Comparing Effective Path Searching Algorithms for Multi-Modal Public Transport Super-Network
This paper compares two effective path searching algorithms, the Kth shortest path algorithm and the depth-first searching algorithm, for a multi-modal public transport super-network. First, a multi-modal public transport super-network model building method based on the super-network modeling approach is proposed. Then, the procedures of the two algorithms are described in detail. Finally, based on a simplified traffic network representing Wuxi, Jiangsu, in China, a case study is carried out. The differences between the two algorithms are analyzed from the aspects of computing time, effective path searching result for single origin-destination (OD) pair, and effective path searching result for all OD pairs. It is concluded that the depth-first searching algorithm is more accurate and efficient when used to search for the effective paths of a multi-modal public transport super-network.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
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Supplemental Notes:
- © 2018 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Wu, Lixia
- Wang, Wei
- Ding, Haoyang
- Fu, Min
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Conference:
- 18th COTA International Conference of Transportation Professionals
- Location: Beijing , China
- Date: 2018-7-5 to 2018-7-8
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 743-754
- Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility
Subject/Index Terms
- TRT Terms: Multimodal transportation; Public transit; Shortest path algorithms
- Geographic Terms: Wuxi (China)
- Subject Areas: Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01868110
- Record Type: Publication
- ISBN: 9780784481523
- Files: TRIS, ASCE
- Created Date: Dec 21 2022 9:16AM