Estimation of Annual Average Daily Traffic on Road Segments: Network Centrality-Based Method for Metropolitan Areas

This paper presents an alternative method to estimate Annual Average Daily Traffic (AADT) volume of road segments in metropolitan areas based on the road network centrality. The proposed method is more rigorous than existing network centrality applications due to two novel features incorporated. First is ‘multiple centrality’, which captures traffic that a road segment attracts as the destination as well as a pass-by, in-between point. Second is ‘weighted link cost’ that integrates ‘road type’ variable with ‘geometric distance’ at the global level and with ‘metric distance’ at local level respectively. Therefore, in addition to the ‘topological distance’, which commonly employ in existing methods, the new method can effectively capture some of the roadway characteristics. The case study that conducted in Colombo Metropolitan Area, Sri Lanka revealed a strong correlation between AADT values and weighted network centrality (WNC) values. Further, the study noted that WNC values have a better relationship with AADT than the centrality values computed without weighting. The study developed a model to estimate AADT by utilizing ‘multiple weighted network centrality values’ as endogenous variables, with a reasonable level of predictability and accuracy (validation R 2= 0.93 and MdAPE =26%). Unlike many of the existing methods for estimating AADT, the proposed method requires neither land-use nor travelers’ O-D trip data, hence, smoothly applicable in data-constrained contexts. Therefore, the study recommends the proposed method as a practical tool for transport planners and engineers, especially who work in developing countries.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Jayasinghe, Amila
    • Sano, Kazushi
  • Conference:
  • Date: 2017

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 18p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01629855
  • Record Type: Publication
  • Report/Paper Numbers: 17-03141
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 27 2017 9:26AM