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Massachusetts Institute of Technology

Utilizing automatically collected smart card data to enhance travel demand surveys

Abstract

dc:description.abstract

Public transport agencies have used manual surveys to collect demographic and travel diary information in order to understand their customers' travel behavior for many years. Recently many agencies have also begun to use automated sources of data from fare collection, vehicle location, and passenger counting systems to improve the understanding of their customers' detailed geographic and temporal travel behavior as well as frequency of usage, and travel pattern variation at a much larger scale than is possible with manually collected survey data. Transport for London (TfL), the public body responsible for all transportation services in London, was chosen as a case study to determine how and to what extent automatic fare card (Oyster) data can be used to enhance and validate the London Travel Demand Survey (LTDS) single day travel diary responses. This thesis found that combining survey responses with linked Oyster data for specific households could greatly enhance the validity of the single travel day and improve the understanding of the variability of weekly public transport (PT) use. However, it was difficult to match the survey diary responses and Oyster card records after the interview had taken place. This was evidenced by the fact that only 51.1% of Oyster journey stages had matching survey journey stages, only 45.6% of survey stages had matching Oyster stages, and only 44% of the sample had perfectly matching survey and Oyster stages. Even when there were matches, there were large differences in many journey start times and durations with an average start time difference of 61.2 minutes. This suggests that it would be advantageous to integrate the Oyster records earlier in the survey process, using some type of prompted recall methods with Oyster records in the near term, and new location tracking smart phone applications in the future. Analysis of the weekly variation in PT travel found that the single day survey overestimates typical PT use overall, but it underestimates the intensity of PT use on days when the survey sample chose to use the PT mode. Additionally, the reported frequency of PT use in the LTDS was significantly higher than the actual use as captured by the Oyster system, and therefore the LTDS is generally overestimating the PT use overall for London residents.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Riegel, Laura K. (Laura Kathleen)
Advisor dc:contributor.advisor
  • John P. Attanucci and Mikel E. Murga.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/82850
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/82850

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Riegel, Laura K. (Laura Kathleen). Utilizing automatically collected smart card data to enhance travel demand surveys. Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82850