• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.11-27
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• 2017

The road network system of major domestic urban areas such as city of Seoul was rapidly developed and regionally expanded. In addition, many kinds of life-lines such as electrical cables, telephone cables, water&sewerage lines, heat&cold conduits and gas lines were needed in order for urban residents to live comfortably. Therefore, most of the life-lines were individually buried in underground and individually managed. The utility tunnel is defined as the urban planning facilities for commonly installing life-lines in the National Land Planning Act. Expectation effectiveness of urban utility tunnels is reducing repeated excavation of roads, improvement of urban landscape; road pavement durability; driving performance and traffic flow. It can also be expected that ensuring disaster safety for earthquakes and sinkholes, smart-grind and electric vehicle supply, rapid response to changes in future living environment and etc. Therefore, necessity of urban utility tunnels has recently increased. However, all of the constructed utility tunnels are cut-and-cover tunnels domestically, which is included in development of new-town areas. Since urban areas can not accommodate all buried life-lines, it is necessary to study the feasibility assessment system for utility tunnel by urban patterns and capacity optimization for urban utility tunnels. In this study, we break away from the new-town utility tunnels and suggest a quantitative assessment model based on the evaluation index for urban areas. In addition, we also develop a program that can implement a quantitative evaluation system by subdividing the feasibility assessment system of urban patterns. Ultimately, this study can contribute to be activated the urban utility tunnel.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.282-294
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• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.571-580
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• 2012

Epidemiologic studies of air pollution need accurate exposure assessments at unmonitored locations. A land use regression (LUR) model has been used successfully for predicting traffic-related pollutants, although its application has been limited to Europe, North America, and a few Asian region. Therefore, we modeled traffic-related pollutants by LUR then examined whether LUR models could be constructed using a regulatory monitoring network in Metropolitan area in Korea. We used the annual-mean nitrogen dioxide ($NO_2$) in 2010 in the study area. Geographic variables that are considered to predict traffic-related pollutants were classified into four groups: road type, traffic intensity, land use, and elevation. Using geographical variables, we then constructed a model to predict the monitored levels of $NO_2$. The mean concentration of $NO_2$ was 30.71 ppb (standard deviation of 5.95) respectively. The final regression model for the $NO_2$ concentration included five independent variables. The LUR models resulted in $R^2$ of 0.59. The mean concentration of $NO_2$ of elementary schools was 34.04 ppb (standard deviation of 5.22) respectively. The present study showed that even if we used regulatory monitoring air quality data, we could estimate $NO_2$ moderately well. These analyses confirm the validity of land use regression modeling to assign exposures in epidemiological studies, and these models may be useful tools for assessing health effects of long-term exposure to traffic related pollution.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.37-45
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• 2005

This paper presents a relationship between Nash bargaining game and Wardrop user equilibrium, which has been widely used in transportation modeling for route choice problem. Wardrop user equilibrium assumes that drivers in road network have perfect information on the traffic conditions and they choose their optimal paths without cooperation each other. In this regards, if the bargaining game process is introduced in route choice modeling, we may avoid the strong assumptions to some extent. For such purpose, this paper derives a theorem that Nash bargaining solution is equivalent to Wardrop user equilibrium as the barging process continues and prove it with some numerical examples. The model is formulated based on two-person bargaining game. and n-person game is remained for next work.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1D
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• pp.43-50
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• 2011

The monitoring system for link travel speed using taxi probe is one of key sub-systems of ITS. Link travel speed collected by taxi probe has been widely employed for both monitoring the traffic states of urban road network and providing real-time travel time information. When sample size of taxi probe is small and link travel time is longer than a length of time interval to collect travel speed data, and in turn the missing state is inevitable. Under this missing state, link travel speed data is real-timely not collected. This missing state changes from single to multiple time intervals. Existing single interval prediction techniques can not generate multiple future states. For this reason, it is necessary to replace multiple missing states with the estimations generated by multi-interval prediction method. In this study, a multi-interval prediction method to generate the speed estimations of single and multiple future time step is introduced overcoming the shortcomings of short-term techniques. The model is developed based on Non-Parametric Regression (NPR), and outperformed single-interval prediction methods in terms of prediction accuracy in spite of multi-interval prediction scheme.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.183-193
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• 2007

