• Title/Summary/Keyword: macroscopic fundamental diagram

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Deriving Macroscopic Fundamental Diagrams Using Probe Vehicle Data Based on DSRC (DSRC 기반 프로브 자료를 이용한 거시 교통류 모형 추정 방법)

  • Shim, Jisup;Yeo, Jiho;Lee, Sujin;Jang, Kitae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.6
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    • pp.29-41
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    • 2017
  • In this study, we used individual trip data to estimate a macroscopic fundamental diagram (MFD) that relates flow (or production) to density (or state) in Daegu metropolitan city. The individual trip data were generated by processing data that were collected from DSRC-based (dedicated short range communication) traffic data collection system. Using the processed individual trip data, we first examined whether the assumptions for MFD are valid, and then the relation between outflow and accumulation was estimated in our study site. As a result, we found that i) the assumptions are valid to construct MFD; and ii) the reproducible and well-defined MFDs exist in the network level.

A Network Partition Approach for MFD-Based Urban Transportation Network Model

  • Xu, Haitao;Zhang, Weiguo;zhuo, Zuozhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.11
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    • pp.4483-4501
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    • 2020
  • Recent findings identified the scatter and shape of MFD (macroscopic fundamental diagram) is heavily influenced by the spatial distribution of link density in a road network. This implies that the concept of MFD can be utilized to divide a heterogeneous road network with different degrees of congestion into multiple homogeneous subnetworks. Considering the actual traffic data is usually incomplete and inaccurate while most traffic partition algorithms rely on the completeness of the data, we proposed a three-step partitioned algorithm called Iso-MB (Isoperimetric algorithm - Merging - Boundary adjustment) permitting of incompletely input data in this paper. The proposed algorithm was implemented and verified in a simulated urban transportation network. The existence of well-defined MFD in each subnetwork was revealed and discussed and the selection of stop parameter in the isoperimetric algorithm was explained and dissected. The effectiveness of the approach to the missing input data was also demonstrated and elaborated.