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Norman Thesis.pdf (4.07 MB)
ETD Abstract Container
Abstract Header
A Methodology for Identifying Inconsistencies Between Scheduled and Observed Travel and Transfer Times using Transit AVL data: Framework and Case Study of Columbus, OH
Author Info
Wang, Yuxuan
ORCID® Identifier
http://orcid.org/0000-0002-1512-8846
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1593636407701171
Abstract Details
Year and Degree
2020, Master of City and Regional Planning, Ohio State University, City and Regional Planning.
Abstract
Transit schedules are essential planning tools for many passengers – especially for low-frequency services, transfers, or travel decisions made ahead of the time. This underscores the continued importance of accurate transit schedules to passengers. Agencies, on the other hand, also count on reliable travel times and schedule adherence data for timetable and headway scheduling, as well as operational planning, to provide reliable services to passengers. The objective of this study is to develop a tool to identify potential discrepancies between scheduled and observed mean travel times at a stop to-stop level after removing outliers, and to identify potential inconsistencies between scheduled and observed transfer times at the transfer point level. Demonstrations of the tool’s application are provided using data collected from the Central Ohio Transit Authority (COTA). In the COTA application, the study reveals that for certain route sections, the schedules do not accurately capture the observed temporal variation in mean travel times throughout the day, especially between peak hours and midday. In other cases, spatial patterns are visible in the discrepancies between observed and scheduled travel times, with segments near major intersections tending to have longer than scheduled travel times, which result in further delays. Stop-to-stop level travel time distributions are examined to support scheduling purposes. Several distributions are shown to provide a better fit to observed stop-to-stop travel times than commonly used distributions, namely, the Epsilon skewed normal, Generalised Extreme Value, and mixture normal distributions. Furthermore, this research examines correlations between travel times across stop-to-stop segments to understand the degree to which delays may propagate. The results show that most stop-to-stop travel times can be considered independent from the those of adjacent segments. Higher positive correlations can be observed at areas with lower traffic and passenger activities. In addition, potential driver behaviour changes when running ahead of schedule are pointed out by calculating the conditional travel times given no delays. In a further analysis, discrepancies between scheduled and observed transfer times are examined. Like many other agencies, transfers are not coordinated nor guaranteed by COTA. Overall transfer reliability is examined at the system level, and conditional probabilities of passengers being able to make a connection after a delay on the first bus are derived. It is found that three minutes of scheduled transfer time correspond to an 85% probability of the transfer being successful. If the first bus arrives on or before the transfer bus is scheduled to arrive, there is also an 85% probability of the transfer being successful. A general comparison of observed and scheduled transfer times shows that around 20% of transfer points have shorter than scheduled transfer times and 30% have longer than scheduled transfer times. For the remaining 50% of transfer points, the scheduled transfer times roughly correspond to the observed transfer times. Such analyses allow the agency to inform passengers regarding the risks associated with a planned transfer, and it will allow agencies to assess risks of propagating delays to future trips associated with holding the transfer bus to guarantee transfers.
Committee
Andre Carrel (Advisor)
Zhenhua Chen (Advisor)
Gulsah Akar (Committee Member)
Rabi Mishalani (Committee Member)
Pages
129 p.
Subject Headings
Civil Engineering
;
Transportation
;
Transportation Planning
;
Urban Planning
Keywords
Public Transportation
;
Transit Reliability
;
Travel Time Variability
;
Transfer Time Variability
;
Data Visualization
Recommended Citations
Refworks
EndNote
RIS
Mendeley
Citations
Wang, Y. (2020).
A Methodology for Identifying Inconsistencies Between Scheduled and Observed Travel and Transfer Times using Transit AVL data: Framework and Case Study of Columbus, OH
[Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1593636407701171
APA Style (7th edition)
Wang, Yuxuan.
A Methodology for Identifying Inconsistencies Between Scheduled and Observed Travel and Transfer Times using Transit AVL data: Framework and Case Study of Columbus, OH.
2020. Ohio State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=osu1593636407701171.
MLA Style (8th edition)
Wang, Yuxuan. "A Methodology for Identifying Inconsistencies Between Scheduled and Observed Travel and Transfer Times using Transit AVL data: Framework and Case Study of Columbus, OH." Master's thesis, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1593636407701171
Chicago Manual of Style (17th edition)
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Document number:
osu1593636407701171
Download Count:
228
Copyright Info
© 2020, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.
Release 3.2.12