Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai, China
As the propensity to link multiple intermediate stops in a trip chain (a sequence of journeys that starts and ends at home, includes visiting one or more locations) is more prevalent, the relationship between travel mode choice and trip chain pattern aroused the attention of academics. This paper examines two distinct structures to identify the decision process of travelers between travel mode choice and trip chain pattern: one structure in which trip chain pattern organization precedes travel mode choice, another structure in which travel mode choice decision precedes the organization of trip chain pattern. To accommodate multi-day behavioral variability and unobserved heterogeneity in personal characteristics ignored by traditional travel surveys, multi-day Global Positioning System (GPS) data collected in Shanghai is employed to estimate these two structures within Nested Logit (NL) model. The Monte Carlo (MC) method simulates the switch of trip-chaining and mode choice under possible Transportation Demand Management (TDM) strategies based on estimation results. The findings of this study are as follows: (1) trip chain pattern decision precedes travel mode choice, which means trip-chaining is organized first and affects travel mode choice; (2) complex trip chain is related to higher automobile dependency, and it is a barrier to the tendency to adopt public transit; (3) people who generally travel by automobiles might switch to public transit when private cars are unavailable, and an increase in household bicycle ownership enhances competition between the bicycle and public transit which leads people to turn to cycling. These findings help implement TDM strategies to develop sustainable transportation systems and optimize the urban trip structure.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/09666923
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Supplemental Notes:
- © 2021 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Huang, Yuqiao
- Gao, Linjie
- Ni, Anning
- Liu, Xiaoning
- Publication Date: 2021-5
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
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Serial:
- Journal of Transport Geography
- Volume: 93
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0966-6923
- Serial URL: http://www.elsevier.com/locate/jtrangeo
Subject/Index Terms
- TRT Terms: Case studies; Global Positioning System; Logits; Mode choice; Monte Carlo method; Travel demand management; Trip chaining
- Geographic Terms: Shanghai (China)
- Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01774120
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 14 2021 9:53AM