• International Journal of Highway Engineering
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• v.19 no.2
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• pp.167-174
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• 2017

PURPOSES: This study aims to analyze the impact of the implementation of a school zone traffic safety improvement project on the number of accidents involving children in these zones. METHODS : To analyze the correlation between school zone traffic safety features of roads in the zone and the number of accidents involving children, we developed an occurrence probability model of traffic accidents involving children by using a binary logistic regression model with SPSS 23.0 software. Two separate models were developed for two zones: interior block and arterial road. RESULTS :The model depicted that in the case of the interior block, shorter sidewalk width, speed bump, and an elevated crosswalk were key factors affecting the occurrence of accidents involving children. In the case of arterial roads exceeding a width of 12 m, the speed limit, roadside barriers, and red paving of road surfaces were found to be the key factors. CONCLUSIONS:The results of this study can serve as the elementary research data to help improve the effectiveness of school zone traffic safety improvement projects and school zone road repair projects in future.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.136-145
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• 2004

In companion paper, the composition and structure of the traffic environment is derived. Rules to regulate agent behaviors and the frameworks to communicate between the agents are proposed. In this paper, the model of a driver agent which controls a vehicle agent is constructed. The driver agent is capable of having different driving styles. That is, each driver agent has individual behavior settings of the yielding index and the passing index. The yielding index can be defined as how often the agent yields in case of lane changes, and the passing index can be defined as how often the agent passes ahead. According to these indices, the agents overtake or make their lanes for other vehicles. Similarly, the vehicle agents can have various vehicle dynamic models. According to their dynamic characteristics, the vehicle agent shows its own behavior. The vehicle model of the vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted flow model. The result has shown that it is possible to express the characteristics of each vehicle and its driver in a traffic flow, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed in this paper shows the effectiveness and the practical usefulness of the traffic simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.304-309
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• 2008

This paper propose the traffic anomaly detection scheme based time series model. We apply ARIMA prediction model to this scheme and transform the value of the abnormal symptom into the probability value to maximize the traffic anomaly symptom detection. For this, we have evaluated the abnormal detection performance for the proposed model using total traffic and web traffic included the attack traffic. We will expect to have an great effect if this scheme is included in some network based intrusion detection system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.246-252
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• 2015

This paper compared the consistency of the Environment Stress(ES) model and the Potential Risk Assessment Model (PARK model, which was developed based on a Korean mariner risk perception) for the Busan adjacent waterway. Evaluation of accuracy and comparison of these two models have been made by Vessel Traffic Service (VTS) officers in the Busan VTS Centre. The assessment results of Busan waterway show that the PARK model is more consistent than the ES model as follows. (1) The difference between assessment results applying ES model and PARK model with risk degree of VTSOs were 34% and 5% respectively in six typical traffic situations. (2) The assessment using PARK model is more suitable and identical with the VTSOs opinion in his or her duty time.

• Spatial Information Research
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• v.23 no.4
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• pp.79-89
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• 2015

This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.71-80
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• 2023

With the rapid advancement of the Internet, the use of encrypted traffic has surged in order to protect data during transmission. Simultaneously, network attacks have also begun to leverage encrypted traffic, leading to active research in the field of encrypted traffic analysis to overcome the limitations of traditional detection methods. In this paper, we provide an overview of the encrypted traffic analysis field, covering the analysis process, domains, models, evaluation methods, and research trends. Specifically, it focuses on the research trends in the field of anomaly detection in encrypted network traffic analysis. Furthermore, considerations for model development in encrypted traffic analysis are discussed, including traffic dataset composition, selection of traffic representation methods, creation of analysis models, and mitigation of AI model attacks. In the future, the volume of encrypted network traffic will continue to increase, particularly with a higher proportion of attack traffic utilizing encryption. Research on attack detection in such an environment must be consistently conducted to address these challenges.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.14-25
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• 2018

In recent years, it has become technically easier to explain factors related with traffic accidents in the Big Data era. Therefore, it is necessary to apply the latest analysis techniques to analyze the traffic accident data and to seek for new findings. The purpose of this study is to compare the predictive performance of the negative binomial regression model and the deep learning method developed in this study to predict the frequency of traffic accidents in expressways. As a result, the MOEs of the deep learning model are somewhat superior to those of the negative binomial regression model in terms of prediction performance. However, using a deep learning model could increase the predictive reliability. However, it is easy to add other independent variables when using deep learning, and it can be expected to increase the predictive reliability even if the model structure is changed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.107-114
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• 2014

The purpose of this study is to explore a correlation model of traffic safety and personality in elderly and non-elderly people. The correlation model is constructed by a factor regression analysis with latent factors and items related to traffic safety consciousness. As a result, it is found that non-elderly people with positive, active, perfectionistic, and unforgiving personality are likely to speed, have a high chance to be involved in traffic accidents, and tend to give low scores to traffic conditions. However, elderly people who are highly educated are likely to give high scores to traffic conditions and do not speed. Instead, elderly people become more likely to be involved in traffic accidents when they are engaged in more social activities. The results could contribute to developing traffic safety education and policy that is better customized to the specific needs of different groups of road users.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1571-1579
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• 2014

93% of road traffic accidents result from drivers' fault and Korea has the largest number of deaths from traffic accidents among the OECD members. For this reason, the country is measuring Traffic Culture Index (TCI) in each city, gun and gu annually to improve traffic safety policies and promote safety consciousness, but the influencing relation between TCI and actual traffic accidents is only based on the assumptions and no verification has been carried out, yet. Therefore, this study aims to verify if in reality, TCI represents the traffic culture level and has an influencing relation with traffic accidents and to suggest an improvement plan of research on the present state of TCI, based on the result. For this purpose, bases on data of the report about the present state of TCI from 2010 to 2012, and the influencing relation between the number of traffic accidents and the number of deaths from traffic accidents was analyzed through structural equation model. For influencing relation analysis through structural equation, research 1 to analyze the relation among TCI in each city, gun and gu, the number of traffic accidents and the number of deaths, and research 2 to analyze the influencing relation of the increase in TCI, the number of traffic accidents and the number of deaths were carried out. When verifying the influencing relation with traffic accidents through structural equation, the goodness of fit of the model was low in research 1 and as TCI increased, the number of accidents and deaths decreased in research 2 and thus the effect of TCI was verified.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.979-987
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• 2005

In this research we study conventional and new statistical methods to analyse and detect outliers in network traffic and we apply the nonlinear time series model to make better performance of detecting abnormal traffic rather the linear time series model to compare the performances of the two models.