Mode differentiation in partitioning of mixed bi-modal urban networks

Mansour Johari, Shang Jiang, Mehdi Keyvan-Ekbatani, Dong Ngoduy

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)


Empirical studies have demonstrated the existence of a well-defined Network Macroscopic Fundamental Diagram (NMFD). Well-shaped NMFD, however, may not be a universal law because urban networks often display heterogeneous congestion distributions. Therefore, different algorithms have been proposed to partition a heterogeneous network into homogeneous sub-networks. These algorithms mainly consider uni-modal networks, despite the multi-modal nature of urban traffic flows. This paper is one of the first studies dedicated to the partitioning problem of bi-modal networks. First, a three-step partitioning algorithm is developed concerning NMFD-based applications. Second, the role played by mode differentiation in bi-modal network partitioning is investigated through the lens of speed-NMFDs. The results demonstrate that the algorithm performs well. Mode differentiation should be considered in the partitioning process while is defined differently in free-flow and saturated conditions. The links' lengths, bus stop distribution, speed limit zone, and the existence of bus terminals might affect speed-NMFD properties.

Original languageEnglish
Pages (from-to)463-485
Number of pages23
JournalTransportmetrica B
Issue number1
Publication statusPublished - 2023


  • bi-modal urban networks
  • MFD
  • mode differentiation
  • Network partitioning
  • NFD
  • NMFD

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