• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.49-76
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• 1996

Until recently, the inductive loop detecters(ILD) have been used to collect a traffic information in a part of traffic manangment and control. The ILD is able to collect a various traffic data such as a occupancy time and non-occupancy time, traffic volume, etc. The occupancy time of these is very important information for traffic control algorithms, which is required a high accuracy. This accuracy may be improved by classifying a vehicle type with ILD. To classify a vehicle type based on a Analog Digital Converted data collect form ILD, this study used a typical and modifyed statistic method and General Learning Vector Quantization unsuperviser neural network model and a hybrid model of GLVQ and statistic method, As a result, the hybrid model of GLVQ neural network model is superior to the other methods.

• International Journal of Highway Engineering
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• v.7 no.3 s.25
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• pp.43-52
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• 2005

Highway classification is an essential part of defining design criteria of roads. This study is to classify highways by factor analysis. To accomplish the objectives, factor analysis is performed for classifying highways using the traffic data observed at the permanent traffic count points in 2004. A total off variables are applied : AADT, K factor, D factor, heavy vehicle proportion, day time traffic volume proportion, peak hour volume proportion, sunday factor, vacation factor and COV(Coefficient of Variation). The results of factor analysis show that variables are divided into two factors, which are the factor related to the fluctuational characteristics of traffic volume and the factor related to heavy vehicle and directional volume characteristics. According to the results of cluster analysis, 353 permanent traffic count points are categorized into such three groups as type I for urban highway, type II for rural highway, type III for recreational highway, respectively.

• Journal of Urban Science
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• v.10 no.1
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• pp.49-60
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• 2021

The purpose of this study is to analysis the impact on the inside of the new city when an incidents occurs on the Songdo International City connecting road, which has a limited access. The analysis data used KTDB's O/D and network data of the Seoul metropolitan area. In addition, the scenario composition applied a method of reducing the number of lanes on the road according to the situation of incidents, targeting bridges advancing from Songdo International City to the outside in the morning peak hours. The analysis method analyzed the traffic volume, total travel time, total travel kilometer, and route change in the new city based on the results of the traffic allocation model. As a result of the analysis, the range of influence was shown to two types. First, of the seven bridges, Aam 3, Aam 2, and Aam 1 were analyzed to have an impact only in some areas of the northwestern part of the new city. On the other hand, the remaining bridges were analyzed to affect the new city as a whole. The analysis results of this study are expected to be used as basic data to establish the scope of internal road network management when similar cases occur in the future.

• The Journal of Bigdata
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• v.2 no.2
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• pp.1-7
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• 2017

Intelligent transportation system (ITS) has been introduced to maximize the efficiency of operation and utilization of the urban traffic facilities and promote the safety and convenience of the users. With the expansion of ITS, various traffic big data such as road traffic situation, traffic volume, public transportation operation status, management situation, and public traffic use status have been increased exponentially. In this paper, we derive structural characteristics of urban traffic according to the vehicle flow by using big data network analysis. DSRC (Dedicated Short Range Communications) data is used to construct the traffic network. The results can help to understand the complex urban traffic characteristics more easily and provide basic research data for urban transportation plan such as road congestion resolution plan, road expansion plan, and bus line/interval plan in a city.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.779-784
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• 2011

Freeway FFS (Free-Flow Speed) under the state of LOS (Level of Service) A has been regarded as a homogeneous state to all levels of traffic volume. The features of low-density FFS is served as the basic data for a decision on limited maximal speed, accident analysis, simulation modeling etc. A few researches for the macroscopic characteristics of design and operation speed have been reported, and any study for the microscopic features of freeway free-flow speed under the state of low density has not been done. Therefore, the characteristics of low-density FFS according to the level of traffic volume (1-3 veh/30 sec) and daily hour periods (0-5, 6-8, 9-11, 12-19, 20-23) is microscopically analyzed in this study with huge volume and speed data. It was found that speed distributions are changed and show different behaviors under the conditions of traffic volume levels and daily time periods. V85s (85th percentile speed) at early morning and night periods decrease when levels of traffic volume increase, whereas V85s at day time do not show considerable differences. Especially, FFSs of levels of traffic volume at early morning and night periods, despite low density, is analyzed as heterogeneity, but homogeneity at day time.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.183-189
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• 2011

