• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.171-177
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• 2008

As the risk of traffic accidents caused by mists emerged as a social problem, recently safety facilities to be prepared for mists are being actively installed when designing roads. But in some part, the facilities are being installed imprudently without analyzing the extent of occurrences of mists that would increase the risk of traffic accidents and appropriate countermeasures against the occurrences of mists are not being suggested. For that reason, in this study, first questionnaire surveys were executed on road users in order to draw the factors affecting the traffic accidents caused by mists, a mist traffic accident predicting model was developed and an accident seriousness determining model that can determine accident seriousness was developed. In this way, by extracting major factors affecting mist traffic accidents to grasp risk factors in roads to be caused by mists, safety of roads can be enhanced and traffic accidents in road operations can be decreased. As the affecting factors influencing mist traffic accidents, were extracted sightable distances, durations of mists and whether daytime or nighttime as major factors and the plan to install the facilities for the prevention of mist traffic accidents was suggested to prevent the traffic accidents to be caused by those factors and also the plan to operate roads considering sightable distances was suggested to solve the problem of insufficient sightable distances to be caused by mists was suggested. It is judged that the road safety in the areas where mists occur can be improved through foregoing methods.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.203-215
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• 2013

PURPOSES : This study deals with first traffic violations occurred by novice drivers, which may be associated with traffic accidents. The objective of this study is to identify what kinds of drivers' characteristics influence on duration till the first traffic violation. METHODS : For the study, Survival Analysis and Cox proportional hazard model, that are usually used in the medical field, were employed. Survival Analysis was conducted to investigate whether there exist differences in survival duration by each covariate, whereas Cox proportional hazard model was used to identify significant factors that affect survival duration till novice drivers violate traffic regulations for the first time after getting a driver license. RESULTS : The results of Survival Analysis indicate that female, age (less than 21), low-frequency examinee of written exam, and non-crash involved drivers have longer duration till the first violation compared to male, greater than 21 years old, high-frequency examinee of written exam, and crash involved drivers, respectively. For the Cox proportional hazard model, license class 1 acquisitor was found to increase the survival duration till the first traffic violation was made, while male, age of 21-24, age of 25-34, age of 45-54, and crash involved drivers were more likely to reduce the survival duration. CONCLUSIONS : Absolutely, traffic violation is closely related to traffic accidents and all of the drivers should keep the traffic regulations to enhance highway safety. The results of this study might provide some insights to construct safe road environments by controlling the factors that reduce the traffic violation duration of novice drivers.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.301-310
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• 2021

The TATI model is a Traffic Accident Text to RGB Image model, which is a methodology proposed in this paper for predicting the severity of traffic accidents. Traffic fatalities are decreasing every year, but they are among the low in the OECD members. Many studies have been conducted to reduce the death rate of traffic accidents, and among them, studies have been steadily conducted to reduce the incidence and mortality rate by predicting the severity of traffic accidents. In this regard, research has recently been active to predict the severity of traffic accidents by utilizing statistical models and deep learning models. In this paper, traffic accident dataset is converted to color images to predict the severity of traffic accidents, and this is done via CNN models. For performance comparison, we experiment that train the same data and compare the prediction results with the proposed model and other models. Through 10 experiments, we compare the accuracy and error range of four deep learning models. Experimental results show that the accuracy of the proposed model was the highest at 0.85, and the second lowest error range at 0.03 was shown to confirm the superiority of the performance.

• Journal of KIISE
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• v.44 no.4
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• pp.433-438
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• 2017

Presently, the ubiquitous emergence of high-speed-network environments has led to a rapid increase of various applications, leading to constantly complicated network traffic. To manage networks efficiently, the traffic classification of specific units is essential. While various traffic-classification methods have been studied, a methods for the complete classification of network traffic has not yet been developed. In this paper, a correlation model of the network flow is defined, and a traffic-classification method for which this model is used is proposed. The proposed network-correlation model for traffic classification consists of a similarity model and a connectivity model. Suggestion for the effectiveness of the proposed method is demonstrated in terms of accuracy and completeness through experiments.

• 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 the Korean Society of Safety
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• v.28 no.2
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• pp.78-83
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• 2013

The traffic culture index is used as a major index in evaluating the traffic safety services of local governments and also serve as important data for the planning and implementation of traffic safety services. However, as the traffic culture index gradually became a standard for comparison among local governments, in part, certain cases arose which questioned the grounds for selecting variables for the index and the validity of the index in terms of its influential relationship between evaluation items. This study analyzed the index's influential relationship by utilizing a PLS structural equation model based on the evaluation results of the 2011 traffic culture index. A variable-linking model was created which recognized the relativity taking into account of the indirect effects between latent variables and this model was proven to be a model suitable in explaining the traffic culture index with a 97.8% explanation power. It was found that traffic safety(0.530), driving behavior(0.527), pedestrian behavior(0.187) and vulnerable road users(0.147), in such order, had an effect on the traffic culture index. It was also found that human casualties due to traffic accidents under "traffic safety" and traffic light compliance rate under "driving behavior" had an important effect. The study showed that motor vehicle share in illegal parking in school zones did not have a valid explanation power regarding "vulnerable road users".

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.51-69
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• 2009

A network model and a Genetic Algorithm (GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing a non-linear objective function with the linear constraints. In the model, the flow-conservation constraints are utilized to restrict the solution space and to force the link flows become consistent to the traffic counts. The objective of the model is to minimize the discrepancies between two sets of link flows. One is the set of link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links. The other is the set of link flows those are estimated through the trip distribution and traffic assignment using the path flow estimator in the logit-based SUE. In the proposed GA, a chromosome is defined as a real vector representing a set of Origin-Destination Matrix (ODM), link flows and route-choice dispersion coefficient. Each chromosome is evaluated by the corresponding discrepancies. The population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment technique is used during the crossover and mutation.

• Wind and Structures
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• v.29 no.3
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• pp.149-161
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• 2019

When a railway vehicle runs in crosswinds, the unsteady aerodynamic forces acting on the train induced by the vehicle speed, crosswind velocity and local landforms are a common problem. To investigate the dynamic performance of a railway vehicle due to the influence of unsteady aerodynamic forces caused by local landforms, a vehicle aerodynamic model and vehicle dynamic model were established. Then, a wind-loaded vehicle system model was presented and validated. Based on the wind-loaded vehicle system model, the dynamic response performance of the vehicle, including safety indexes and vibration characteristics, was examined in detail. Finally, the effects of the crosswind velocity and vehicle speed on the dynamic response performance of the vehicle system were analyzed and compared.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.824-826
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• 2000

네트워크 데이터 traffic 특성은 네트워크의 성능분석과 설계에 중요한 요소이고 적절한 traffic modeling을 통해 load balancing, fault tolerance 및 전송속도 개선 둥 시스템 성능을 높이는데 보다 유용한 자료를 제공할 수 있어 지금까지 많은 연구가 진행되어 왔다. 그러나 네트워크 traffic은 네트워크의 규모와 서비스 종류 등 여러 가지 이유로 어느 한가지 모델로 규정짓는 것이 용이하지 않다. 또한 근래 인터넷 사용자의 수가 급속히 증가함에 따라 네트워크 traffic의 대부분이 world wide web에 기인하는 특성을 볼 수 있다. 본 논문에서는 웹서버 운용환경 하에서 적용될 수 있는 traffic model들에 대해 고찰하고 실제 네트워크에서의 패킷 모니터 링을 통한 traffic 분석 예를 보인다.