• Title/Summary/Keyword: 통행시간추정

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Calculation of the Peak-hour Ratio for Road Traffic Volumes using a Hybrid Clustering Technique (혼합군집분석 기법을 이용한 도로 교통량의 첨두율 산정)

  • Kim, Hyung-Joo;Chang, Justin S.
    • Journal of Korean Society of Transportation
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    • v.30 no.1
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    • pp.19-30
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    • 2012
  • The majority of daily travel demands concentrate at particular time-periods, which causes the difficulties in the travel demand analysis and the corresponding benefit estimation. Thus, it is necessary to consider time-specific traffic characteristics to yield more reliable results. Traditionally, na$\ddot{i}$ve, heuristic, and statistical approaches have been applied to address the peak-hour ratio. In this study, a hybrid clustering model which is one of the statistical methods is applied to calculate the peak-hour ratio and its duration. The 2009 national 24-hour traffic data provided by the Korea institute of Construction Technology are used. The analysis is conducted dividing vehicle types into passenger cars and trucks. For the verification for the usefulness of the methodology, the toll collection system data by the Korea Express Corporation are collected. The result of the research shows lower errors during the off-peak hours and night times and increasing error ratios as the travel distance increases. Since the method proposed can reduce the arbitrariness of analysts and can accommodate the statistical significance test, the model could be considered as a more robust and stable methodology. It is hoped that the result of this paper could contribute to the enhancement of the reliability for the travel demand analysis.

Car-sharing in Overseas and Introduction to Korea (Car-sharing의 해외사례 및 국내 도입 효과 추정)

  • Lee, Jae-Yeong;Choe, Gi-Ju;Jeong, U-Hyeon
    • Proceedings of the KOR-KST Conference
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    • 2007.11a
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    • pp.180-187
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    • 2007
  • Car-sharing은 차량소유(Car ownership)의 대안으로서 개인이나 법인에게 차량을 한 시간의 짧은 단위로 이용하도록 하는 회원제 프로그램이다. 이는 차량을 보유하는 편리함 대신에 차량을 공동 이용함으로써 운영비용을 절감할 수 있다. 15년여 전 스위스에서 시작되어 현재는 유럽, 북미, 일본, 싱가포르 등에서 활성화되어 있고, 유럽에서는 대중교통과의 연계서비스까지도 실시하여 그 효과를 증대시키고 있다. 국내에서는 아직 기업의 수익성 사업으로 시도된 사례는 없으나 최근 서울 성산동 주민의 자발적인 참여로 6개 팀이 한 차량을 이용하는 형식으로 시도되어 이제 그 첫걸음을 떼고 있다. 본 논문에서는 Car-sharing에 대한 개념, 정의 및 택시나 렌터카 등 유사수단과의 비교, 그리고 해외에서 현재 운영 중인 Car-sharing 프로그램의 사례를 소개하고, Car-sharing 도입 시 발생하는 개인의 운영비용 절감뿐만이 아닌 차량통행 감소, 주차 수요 감소, 대중교통 이용률 증가, 오염물질 배출 저감, 교통 혼잡 감소 등 많은 종류의 사회적 편익을 국내 도입 시를 가정해 비용과 함께 개략적으로 추정, 편익-비용 분석을 통해 그 경제적인 효과를 검토하였다.

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Estimates of Time-varying Values of Traffic Information on Variable Message Sign (첨두 및 비첨두시 VMS 교통정보의 가치 변화 연구)

  • Rhee, Kyoung-Ah;Lee, Young-Ihn
    • Journal of Korean Society of Transportation
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    • v.30 no.1
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    • pp.135-147
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    • 2012
  • The benefit of traffic information on variable message sign can be divided into two. At the public level, the benefit of ATIS is the travel time saving, which is not only induced from ATIS, but also mixed with that of ATMS. In the economic appraisal of ITS, the benefit of ATIS has so far been regarded as the derived benefit from ATMS. At the user level, the benefit of ATIS is reduced driver uncertainty through the forward traffic status information. User can benefit from the information on VMS and therefore may have the willingness to pay for it. Recently attempt to qualify the value of information on VMS was increased, but there was a danger of distorting or over-estimates of the ATIS benefit because the related studies didn't consider the time-dependent attributes of traffic information and provided the single value. Estimates of the time-varying value should be needed for a rigorous economic appraisal of ATIS. In this study, we varied the value of information on VMS according to peak and non peak trip and verified the hypothesis that time-varying of value was statistically significant.

