• Title/Summary/Keyword: Outflow Traffic Volume

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Analysis of Diversion Rate using Expressway Traffic Data(FTMS, TCS): Focusing on Maesong~Balan IC at Seohaean Expressway (고속도로 교통데이터(FTMS, TCS)를 이용한 경로전환율 분석: 서해안고속도로 매송~발안 구간을 중심으로)

  • Ko, Han-Geom;Choi, Yoon-Hyuk;Oh, Young-Tae;Choi, Kee-Choo
    • Journal of Korean Society of Transportation
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    • v.30 no.3
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    • pp.31-41
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    • 2012
  • Due to growing interests in the distribution of traffic volume through information dissemination such as VMS and traffic broadcasting system, the research on the driver's reaction and effect of the traffic report has continued. In this study, we propose a methodology, which estimates the traffic volume of diversion and the consequential diversion rate using FTMS data and TCS data, and the estimation is based on the analysis of the national highway and IC, in which real-time FTMS and TCS data are established. We also calculate the diversion rate of actual targeted sections and analyze the changes in time and spatial diversion rate. In this study, we define a deviation (considering a deviation due to dynamic properties of traffic conditions) found when the outflow traffic volume is temporarily higher than the average outflow traffic volume on a relevant time slot after providing traffic information. The diverting volume is considered to be caused by the traffic information, and the study determines the ratio of traffic volume on highways to that of route diversion as the diversion rate. The analysis on changes in the diversion rate in accordance with the time flow, the initial change in the diversion rate on upstream IC that first acquires the report on the traffic congestion is significant. After that, the change in the diversion rate on upstream IC affects the route diversion on downstream IC with spatial and time flow, and this again leads the change in upstream IC. Thereby, we confirmed that there is a feedback-control circulation system in the route diversion.

The Effect of Traffic Conditions on Office Rent (The Case of CBD, Kangnam and Yoido) (지역교통여건이 오피스 임대료에 미치는 영향 (도심, 강남, 여의도 지역을 중심으로))

  • Jung, Chang-Mu;Kim, Si-Baek
    • Journal of Korean Society of Transportation
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    • v.26 no.6
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    • pp.29-38
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    • 2008
  • In Seoul, the volume of office market has been expanding rapidly and the currency will be maintained. Many researches have looked at determinants of the office rent, we still cannot have adequate and accurate information of the impacts of traffic congestions around office buildings on the office rents. To gauge the effect of traffic conditions surrounding an office building on the office rent, a hedonic price model was estimated. The regression analysis estimates the values or implicit prices of the individual rent determinants; these parameters in turn allow for a detailed examination of the variables that impact office rents. The result shows that traffic conditions of office buildings play an important role in determining the office rental rate. Since a number of adjacent streets provided excellent opportunities to connect with the neighborhood, it pulls up the rental rate. Similarly, traffic congestions depreciates the value of an office buildings restricting the accessibility to the office building. We also provide evidence of the existence of spatial submarkets and find that market takes different spatial forms depending on the local context.

Development of a Freeway Travel Time Estimating and Forecasting Model using Traffic Volume (차량검지기 교통량 데이터를 이용한 고속도로 통행시간 추정 및 예측모형 개발에 관한 연구)

  • 오세창;김명하;백용현
    • Journal of Korean Society of Transportation
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    • v.21 no.5
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    • pp.83-95
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    • 2003
  • This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.