journal article·2024-09-18Open access

Application of Historical Comprehensive Multimodal Transportation Data for Testing the Commuting Time Paradox: Evidence from the Portland, OR Region

Huajie Yang, Jiali Lin, Jiahao Shi, Xiaobo Ma

Applied Sciences· Volume 14· Issue 18

Abstract

There have been numerous theoretical and empirical transportation studies contesting the stability of commuting time over time. The constant commuting time hypothesis posits that people adjust trip durations, shift across modes, and sort through locations, so that their average commuting time remains within a constant budget. There is a discrepancy between studies applying aggregate analysis and those using disaggregate analysis, and differences in data collection may have contributed to the varying conclusions reported in the literature. This study conducts both aggregate and disaggregate analyses with two travel surveys of the Portland region. We employ descriptive analysis and t-tests to compare the aggregate commuting times of two years and use regression models to explore factors affecting the disaggregate commuting time at the individual trip level to examine whether the stability of the commuting time remains after substantial changes in the transportation and land use systems. Our study indicates that the average commuting time, along with the average commuting distance, increased slightly, as the mode share shifted away from driving during the examined period. The growth in shares of non-driving modes, which are slower than driving, coupled with an increased travel distance, contributed to the small increase in the average commuting time. Our analysis also indicates that the average travel speed improved for transit riders as well as drivers, contradicting earlier research that claims that public transit investment has worsened the congestion in Portland.
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Research context

OpenAlex topics: Urban Transport and Accessibility · Transportation Planning and Optimization · Human Mobility and Location-Based Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Faculty of Innovation and Design, City University of Macau, Macau SAR 999078, China

Department of Civil & Architectural Engineering & Mechanics, University of Arizona, 1209 E 2nd St, Tucson, AZ 85719, USA

Funding

Macau Science and Technology Development Fund

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