• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.5
• /
• pp.779-797
• /
• 2017

Recently, underground road construction is attracting attention because the ground transportation facilities in the urban area have reached the saturation level and traffic volume has increased and the air pollution has risen. Construction of underground roads is not only reduce trafficjam in downtown but also design the city eco-friendly, so existing roads as well as new roads go underground. It is essential to construct divergence tunnels that serve as IC (interchage) and JC (Junction) when constructing underpasses. Therefore, the analysis of the effect of the existing tunnel by the divergence tunnel should be considered. In this study, numerical analysis is performed to analyze the effect of existing tunnel on the excavation of the divergence tunnel. The divergence tunnels were set in 5 cases at $45^{\circ}$ intervals in the clockwise direction starting from the lower part of the existing tunnel. In each case, numerical analyses were carried out by using the DCM (Displacement Controlled Model) for applying the volume loss of 0.5%, 1.0% and 1.5%. As a result, when the volume loss increased, the effect on displacement, fracture range, and effect on stability increased as well. In addition, it was confirmed that the divergence tunnel located directly underneath is the weakest for the stability, and the case where the divergence tunnel is located diagonally rather than the vertical and horizontal direction is found to be vulnerable to displacement and lining destruction.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.109-122
• /
• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Korean Society of Transportation
• /
• v.22 no.4 s.75
• /
• pp.43-56
• /
• 2004

The KHCM procedure is a micro level analysis at signalized intersections requiring a lot of input variables and complex computations. The research was to investigate the possibility of simplifying the analysis procedures by using the generalized or the combined variables that less influence on the adjusted traffic volume and through-car equivalents of left or right turns. It was also tried to make lane grouping into directional flow ratio(v/s) based on a field surveys. The maximum and minimum values of each variables were compared with each other through the KHCM analysis procedures in terms of control delay. The lane grouping and the synthetical influence of a simplified method was evaluated with the scenario built in prevailing maximum and minimum conditions. The study showed that the control delay was not significantly sensitive to the selected variables and the lane grouping and their synthetical influence as well.

• International Journal of Highway Engineering
• /
• v.14 no.6
• /
• pp.131-138
• /
• 2012

PURPOSES : Two-lane highways have one lane in each direction, and lane changing and passing maneuvers take place in the opposing lane depending on the availability of passing sight distance. 2001 Korea Highway Capacity Manual (KHCM) is classified into two classes of two-lane highways (Type I, II), and average travel speed and time-delayed rate are used as measures of effectiveness (MOEs). However, since existing two-lane highways have both uninterrupted and interrupted traffic flow-system elements, a variety of free-flow speeds exhibits in two-lane highways. In addition, it is necessary to check if the linear-relationship between volumes and time-delayed rate is appropriate. Then, this study is to reestablish the relationship between average travel speed, time-delayed rate, and flow. METHODS : TWOPAS model was selected to conduct this study, and the free-flow speeds of passenger cars and the percentage of following vehicles observed in two-lane highways were applied to the model as the input. The revised relationships were developed from the computer simulation. RESULTS : In the revised average travel speed vs. flow relationship, the free-flow speed of 90km/h and 70km/h were added. It shows that the relationship between time delayed-rate and flow appeared to be appropriate with the log-function form and that there was no difference in time-delayed rate between the free flow speeds. In addition to revise the relationships, the speed prediction model and the time-delayed rate prediction model were also developed. CONCLUSIONS : The revised relationships between average travel speed, time-delayed rate, and flow would be useful in estimating the Level of Service(LOS) of a two-lane highway.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.6
• /
• pp.54-63
• /
• 2014

Traffic accident frequency and severity level in Korea are known to be very serious. Especially the number of pedestrian fatalities was much worse and 1.6 time higher than the OECD average. According to the National Police Agency, the flash signals are reported to have many safety benefits as well as travel time reduction, which is opposed to the foreign studies. With this background of expanding the flash signal, this research aims to investigate the overall impact of the flash signal operation on safety, investigating and comparing the accident occurrence on the flash signal and the full signal intersections. For doing this accident prediction models for both flash and full signal intersections were estimated using independent variables (geometric features and traffic volume) and 3-year (2011-2013) accident data collected in Seoul. Considering the rare and random nature of accident occurrence and overdispersion (variance > mean) of the data, the negative binomial regression model was applied. As a result, installing wider crosswalk and increasing the number of pedestrian push buttons seemed to increase the safety of the flash signal intersections. In addition, the result showed that the average accident occurrence at the flash signal intersections was higher than at the full signal-operated intersections, 9% higher with everything else the same.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.1
• /
• pp.35-42
• /
• 2010