Traditionally, a congestion charge based on first-best congestion pricing theory, namely, the theory of marginal cost pricing theory, is equal to the difference between marginal social cost and marginal private cost. It is charged on each link so as to derive a user equilibrium flow pattern to a system optimal one. Based on this theory this paper investigates on the characteristics of first-best congestion pricing of multiple user class on road with variable demand, and presents two methods for analysis of social and spatial equity. For these purposes, we study on the characteristics of first-best congestion pricing derived from system optimal in time and in monetary unit, and analyze equity from this congestion pricing with an example network.

• The Journal of Engineering Geology
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• v.4 no.2
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• pp.169-186
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• 1994

A GIS technique was developed for aggregate resources management and transport route analysis. In the study, the management of aggregate resources deals with resources evaluation and control of aggregate supply. The computer system was specially designed for this analysis on the basis of relational database model, and it was named ARIS(Aggregate Resources Information System). A Vector database for this study area of Chungcheong - Do was established for analysis of ARIS. In network analysis, there are many essential elements such as road name, speed limit and width, turns and stops etc. Impedance was also measured for the resistance against transportation of aggregate resources. Actually, the impedances are attributes of arcs, turns and stops. Finally, the feasibility of ARIS was tested to use as a decision making tool of aggregate resources management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.21-36
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• 2015

These days Automated Vehicle(AV) has been receiving attention as a fundamental solution to resolve the various transportation problems and various researches related to the benefits of AV have been done. However, previous researches mainly analyzed the effects in the virtual network. The purpose of this research is to predict and to find out the benefits by introducing the Automated Vehicle to present road traffic system. Thus, the study analyzes the traffic-flow changes of Gyeongbu freeway Seoul-Singal basic section which is planned for setting the test-bed. The results show that Automated Vehicle can have negative effects on the traffic-flow in low volume of LOS A and B. However, the average speed increases and the traffic density decreases in more than LOS C, the traffic volume increase. Therefore, the introduction of Automated Vehicle achieves positive effect on various transportation problems such as the traffic congestion.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.44-54
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• 2019

Recently, image-based object detection has made great progress with the introduction of Convolutional Neural Network (CNN). Many trials such as Region-based CNN, Fast R-CNN, and Faster R-CNN, have been proposed for achieving better performance in object detection. YOLO has showed the best performance under consideration of both accuracy and computational complexity. However, these data-driven detection methods including YOLO have the fundamental problem is that they can not guarantee the good performance without a large number of training database. In this paper, we propose a data sampling method using CycleGAN to solve this problem, which can convert styles while retaining the characteristics of a given input image. We will generate the insufficient data samples for training more robust object detection without efforts of collecting more database. We make extensive experimental results using the day-time and night-time road images and we validate the proposed method can improve the object detection accuracy of the night-time without training night-time object databases, because we converts the day-time training images into the synthesized night-time images and we train the detection model with the real day-time images and the synthesized night-time images.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.107-122
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• 2016

This study aims to develop a framework to estimate mobile source emissions with the macroscopic travel demand model including enhanced estimates of intra-zonal travel emissions using Space Syntax analysis. It is acknowledged that "the land-use and transportation interaction model explains the influence of urban structure on accessibility and mobility pattern". Based upon this theory, the estimation model of intra-zonal travel emissions is presented with the models of total travel distance, total travel demand, and average travel speed of intra-zonal trips. Thess statistical models include several spatial indices derived from the Space Syntax analysis. It explains that urban spatial structure is a critical factor for intra-zonal travel emissions, which is lower in compact zone with smaller portion of land area, lower sprawl indicator, and more grid-type of road network. Also the suggested framework is applied in the evaluation of the effectiveness of bicycle lane project in Suwon, Korea. The estimated emissions including intra-zonal travel is as double as the results only with inter-zonal demands, which shows better performance of the suggested framework for more realistic outcomes. This framework is applicable to the estimation of mobile source emissions in nation-wide and the assessment of transportation-environment policies in regional level.