• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.149-161
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• 2022

Because the speed limit affects moving speed, it is closely related to traffic accidents as well as traffic flow. The existing speed limit calculation methods consider various engineering factors such as lanes, intersection spacing, driveways, crosswalks, 85 percentile speed, land uses, and roadway geometric characteristics etc. However, it can be said that the engineering analysis is insufficient because the traffic impact analysis considering traffic volume is not carried out. In addition, only 85 percentile speed, which is the spot speed, does not reflect the characteristics of the traffic flow on the road. In this paper, the effect of the speed limit change on the moving speed and the travel speed was analyzed in detail accordinr to the variation of intersection spacing and traffic volume. And by using the results, we proposed a speed limit calculation method that maintains the same service level as before the speed limit change, thereby increasing the speed improvement effect and reducing the difference between moving speed and travel speed. In addition, a variable speed limit operation method according to the change in traffic volume was also suggested. This method is expected to be effective in terms of safety by reducing the speed difference, which affects the severity of traffic accidents, while securing the speed improvement effect, and increasing the speed limit compliance rate of drivers by operating the speed limit that reflects the speed change due to the variation of traffic volume.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.1-12
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• 2007

A method for assessing fatigue vulnerability of steel bridge members considering corrosion and truck traffic variation with time is proposed to evaluate the reduction of fatigue strength in steel bridge members. A fatigue limit state function including corrosion and traffic variation effect is established. The interaction between the average corrosion depth and the fatigue strength reduction factor is applied to the limit state function as the reduction term of strength. Three types of truck traffic change is modeled for representing real traffic change trend. Monte-Carlo simulation method is used for reliability analysis which provides the data to obtain fatigue vulnerability curves. The estimation method proposed was verified by comparing with the results of reference study and applying to the steel bridges in service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.55-65
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• 2021

In January 2020, the first COVID-19 confirmed patient occurred in Korea, and the pandemic continues to this day. In unprecedented situations, COVID-19 also affected the transportation sector, and there were no appropriate measures against changes in traffic volume and use of public transportation due to changes in citizens' lifestyles. Currently, each local government has not established separate measures for pandemic disease measures. In order to establish future disease countermeasures in the transportation sector, a predictive model was developed by analyzing the traffic volume and the number of public transportation uses, and conducting correlation analysis with the current status of COVID-19. As a result of the analysis, the traffic volume decreased, but the traffic volume decreased due to the increase in personal transportation, but it did not reach the number of public transportation uses. In addition, it was analyzed that the use of public transportation was initially affected by the number of confirmed cases, but over time, it was more sensitive to death and mortality than to the number of confirmed cases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.371-377
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• 2022

Urban rails and buses are representative public transit systems that not only cooperate with each other, but also compete with each other. In other words, there is a possibility that the overall demand for public transportation may increase due to the introduction of a competitive public transportation system, or there is a possibility that demand will be maintained at the level that is simply converted to a competitive system. The objective of this study is to analyze the change in public transit flow when an additional transit system is introduced in a city with alternative public transit systems. To carry out this objective, we analyzed changes in public transit passenger flow before and after the introduction of an urban rail transit line 3 in Daegu Metropolitan City, where two public transit systems, urban rail and bus, exist. For accurate analysis, big data collected by passenger transportation cards were utilized for one week in the second week of April 2015, 2016, and 2019. From the analysis, it was found that although the urban rail passenger flow increased due to the additional urban rail transit system, the change in the overall public transit passenger flow in the city was insignificant. In other words, it is interpreted that the bus transit passengers have been shifted to the urban transit systems. Based on the results, this study suggested various policies to increase the demand for public transit rather than simply adding public transit systems.

• Journal of Korean Society of Transportation
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• v.19 no.2
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• pp.61-72
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• 2001

기존의 링크교통량으로부터 OD추정모형은 기존 OD에 대한 추정의 종속성이 커, 기존 OD나 관측링크교통량의 오차에 따라 추정결과가 일관적이지 않은 문제점을 가지고 있다. 또한 관측링크교통량의 정확도가 중요함에도 불구하고 차종구분 없이 링크교통량을 이용하여 정보의 손실을 초래하였고 결과적으로 OD 추정력을 저하시켰다. 그렇지만 다차종 링크교통량으로부터 다차종 OD를 구하는 연구는 거의 없었으며, 그 추정결과가 단일차종에 대한 추정결과와 어떻게 다른지에 대한 연구도 전무하였다. 본 연구의 목적은 기존의 OD 추정모형이 기존 OD에 대해 종속성을 가지며 차종구분 없이 모형을 구성함으로써 추정력의 저하를 초래하였음을 밝히고, 이에 대한 대안으로 종속성 문제를 완화하고 차종구분을 통해 OD 추정모형의 추정력을 증진시키자 하는 것이다. 이를 위해 유전알고리즘을 이용한 다차종 OD행렬 추정모형(GAMUC)을 구축하고, 이를 기존의 바이레벨 모형의 IEA 알고리즘 및 다차종으로 확장한 모형(IEAMUC)과 게임이론측면에서 검토하였으며, 사례네트워크에 대해 각 기법을 비교하였다. 본 연구는 유전알고리즘을 이용한 OD 추정기법을 축도로에 적용한 임용택 등(2000)과 이를 네트워크로 확장한 백승걸 등(2000)의 연구를 다차종으로 확장한 것이다. 사례분석 결과 기존 OD의 오차변화나 관측링크교통량의 오차변화 등에 있어 GAMUC가 IEA나 IEAMUC보다 추정력이 양호하여, 실제 OD를 알 수 없는 도시부 네트워크에서 GAMUC 모형의 적용력이 우수하였다. 또한 차종을 구분하지 않은 기존 모형은 실제 OD와는 전혀 다른 OD 구조를 도출할 수 있음을 보였으며, 단일 차종을 여러 차종으로 구분하여 OD를 추정하는 것이 더 양호한 추정력을 확보하는 것으로 나타났다.

