A Novel Methodology to Assimilate Sub-Path Flows in Bi-Level OD Matrix Estimation Process

Krishna N.S. Behara, Ashish Bhaskar, Edward Chung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)


Traditional bi-level origin-destination (OD) matrix estimation process adjusts the matrix (at the upper level) based on the deviation between the observed and simulated traffic counts. The problem is mathematically under-determined, and the quality of the solution can be enhanced by restricting the upper level search space with information from other sources. This paper presents a methodology that assimilates sub-path flows in the upper level objective function. The contributions of the study are two-fold: first, it proposes the idea of 'structural comparison of sub-path flows' to relax the requirement of 'known' penetration rate of vehicles' trajectories; second, it proposes an innovative upper level formulation where the structural difference between the observed and assigned sub-path flows is integrated with the traditional deviations between the observed and assigned link flows. The sub-path flows can be estimated from advanced data sources such as Bluetooth MAC scanner. The proposed methodology is tested using simulation on a realistic network from Brisbane, Australia and results indicate its practical relevance for situations when the penetration rate of Bluetooth trajectories is generally unknown. The proposed method has a better ability to maintain structural consistency and showed considerable improvements in the quality of OD estimates as compared to the traditional traffic counts-based approach.

Original languageEnglish
Pages (from-to)6931-6941
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number11
Publication statusPublished - 1 Nov 2021
Externally publishedYes


  • bi-level optimization
  • Bluetooth
  • Brisbane
  • gradient descent
  • OD matrix estimation
  • OD structure
  • sub-path flows

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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