter islands and driveways were identified as specific variables. CONCLUSIONS:This study developed seven accident models and analyzed the common and specific variables by time of day and gender. The results suggest approaches to providing countermeasures for safer circular intersections.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.90-99
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• 2015

The climate of Korea has clear rainy and dry season due to seasonal wind. In general, The rainy season in Korea is from early summer through to early fall. And precipitation accounted for more than half of the total annual rainfall in this period. This study is aiming to analysis of variation in saturation flow rate at signalized intersection during rainfall. The range of spatial is urban signalized intersections in Seoul and temporal is rainfall or ideal condition in daylight. Traffic data are collected through CCTV of Seoul Metropolitan Police Agency, and on-site video recordings directly. Weather condition data are collected from the Korea Meteorological Administration. In addition, the value of saturation headway and saturation flow rate, in rainfall condition, are derived through video frame analysis. As a results of analysis, decrease of saturation flow rate and increase of saturation headway during rainfall were confirmed by comparison with non-rainfall. The higher rainfall rate is, the more decreased saturation flow rate at the intersections. Rainfall rate is divided three area by the results of statistical test, and saturation flow rate decrease 7%, 17%, 21%, respectively.

• Journal of the Korean Society of Safety
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• v.25 no.2
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• pp.89-94
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• 2010

This study deals with the traffic accident according to the improvement projects of frequent accident locations. The objective is to analyze the impact of improvements on the accident reduction. In pursuing the above, the study gives the particular attentions to developing the models based on the data of 70 intersections improved. The main results analyzed are as follows. First, 4 multiple linear regression accident models(total, side right-angle, rear end and side stripe accident) which were statistically significant were developed. Second, total accidents reduction by sight-distance and turning traffic flow improvements, side right-angle by sight-distance, over-speed and lane operation, rear end by turning traffic flow, signal and lane operation, and side stripe by traffic impedance improvements were analyzed. Finally, the above 4 models were evaluated to be statically significant through the correlation analysis and pair-sample t-test.

• Journal of the Society of Disaster Information
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• v.11 no.4
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• pp.597-606
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• 2015

Until now, u-turn lane installation methods have been studied variously. But, There is no specific standard yet. This study ranges are commercial area in Incheon metropolitan city through field investigation and presents specific design standard for efficient operation of left turn using a field data through calculating relevant permitted u-turn lane length and minimum separation distance from the front intersection to starting point of permitted u-turn lane in urban signalized intersections in commercial area. Relevant permitted u-turn lane length is found to be 32m and minimum separation distances from the front intersection to starting point of permitted u-turn lanes are 72m, 40m, 24m in case of 1 left turn lane, 2 left turn lanes and 3 left turn lanes respectively. By comparing result values and field data, they had a large difference under the similar situations in their lengths. This result is caused of no specific standard about design of u-turn lanes. If results of this study applied to design of u-turn lanes, signalized intersections in urban commercial areas would be operated more safety and efficiently.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.123-134
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• 2016

Traffic accident at intersections takes 44.3% of total number of accidents on entire road network of Korea in 2014. Although several studies addressed contributory factors of accidents at signalized intersection, very few is known about the factors at rural unsignalized intersections. The objective of this study is therefore to investigate specific characteristics of crashes at rural unsignalized intersection and to identify contributory factors in causing crashes by statistical approach using the Ordered Logistic Regression Model. The results show that main type of car crashes at unsignalized intersection during the daytime is T-bone crashes and the number of crashes at 4-legged intersections are 1.53 times more than that at 3-legged intersections. Most collisions are caused by negligence of drivers and violation of Right of Way. Based upon the analysis, accident severity is modeled as classified by two types such as 3-legged intersection and 4-legged intersection. It shows that contributory factors in causing crashes at rural unsignalized intersections are poor sight distance problem, average daily traffic, time of day(night, or day), angle of intersection, ratio of heavy vehicles, number of traffic violations at intersection, and number of lanes on minor street.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.26-37
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• 2017

The study is to develop safety performance functions(SPFs) for urban intersections using random effects Tobit regression model and to analyze correlations between crashes and factors. Also fixed effects Tobit regression model was estimated to compare and analyze model validation with random effects model. As a result, AADT, speed limits, number of lanes, land usage, exclusive right turn lanes and front traffic signal were found to be significant. For comparing statistical significance between random and fixed effects model, random effects Tobit regression model of total crash rate could be better statistical significance with $R^2_p$ : 0.418, log-likelihood at convergence: -3210.103, ${\rho}^2$: 0.056, MAD: 19.533, MAPE: 75.725, RMSE: 26.886 comparing with $R^2_p$ : 0.298, log-likelihood at convergence: -3276.138, ${\rho}^2$: 0.037, MAD: 20.725, MAPE: 82.473, RMSE: 27.267 for the fixed model. Also random effects Tobit regression model of injury crash rate has similar results of model statistical significant with random effects Tobit regression model.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.17-28
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• 2009

There are many limitations in dealing with rapidly changing traffic demand in urban cities. Thus recently, traffic operation and management skills are more emphasized rather than the expansion of traffic facilities. In particular, in the interrupted flow formed by signalized intersections, it is quite important to give optimal signal timing to each intersection with consideration of progression. However, as fixed signal times per direction can affect passing capacity in signalized intersections, the present four-signal phase including a left-turn signal has many limitations, including reduction of directional road capacity when traffic demand is increases dramatically during peak hours. Because of this problem, lots of studies about internal metering techniques for oversaturated signal control skills have progressed but these techniques are not used widely due to the absence of detectors for queue sensing in real-time signal control systems. In this research, a new methodology called the "restrictive left-turn signal control", which is already used at the intersection above Samsung subway station, is suggested in order to reduce control delay of urban arterial roads. The restrictive left-turn signal control allows a driver to make a U-turn and then a right turn instead of turning left in that intersection. With this change, the restrictive left-turn signal control can contribute to increased intersection capacity by reducing the number of signal phases and maximizing the through phase time. However, road structure and traffic conditions at the target intersections should be considered before the adoption of the proposed signal control.

• 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.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.69-77
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• 2011

This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.