Study on Location Decisions for Cloud Transportation System Rental Station (이동수요 대응형 클라우드 교통시스템 공유차량 대여소 입지선정)

  • Shin, Min-Seong;Bae, Sang-Hoon
    • Journal of Korean Society of Transportation
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    • v.30 no.2
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    • pp.29-42
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    • 2012
  • Recently, traffic congestion has become serious due to increase of private car usages. Carsharing or other innovative public transportation systems were developed to alleviate traffic congestion and carbon emissions. These measures can make the traffic environment more comfortable, and efficient. Cloud Transportation System (CTS) is a recent carsharing model. User can rent an electronic vehicles with various traffic information through the CTS. In this study, a concept, vision and scenarios of CTS are introduced. And, authors analyzed the location of CTS rental stations and estimated CTS demands. Firstly, we analyze the number of the population, employees, students and traffic volume in study areas. Secondly, the frequency and utilization time are examined. Demand for CTS in each traffic zone was estimated. Lastly, the CTS rental station location is determined based on the analyzed data of the study areas. Evaluation standard of the determined location includes accessibility and density of population. And, the number of vehicles and that of parking zone at the rental station are estimated. The result suggests that Haewoondae Square parking lot would be assigned 11 vehicles and 14.23 parking spaces and that Dongbac parking lot be assigned 7.9 vehicles and 10.29 parking spaces. Further study requires additional real-time data for CTS to increase accuracy of the demand estimation. And network design would be developed for redistribution of vehicles.

The Development of Estimation Technique of Freeway Origin-Destination Demand Using a Real Traffic Data of FTMS (교통관리시스템의 실시간 교통자료를 이용한 고속도로 동적OD 추정기법의 개발)

  • Kim, Ju-Young;Lee, Seung-Jae
    • Journal of Korean Society of Transportation
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    • v.23 no.4 s.82
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    • pp.57-69
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    • 2005
  • The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using real-time traffic data collected from Freeway Traffic Management System (FTMS). In existing research, the micro-simulation models had been used to get a link distribution proportion by time process. Because of hi-level problem between the traffic flow model and the optimal OD solution algorithm, it is difficult for the existing models to be loaded at FTMS. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a genetic algorithm. The proposed methodology is evaluated by using the real-time data of SOHAEAN freeway, South Korea.

Analysis of Pedestrian Evacuation Behaviors by the Evacuation Information Scenarios Using Social Force Model: Focusing on Sejong City (Social Force Model을 활용한 보행자 대피행태 및 정보제공 시나리오분석: 세종시를 중심으로)

  • Choi, Seung hyun;Jung, Ho yong;Do, Myung sik
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.1
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    • pp.31-41
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    • 2018
  • This study aims to analyze region-based pedestrian evacuation behaviors and information offering effect using Social Force Model, which is micro simulation. All pedestrians were assumed to move to shelters through pedestrian roads according to guidance information at emergency situations, and the pedestrians were classified into adults and the handicapped. According to the results of the road network analysis and simulation analysis, the shelters to which pedestrians can move within the shortest time from each zone were selected as optimum shelters. From this study, the analysis showed that the information provision effects are informative even though total evacuation time increases due to the increase of pedestrian conflict. This study can be used as baseline data for urban area's pedestrian disaster prevention plans.

