01620115

Component

https://doi.org/10.3141/2652-01

Origin–destination matrices provide vital information for service planning, operations planning, and performance measurement of public transportation systems. In recent years, methodological advances have been made in the estimation of origin–destination matrices from disaggregate fare transaction and vehicle location data. Unlike manual origin–destination surveys, these methods provide nearly complete spatial and temporal coverage at minimal marginal cost. Early models inferred destinations on the basis of the proximity of possible destinations to the next origin and disregarded the effect of waiting time, in-vehicle time, and the number of transfers on path choice. The research reported here formulated a dynamic programming model that inferred destinations of public transportation trips on the basis of a generalized disutility minimization objective. The model inferred paths and transfers on multileg journeys and worked on systems that served a mix of gated stations and ungated stops. The model is being used to infer destinations of public transportation trips in Boston, Massachusetts, and is producing better results than could be obtained with earlier models.

01628042

17-02481

English

pp 1–7

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309441933

Digital/other

Figures (4) ; Maps; References (13)

Automatic vehicle location; Dynamic programming; Fares; Methodology; Origin and destination; Public transit

Boston (Massachusetts)

Planning and Forecasting; Public Transportation

PRP, TRIS, TRB, ATRI

Dec 8 2016 10:55AM

• Applications of Inferred Origins, Destinations, and Interchanges in Bus Service Planning
• Constructing Transit Origin–Destination Matrices with Spatial Clustering
• Estimating Fare Noninteraction and Evasion with Disaggregate Fare Transaction Data
• Estimation of Platform Waiting Time Distribution Considering Service Reliability Based on Smart Card Data and Performance Reports
• Exploratory Method for Practitioners Analyzing the Impact of Integrated Fare Structures in Decentralized Metropolitan Regions: A Toronto Region Case Study
• Fare System of Urban Public Transportation Services in Davao City, Philippines
• Investigating Potential Transit Ridership by Fusing Smartcard and Global System for Mobile Communications Data
• Modeling the Impact of Transit Fare Change on Passengers’ Accessibility
• Perceived Reality: Understanding the Relationship Between Customer Perceptions and Operational Characteristics
• Quantile Regression Analysis of Transit Travel Time Reliability with Automatic Vehicle Location and Farecard Data
• Statistical Inference of Transit Passenger Boarding Strategies from Farecard Data
• The Youth Pass: A Study of the Conflicts Between Ideal and Practical Research Design in a Pilot Social Program
• Transit Trip Itinerary Inference with GTFS and Smartphone Data