A Probabilistic Trip Chaining Algorithm for Transit Origin–Destination Matrix Estimation Using Automated Data

Development of an origin-destination demand matrix is crucial for transit planning. The development process is eased with automated data collection, making it possible to mine boarding and alighting patterns on an individual basis. This research proposes a probabilistic method for trip chaining which uses Automatic Fare Collection (AFC) and General Feed Transit Specification (GTFS) data. The proposed method avoids problems resulting from errors in AFC transaction locations or selection of incorrect subroutes from GTFS data which may result in incorrect inference of the origin or destination. The method has been applied to the Twin Cities AFC data as a case study. The transit system is an open system where passengers tap smart cards once while boarding or sometimes alighting (on outbound pay-exit buses). Based on the consecutive tags of the passenger, an algorithm with different capabilities is developed for different cases based on the pay-exit property. The method is compared with a baseline algorithm which shows improvements in the quantity and quality of inferred trips. Finally, the inferred origin-destination demand matrices as well as route ridership are presented visually for planning purposes.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
• Authors:
  • Kumar, Pramesh
  • Khani, Alireza
  • He, Qing
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: References;
• Pagination: 7p

Subject/Index Terms

• TRT Terms: Algorithms; Automatic fare collection; Data collection; Origin and destination; Public transit; Smart cards; Traffic estimation; Transportation planning; Trip chaining
• Identifier Terms: General Transit Feed Specification
• Geographic Terms: Twin Cities Metropolitan Area (Minnesota)
• Subject Areas: Data and Information Technology; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01661384
• Record Type: Publication
• Report/Paper Numbers: 18-05342
• Files: TRIS, TRB, ATRI
• Created Date: Feb 27 2018 9:45AM