The rapid economic development induced the massive road constructions, becoming bigger and high-speed of the vehicles. However, it brings lots of social problems, such as air pollutions, traffic noise and vibration. Special concrete block for the base course of asphalt pavement is needed to decrease traffic noise such as tire's explosive and vehicles sound, applying Helmholtz Resonators theory to asphalt pavement. If it is applied to the area where it happens considerable noise such as a junction, the street of a housing complex and a residential street, it is one of considerable method to solve the social requirements of noise problem. This research examines couple of laboratory tests for the sound absorption effect of the concrete block and the base concrete block. There are specimens which is fixed hall-size, space, depth as the condition of this research, and these are analysed of noise decrease effect using different condition of the first noise of each vehicle. As a result of analysis data according to vehicle noise volume, measurement distance, a form and size of the hall using the base concrete block, the use of special concrete base showed a good alternative solution for decreasing traffic noise level, from 4 dB to 9 dB.

• Journal of Korean Society of Transportation
• /
• v.29 no.5
• /
• pp.55-65
• /
• 2011

In effort to estimate sustainability of the transportation sector, this study conducts a comparative analysis of methodology suggested for measuring greenhouse gas emission. There are two approaches proposed by the UN IPCC: 1) top-down approach (TDA) based on the amount oil sales, and 2) bottom-up approach (BUA) utilizing the velocity of moving source and traffic volume data. The subject areas for analysis were selected based on research results by the Korea Transportation Institute that evaluate traffic sustainability of each local government. Gwacheon-si being one of the top ranked areas in sustainability, and Anseong-si being ranked at the 7th level were analyzed. By the tier 1 methodology, Gwacheon-si and Anseong-si are estimated to create 74,813ton/yr, and 584,125ton/yr of the greenhouse gas emission, respectively. The tier 3 methodology, however, estimates Gwacheon-si and Anseong-si to create 91,462ton/yr, and 163,801ton/yr of the emission, respectively. Comparison of the two estimated emissions shows considerable differences; i.e., the tier 3 method over estimates Gwacheon-si's emission by 22.3% whereas it underestimates Anseong-si's greenhouse gas emission by the factor of about 3.5 compared to the emissions obtained from the tier 1 method. The result from this study implies that the traffic-sustainability-index based grade of each local government can be evaluated differently by the method adopted for measuring greenhouse gas emission.

• Journal of Korean Society of Transportation
• /
• v.29 no.1
• /
• pp.17-27
• /
• 2011

This paper investigates some critical errors influencing travel demand estimation in Korea Transportation Data Base (KTDB), and through this investigation reasonable traffic analysis zone (TAZ) size and internal trips ratio are analyzed. With varying zone size, the accuracy of travel demand estimation is studied and appropriate level of zone size in KTDB is also presented. For this purpose zonal structure consisting of location of zone centroid, number of centroid connecters has been constructed by social economic index, and then some descriptive statistical analyses such as F-test, coefficient of correlation are performed. From the results, this paper shows that the optimum levels of zone system were various according to the order and capacity of roads, and also shows that the smaller TAZ, the less error in this research. In conclusion, in order to improve accuracy of traffic demand estimation it is necessary to make zone size smaller.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.76-91
• /
• 2017

The Area of a domestic railway station is designed based on the 4-step traffic demand forecasting model with the average daily passenger count as one of its parameter. However, nowadays, due to increasing rate of railway station's function, the non-passengers are increasing. In order to consider those non-passengers who aren't using trains, assumed volume are added to the average daily passenger count of station to estimate the area, but the criteria being applied has no concrete basis. Therefore, this study aimed to recalculate the increasing non-passenger rate based on actual survey data of station users in any type of railway station to obtain the optimum area. Subsequently, the the design area was performed through pedestrian simulation. According to the result of the simulation, it was found that the total space of the exciting railway stations can be reduced up to 45% and will still satisfy the level of service(LOS) requirement.

• Journal of Korean Society of Transportation
• /
• v.34 no.5
• /
• pp.377-393
• /
• 2016

Vehicle emissions have been known as a critical factor to give a negative impact on the public health. In particular, particulate matters(PM) and NOx are highly related with respiratory diseases such as asthma. This study aimed at analyzing spatio-temporal patterns of PM and NOx generated from urban freeway traffic. MOVES, which is a well-known emission analysis tool presented by US Environmental Protection Agency(EPA), was applied to estimate PM and NOx based on traffic volume and speed data obtained from Seoul Outer Ring Expressway during January~June, 2012. K-means clustering analysis was used for categorizing the Level of Vehicle Emissions(LOVE) to support more systematical identification of the significance of emissions. Then, spatio-temporal analyses of estimated emissions were conducted by LOVE. Finally, this study proposed a set of strategies to reduce both PM and NOx to enhance public health based on analysis results.