• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.39-52
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• 2002

Traffic data by vehicle classification is difficult for mutual exchange of data due to the different vehicle classification from each other by the data sources; as a result, application of the data is very limited. In Particular. in case of TCS vehicle classification in national highways, passenger car, van and truck are mixed in one category and the practical usage is very low. The research standardize the vehicle classification to convert other data and develop the model which can estimate national highway traffic data by the standardized vehicle classification from the raw traffic data obtained at the highway tollgates. The tollgates are categorized into several groups by their features and the model estimates traffic data by the standardized vehicle classification by using the point estimation and bootstrap algorithm. The result indicates that both of the two methods above have the significant level. When considering the bias of the extreme value by the sample size, the bootstrap algorithm is more sophisticated. Using result of this study, we is expect the usage improvement of TCS data and more specific comparison between the freeway traffic investigation and link volume on freeway using the TCS data.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.75-85
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• 2018

PURPOSES : This study aimed to analyze traffic accidents at circular intersections, and discuss accident reduction strategies based on land use and vehicle type. METHODS : Traffic accident data from 2010 to 2014 were collected from the "traffic accident analysis system" (TAAS) data set of the Road Traffic Authority. To develop the accident rate model, a multiple linear regression model was used. Explanatory variables such as geometry and traffic volume were used to develop the models. RESULTS : The main results of the study are as follows. First, it was found that the null hypotheses that land use and vehicle type do not affect the accident rate should be rejected. Second, 16 accident rate models, which are statistically significant (with high $R^2$ values), were developed. Finally, the area of the central island, number of speed humps, entry lane width, circulatory roadway width, bus stops, and pedestrian crossings were analyzed to determine their effect on accidents according to the type of land use and vehicle. CONCLUSIONS : Through the developed accident rate models, it was revealed that the accident factors at circular intersections changed depending on land use and vehicle type. Thus, selecting the appropriate location of bus stops for trucks, widening entry lanes for cars, and installing splitter islands and optimal lighting for motorcycles were determined to be important for reducing the accident rate. Additionally, the evaluation showed that commercial and mixed land use had a weaker effect on accidents than residential land use.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.1-15
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• 2023

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.121-134
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• 2003

Forecasting models for crosswalk pedestrian volume, which consider safety of crosswalks and good traffic operation accidents, have been established in order to reduce total number of crosswalk pedestrian accidents. However, the existing models did not include pedestrian volume which seemed to be very significant in the forecasting models because there were no pedestrian volume related data and no methods of estimating pedestrian volume. This paper presents estimating models for the total number of trips, which are produced in zone i and attracted to zone j, and a process of estimating pedestrian volume in the goal year. First of all, the estimating models included the characteristics of land-use around a signalized intersection and the crosswalk pedestrian volume as factors. Secondly, the estimated crosswalk pedestrian volume was distributed to the crosswalk pedestrian volume each path in the basic year by friction factors of Gravity Model, adjustment factors for area and ratio of pedestrian volume who moved diagonally at the crosswalk. Thirdly, the estimating models of crosswalk pedestrian volume in the goal year were presented by using the distributed crosswalk pedestrian volume.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.1-12
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• 2014

The tier 3 methodology used in estimation of greenhouse gas emissions from road sectors is based on mileage data. However, such data can neither accurately represent the mileage of regional unit nor have sufficient integrated data reflecting the characteristics by region, vehicle type, fuel type and road type. Such estimation of greenhouse gas emissions is not reliable. Accordingly, the purpose of this study is, firstly to accumulate activity data based on distance traveled which enables us to accurately estimate the amount of green gas emitted by regional unit(emission point), and secondly, to develop a methodology for estimation of greenhouse gas emissions using these data. To do this, the study utilizes the mileage data of Korea Transportation Safety Authority(TS), statistics of registered motor vehicles, statistical yearbook of traffic volume from the Ministry of Land, Infrastructure and Transport(MLIT), the Korea Transport Database of the Korea Transport Institute(KOTI), and average road speed by local government. Methodology for estimation by local government level(emission point) is meaningful, because it reflects traffic pattern data including flow in and out and internal traffics. Finally, to verify the methodology presented in this study, it is applied to Seoul. Both greenhouse gas estimates, one by multiplying the average mileage and the number of registered vehicles and the other by multiplying traffic volume and road extension, are less than the amount estimated by the methodology presented in this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1524-1531
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• 2004

This study analyzes a load balancing technique using Round Robin Algorithm. The study uses two software packages (Packet Capture and Round Robin Test Package) to check packet volume from Virtual Network structure (data generator, virtual server, Server1,2,3), and finds out traffic distribution toward Server1,2 and 3. The functions of implemented Round Robin Load Balancing Monitoring System include round robin testing, system monitoring, and graphical indication of data transmission and packet volume. As the result of the study shows, Round Robin Algorithm allows servers to ensure definite traffic distribution, unless incoming data loads differ much. Although error levels are high in some cases, they were eventually alleviated by repeated tests for a long period of time.

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.83-91
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• 2012

The objective of this study is to build a methodology for evaluating intelligent transportation systems (ITS) projects, by selecting measures of effectiveness (MOEs) and developing an approach to collect and process traffic data. While reviewing the existing MOEs and evaluation methodologies for ITS projects, several problems were found, such as the complication in delineating study areas, the absence of standardized evaluation methodologies, and the duplication in selecting MOEs. To tackle these problems, two MOEs capable of directly evaluating traffic conditions were chosen: i.e., average vehicle speed and traffic volume. Both MOEs can not only include all the functions of the existing MOEs, but also be simpler and more objective in evaluating real traffic conditions. The traffic volume can be measured by using either "cordon line" or "all point average" methods. On the other hand, measuring the average vehicle speed depends on site-specific characteristics such as traffic flow states (interrupted or uninterrupted) and traffic conditions (congested or uncongested). The present methodology is easily understandable for anyone and applicable for any ITS project, and is also expected to contribute to building a standardized evaluation system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.130-145
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• 2021

As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.66-83
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• 2021

Vehicles experience changes in driving behavior due to the various facilities on the freeway. These sections may cause repetitive traffic congestion when the traffic volume increases, so safety issues may be raised. Therefore, the purpose of this study is to perform microscopic traffic analysis on these sections using drone images and to identify the causes of traffic problems. In the case of drone image, since trajectory data of individual vehicles can be obtained, empirical analysis of driving behavior is possible. The analysis section of this study was selected as the weaving section of Pangyo IC and the sag section of Seohae Bridge. First, the trajectory data was extracted through the drone image. And the microscopic traffic analysis performed on the speed, density, acceleration, and lane change through cell-unit analysis using Generalized definition method. This analysis results can be used as a basic study to identify the cause of the problem section in the freeway. Through this, we aim to improve the efficiency and convenience of traffic analysis.