Estimating Transit Route OD Flows in the Presence of Multiple Latent Flow Patterns

Route-level Origin-Destination (OD) flow matrices provide useful information for ridership forecasting, service planning and control strategies development. While methods for estimating route-level OD matrices from boarding and alighting counts are based on different assumptions and employ different estimation approaches, they all assume, explicitly or implicitly, that the passenger flow patterns reflect a single underlying probability OD flow matrix. However, across the day and even within a time-of-day (e.g., morning, mid-day, and evening periods), different travelers are engaged in a variety of trip purposes, such as work, personal business, education, and shopping. Such variations within a time-of-day period are becoming even more prevalent with the advent of more complex life and work needs and duties across varying household structures. Therefore, passengers’ travel purposes, which are associated with different sets of origin-destination pairs and departure times within a time-of-day period would be more realistically represented by multiple underlying probability OD flows reflecting the variety of travel purposes. In this study, the computationally efficient variational Bayes method is extended to capture the presence of multiple underlying OD flow matrices. In addition, a data-inspired simulation based evaluation is conducted to assess the value of recognizing multiple underlying probability OD flow matrices. Moreover, a preliminary empirical study is conducted to investigate the potential presence of multiple underlying probability OD flow matrices on an operational bus route.

• Record URL:
  http://www.purdue.edu/discoverypark/nextrans/assets/pdfs/new/168OSUY2.2%20Estimating%20Transit%20Route%20OD%20Flows%20in%20the%20Presence%20of%20Multiple%20Latent%20Flow%20Patterns_Final_Report.pdf
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• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Ohio State University, Columbus

  Department of Civil and Environmental Engineering and Geodetic Science
  Columbus, OH  United States  43016

  NEXTRANS

  Purdue University
  3000 Kent Avenue
  Lafayette, IN  United States  47906-1075

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Mishalani, Rabi G
  • McCord, Mark R
  • Landgraf, Andrew
• Publication Date: 2017-2-13

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 11p

Subject/Index Terms

• TRT Terms: Bayes' theorem; Boarding and alighting; Bus routes; Bus travel; Estimating; Origin and destination; Periods of the day; Simulation; Trip purpose
• Subject Areas: Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01641095
• Record Type: Publication
• Report/Paper Numbers: NEXTRANS Project No. 168OSUY2.2
• Contract Numbers: DTRT12-G-UTC05
• Files: UTC, TRIS, ATRI, USDOT
• Created Date: Jul 17 2017 9:32AM