Crowdsourced Insights: Shaping Origin–Destination Matrix Estimation Utilizing Transportation Data on Demand
Publication: Journal of Urban Planning and Development
Volume 151, Issue 1
Abstract
In transportation system modeling, the origin–destination matrix estimation (ODME) is a critical facet that relies on traffic assignment. Extracting origin–destination (O–D) demand matrices from regional travel demand models for subnetworks is common; however, challenges persist in their quality, particularly for dynamic traffic assignment and simulation modeling. The ODME procedures have emerged to estimate O–D demands using a seed matrix and real-world measures, often segment volume counts. Recently, the availability of O–D demand data from private sector vendors has been witnessed, sourced from crowdsourced and automated vehicle identification (AVI) technologies. This paper explores the integration of crowdsourced data, segment-level measures, and demand forecasting model outputs in O–D demand estimation, which compares 12 ODME variations that employ different input variable combinations and weights. This paper aims to enhance the guidance and methodologies for analysts who utilize diverse data sources in O–D demand estimation.
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Data Availability Statement
Some or all data, models, or codes used during the study were provided by a third party. Direct requests for these materials may be made to the provider (SL).
Acknowledgments
The work presented in this paper is part of a research project funded by the Florida Department of Transportation. The opinions, findings, and conclusions that are expressed in this paper are those of the author(s) and not necessarily those of the Florida Department of Transportation or the US Department of Transportation.
Author contributions: The authors confirm their contribution to the paper as follows: study conception and design by Syed Ahnaf Morshed, Kamar Amine, and Mohammed Hadi; data collection by Syed Ahnaf Morshed and Kamar Amine; analysis and interpretation of results by Syed Ahnaf Morshed, Kamar Amine, and Mohammed Hadi; draft manuscript preparation by Syed Ahnaf Morshed, Kamar Amine, and Mohammed Hadi. All authors reviewed the results and approved the final version of the manuscript.
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Published In
Journal of Urban Planning and Development
Volume 151 • Issue 1 • March 2025
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Dec 3, 2023
Accepted: Aug 2, 2024
Published online: Oct 18, 2024
Published in print: Mar 1, 2025
Discussion open until: Mar 18, 2025
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