High Spatiotemporal Passenger-Centric Transit Performance Measures using Archived GTFS-Real Time Data

Unreliable public transportation is a barrier to reaching employment, education, and other community lifeline services. Most transit agencies provide a measure of on-time performance as the percentage of time that a bus arrives within a predefined on-time window to a stop. However, automatic vehicle location (AVL) and automatic passenger count (APC) technologies enable higher resolutions performance metrics to be developed. Using archived General Transit Feed Specification (GTFS)-real-time data, this project proposes high spatiotemporal resolution, passenger-centric on-time performance measures for MTA Maryland serving the Baltimore metropolitan area. Metrics include disaggregate on-time performance, reoccurring vs non-reoccurring delay, schedule and headway adherence, and the degree of schedule adherence. These metrics will be weighted by ridership and displayed on a publicly available web-based dashboard. The approach outlined in the project may be generalized to any transit agency that utilizes APC and AVL technology.

Language

• English

Project

• Status: Active
• Funding: $101570
• Contract Numbers:

  CMMM-MSUCC-2023-C0007

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Morgan State University

  1700 E. Cold Spring Lane
  Baltimore, MD 21251, Maryland  United States  21251
• Project Managers:

  Chavis, Celeste

• Performing Organizations:

  Morgan State University

  School of Engineering
  Cold Spring Lane and Hillen Road
  Baltimore, MD  United States  21239
• Principal Investigators:

  Chavis, Celeste

• Start Date: 20231101
• Expected Completion Date: 20241031
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Automatic vehicle location; On time performance; Passenger counting; Performance measurement; Public transit; Real time information
• Identifier Terms: General Transit Feed Specification (GTFS); Maryland Transit Administration
• Geographic Terms: Baltimore Metropolitan Area
• Subject Areas: Data and Information Technology; Passenger Transportation; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01909260
• Record Type: Research project
• Source Agency: Center for Multi-Modal Mobility in Urban, Rural, and Tribal Areas (CMMM)
• Contract Numbers: CMMM-MSUCC-2023-C0007
• Files: UTC, RIP
• Created Date: Feb 22 2024 4:04PM