• Proceedings of the KOR-KST Conference
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• 1993.07a
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• pp.153-201
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• 1993

한국에 있어서 급속한 경제성장과 사업구조의 변화로 인하여 차량과 교통량이 급속히 증가하였다. 따라서 교통량은 기존 시설물의 용량을 초과하게 되었다. 증가된 교통량과 부족한 교통시설로 인하여 사회.경제전반에 걸쳐서 제 교통문제가 발생하게 되었고, 이러한 교통문제를 해결하기 위해서 과학적인 교통수요예측기법이 요구되었다. 본 논문에서는 과거 20여년간의 교통부문의 연구활동 중 특히, 교통수요예측에 관한 연구에 대해서 사례를 중심으로 살펴 보고자 한다. 논문의 주요내용으로는 아래와 같다. 1) 한국의 교통상황을 개략적으로 설명하고, 한국에서 합리적인 교통 수요예측기법이 필요하게된 배경을 설명 2) 교통수요예측에 필요한 사회.경제변수에 관한 자료를 소개하고, 합리적인 수요예측을 위하여 제 변수의 중요성을 설명 3) 한국에서 과거에 적용한 교통수요예측 모형의 구조와 장.단점을 소개 4) 현재 한국에서 적용하고있는 교통수요예측에 관한 모형의 구호와 적용절차를 본 단계의 과정으로 설명함으로써 그 동안 한국에서의 연구, 적용되어온 교통수요예측 모형에 관한 소개와 적용사례를 제시하고자 한다.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.196-205
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• 1998

교통신호에서 주로 고려되는 변수는 신호주기(cycle length), 녹색시간(green split), 옵셋(offset)그리고 좌회전 현시순서(left-turn phase sequence)로 구성된다. 기존의 대부분의 연동 모델들은 고정된 주기하에서 평균적인 유입 교통량을 측정한 후, 선형최적화 이론을 적용하여 최적 신호를 산출한다. 그러나 이 방법은 어디까지나 평균적인 데이터에 대해서 계산을 한 것이기 때문에 실시간 최적화를 제공하기가 어렵다. 본 연구에서는 평균 차량 통행량 대신 실시간으로 입력되는 차량 대기행렬, 차량 도착률을 기초로 대기차량을 최소화하는 동적 신호시간 산출 모델을 개발하였다. 본 모델에서는 Peytechew가 제안한 각 진입로에서의 대기 차량 예측 모델을 기초로 하여 다음 주기에서의 차량 대기 행렬을 예측한 후, 선형 최적화 이론을 적용하여 신호시간을 산출한다. 본 모델에서 산출된 신호주기와 녹색시간은 대기차량길이를 최소화하는 신호 시간으로서 교차로간의 연동효과를 고려하여 실시산 교통상황에 따라 주기별로 변화한다. 본 모델은 3개의 교차로로 구성된 네트워크를 대상으로 적용하였다. 실험 네트워크의 주도로 교통량은 부도로의 교통량 보다 많다고 가정하였으며 각 링크사이에서의 차량 진출입은 없다고 보았다.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.179-201
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• 2004

Online traffic flow modeling is attracting more attention due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper the flow-density relation is analyzed dynamically and interpreted as a states diagram. The dynamic flow-density relation is quantified by applying fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.61-67
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• 2004

It is needed for one to design the better models estimating emission and then with the real time data, make the monitoring system simulating emission rate because of having built the basement of accepting real-time traffic information in ITS projects. The objective of the study is to develop the monitoring system visualizing air pollution to a certain place. It is based on the estimated emission from the patterns of individual vehicles and the changes of traffic flow. For constructing simulator, we loaded referring algorithm in actuality program and simulates the traffic flow movement in a microscopic viewpoint. The simulator is able to express not only the movement of each car but also to visualize processing the emission and diffusion of the air pollutant by computer program. Not only expresses the simulation process the angle of vision but it also cutting down environment expenses and improving the traffic impact assessment and the traffic impact assessment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.106-118
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• 2020

This study examined the impact of COVID-19 on traffic demand (Average Daily Traffic : ADT) by analyzing the available data on highway traffic volume and the spread of COVID-19 cases in Korea. This study used the data from 228 permanent traffic counts (PTCs) on highways from January to May of 2019 and 2020 to analyze the change in ADT. The first cases of infection in Korea occurred on January 20, 2020, and the maximum daily number of infections was 909 on February 29. On April 30, 2020, the daily number of infections decreased to four. The ADT decreased by 3.3% due to the impact of COVID-19. Considering that the traffic volume has increased 2.3% annually over the past decade, the actual decrease in ADT due to the COVID-19 is estimated to be 5.6% (3.3% + 2.3%). The ADT for weekends decreased significantly, compared to during the week. An analysis of the changes in ADT according to the road type revealed decreases in the following: urban roads -4.6%, rural roads -3.2%, and recreational roads -0.7%. Urban roads decreased the most, and tourist roads decreased the least.