K-factor Prediction in Import and Export Cargo Trucks-Concentrated Expressways by Short-Term VDS Data (단기 VDS자료로 수출입화물트럭이 집중하는 고속도로의 K-factor 추정에 관한 연구)

  • Kim, Tae-Gon;Heo, In-Seok;Jeon, Jae-Hyun
    • Journal of Navigation and Port Research
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    • v.38 no.1
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    • pp.65-71
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    • 2014
  • Gyeongbu and Namhae expressways in the country, are the major arterial highways which are connected with the Busan port in the north-south and east-west directions, respectively, and required to study the traffic characteristics about the hourly volume factors(K-factor) by concentrated midium-size and large-size cargo trucks of 20% or higher in expressways. We therefore attempted to predict the K-factor in expressways through the correlation analysis between K-factor and K-factor estimates on the basis of the short-term VDS data collected at the basic segments of the above major expressways. As a result, power model appeared to be appropriate in predicting K-factor by the K-factor estimate based on VDS data for 7 days with a high explanatory power and validity.

Estimation of Vehicles Evacuation Time by using Lane-based Routing Method (차로기반 경로유도방식을 이용한 차량의 소개시간 추정)

  • Do, Myungsik
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.6
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    • pp.29-36
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    • 2013
  • This study is the fundamental research to establish evacuation planning and to analyze evacuation planning characteristics in Gumi-city based on existing network and traffic characteristics data. Assuming an emergency situation, it compared with evacuation time estimates between using existing traffic signal system and proposed lane-based routing method through micro simulations. As a result, using existing traffic signal system could not affect the evacuation times in each level of emergency conditions. However this study found that proposed lane-based routing method is very effective to reduce an evacuation time compared with using existing traffic signal system. Also the proposed method is verified to reduce an evacuation time especially in extreme emergency circumstances.

A Data Fusion Algorithm for Link Travel Time Estimation (링크 통행시간 추정을 위한 데이터 퓨젼 알고리즘의 개발)

  • 최기수;정연식
    • Journal of Korean Society of Transportation
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    • v.16 no.2
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    • pp.177-195
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    • 1998
  • 지능형교통체계(ITS:Intellegent Transport System)의 구현을 위한 가장 중요한 요소중의 하나는 교통정보의 생성이다. 교통정보의 생성은 루프 검지기, 폐쇄회로(CCTV), probe 차량, 경찰, 통신원 등을 수집된 제보자료들을 분석 및 가공함으로써 이루어진다. 그러나 이들 수집원은 주어진 시간에 있어 모든 네트웍을 통해서 자료가 완전히 수집되어지는 것은 아니다. 즉, 특정 지역에 수집원이 몰려 있는 경우가 있는 반면, 전혀 수집되어지지 않는 지역이 발생할 수도 있다. 이러한 공간적인 불균형적 특성은 동시에 발생한 다량의 자료를 처리하는 기술과 자료가 수집되지 않은 지역에 대한 처리기술을 요하게 된다. 본 논문은 전술한 바와 같은 사항에 대하여 ITS의 진행 단계별로 드러날 수 있는 문제점을 검토하고, 자료통합에 대한 일반적인 개념을 우선 설명한다. 다음에 특정시각에 주어진 자료의 통합을 위해 퍼지선형회귀모형(fuzzy linear regression model)과 데이터 퓨전(data fusion)기법의 내용을 소개하고, 신뢰성있는 단일 교통정보생성을 위한 테이터 퓨전 알고리즘을 제시한다. 또한 제시된 알고리즘을 토대로 가상의 자료를 이용하여 적용가능 봉? 타진해 보았다. 제시되어진 알고리즘은 향후 교통정보 수집환경이 어느 정도 형성된다고 볼 때, 예측치와 실측자료간의 자료검증을 통하여 신뢰도를 가질 경우 보다 광범위하게 사용되어질 수 있을 것으로 판단된다.

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Development of Vehicle Queue Length Estimation Model Using Deep Learning (딥러닝을 활용한 차량대기길이 추정모형 개발)

  • Lee, Yong-Ju;Hwang, Jae-Seong;Kim, Soo-Hee;Lee, Choul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.2
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    • pp.39-57
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    • 2018
  • The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.