This paper suggests a user based OST(Open Street Traffic) system that solves TPEG's one-way communication problem, UTIS's limited usage and DSRC's small traffic bandwidth. In current commercial TPEG service, only some service providers collect traffic information. Thus, it can't cover traffic status in local lanes And UTIS, which local governments and police supports, requires additional equipments. Currently, only taxi and official vehicles use this system. Therefore, new traffic service by mobile device and user's participation can provide very detail traffic information coupling with previous traffic systems. But in this new system, real-time high volume data can be a problem. So, in this paper, new data storage manager design(TDSM :Traffic Data Storage Manager) is suggested and its performance is measured against commercial DBMS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.759-766
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• 2020

In recent years, the maritime traffic environment has been changing in various ways, and the traffic volume has been increasing constantly. Accordingly, the requirements for maritime traffic analysis have become diversified. To this end, traffic characteristics must first be analyzed using vessel trajectory data. However, as the conventional method is mostly manual, it requires a considerable amount of time and effort, and errors may occur during data processing. In addition, ensuring the reliability of the analysis results is difficult, because this method considers the subjective opinion of analysts. Therefore, in this paper, we propose an automated method of traffic network generation for maritime traffic analysis. In the experiment, spatiotemporal features are analyzed using data collected at Mokpo Harbor over six months. The proposed method can automatically generate a traffic network reflecting the traffic characteristics of the experimental area. In addition, it can be applied to a large amount of trajectory data. Finally, as the spatiotemporal characteristics can be analyzed using the traffic network, the proposed method is expected to be used in various maritime traffic analyses.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.4
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• pp.285-291
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• 2006

A traffic accident is occurred by unbalance of reciprocal action of driver, vehicle and road conditions. To prevent the traffic accident, rapid and perfect road improvement is needed. But most of road improvement plans have insufficient budget. So decision maker has to determine the priority to invest. A model in this study, analyzing the effect of road conditions to the traffic accident, helps to decide the priority in road improvement. This study considered five danger indices ; 1) traffic volume, 2) speed variance, 3) vehicle mixing rate, 4) curved line radius, and 5) difference between design speed and running speed. Danger rate composed by five indices can be a scale of priority of improvement. The model in this study didn't consider all of factors about traffic accident. But this study can propose the methodology for traffic safety policy. For deriving the model, this study used data from highways in Korea and United States. Therefore the model has to apply the highways only.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.117-125
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• 1993

GSIS is a system that contains spatially referenced data that can be analyzed and converted to information for a specific set of purpose, or application. The key feature of a GSIS is the analysis of data to produce new information. The current emphasis in the transportation is to implement GSIS in conjunction with real time systems Requirements for a transportation GSIS are very different from the traditional GSIS software that has been designed for environmental and natural resource applications. A transportation GSIS may need to include the ability for franc volume, forecasting, pavement management A regional transportation planning model is actually a set of models that are used to inventory and then forecast a region's population, employment, income, housing and the demand of automobile and transit in a region. The data such as adminstration bound, m of landuse, road networks, location of schools, offices with populations are used in this paper. Many of these data are used for analyzing of traffic volume, traffic demand, time of mad construction using GSIS.

• Journal of the Korean Institute of Navigation
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• v.12 no.1
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• pp.85-112
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• 1988

From the point of view of safety of life and property at sea and the protection of the marine environment, the Vessel Traffic Management System along the Korea coastal waterway is inevitably introduced. But the establishing priority per area must be evaluated under the restricted budget. In this case, the estimated traffic flow has a major effect on priority evaluation. In the former paper , an algorithm was proposed for estimating the trip distribution between each pair of zones such as harbours and straits. This paper aims to formulate a simulation model for estimating the dynamic traffic flow per area in the Korea coastal waterway. The model consists of the algorithm constrined by the statistical movement of ships and the observed data, the regression analysis and the traffic network evaluations. The processed results of traffic flow except fishing vessel are summarized as follows ; 1) In 2000, the traffic congestions per area are estimated, in proportion of ship's number (tonnage), as Busan area 22.3%(44.5%), Yeosu area 19.8%(11.2%), Wando-Jeju area18.1%(6.8%), Mokpo area 14.9%(9.9%), Gunsan area 9.1%(9.3%), Inchon area 8.1%(7.7%), Pohang area 5.5%(8.5%), and Donghae area 2.2%(2.1%). 2) For example in Busan area, the increment of traffic volume per annum is estimated 4, 102 ships (23 million tons) and the traffic flow in 2000 is evaluated 158, 793 ships (687 million tons). 3) consequently, the increment of traffic volume in Busan area is found the largest and followed by Yeosu, Wando-Jeju area. Also, the traffic flow per area in 2000 has the same order.