A double time-scale passenger assignment model for high-speed railway networks with continuum capacity approximation. (June 2021)
- Record Type:
- Journal Article
- Title:
- A double time-scale passenger assignment model for high-speed railway networks with continuum capacity approximation. (June 2021)
- Main Title:
- A double time-scale passenger assignment model for high-speed railway networks with continuum capacity approximation
- Authors:
- Xu, Guangming
Liu, Wei
Wu, Runfa
Yang, Hai - Abstract:
- Highlights: This study predicts the time-and-space-dependent flow for high-speed rail network. The passenger flow pattern is ticket-booking-time-dependent. An algorithm is designed for solving the passenger flow assignment model. The model and algorithm are applied on the large-scale rail network of China. Abstract: This study models spatiotemporal passenger flow distribution for high-speed railway (HSR) networks with capacity constraints. The HSR travel demand involves two time-dimensions, i.e., the ticket booking time and the desired departure time. Under the principle of first-booked-first-served, a passenger flow assignment model is formulated, where a later ticket booking time may result in less available travel options. A solution algorithm is then designed for solving the ticket-booking-time-dependent assignment model. The model is tested and illustrated with two numerical examples: a toy network example and a large-scale Chinese HSR network example.
- Is Part Of:
- Transportation research. Volume 150(2021)
- Journal:
- Transportation research
- Issue:
- Volume 150(2021)
- Issue Display:
- Volume 150, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 150
- Issue:
- 2021
- Issue Sort Value:
- 2021-0150-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-06
- Subjects:
- High-speed railway -- Capacity constraint -- Ticket booking time -- Desired departure time -- Continuum capacity approximation
Logistics -- Periodicals
Transportation -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13665545 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tre.2021.102305 ↗
- Languages:
- English
- ISSNs:
- 1366-5545
- Deposit Type:
- Legaldeposit
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- British Library DSC - 9026.274640
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