Identification of the Node Importance of a Passenger Transport Network in Metropolitan Areas
To identify the node importance of a passenger transport network in metropolitan areas, this study measures the synthetical passenger node importance of cities in three aspects by considering space of flow theory in a social network. First, a framework with eight selected basic features is constructed to identify basic urban attribute indexes by using the traditional node importance method in transport network design. Second, network topology attributes (i.e., aggregation and betweenness degrees) are proposed on the basis of a passenger transport network. Third, an urban linkage model based on the gravity model is developed by considering urban linkage in metropolitan areas. The three aspects are integratively evaluated by using the entire-array-polygon method, and then cluster analysis of the comprehensive node importance of a passenger network is performed using the k-means algorithm. A case study of the Chengdu metropolitan area in Sichuan is conducted, and results verify that the proposed algorithm is reasonable and suitable for identifying the node importance of a passenger transport network in a megalopolis.
- Record URL:
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Supplemental Notes:
- © 2019 American Society of Civil Engineers.
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Authors:
- Mao, Jian-nan
- Liu, Lan
- Kang, Lei-lei
- Publication Date: 2019-9
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 87-95
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Serial:
- Journal of Highway and Transportation Research and Development (English Edition)
- Volume: 13
- Issue Number: 3
- Publisher: Research Institute of Highway, Ministry of Transport
- EISSN: 2095-6215
- Serial URL: http://ascelibrary.org/journal/jhtrcq
Subject/Index Terms
- TRT Terms: Algorithms; Case studies; Cluster analysis; Metropolitan areas; Network links; Network nodes; Networks; Passenger transportation; Traffic flow; Traffic models
- Geographic Terms: Chengdu (China)
- Subject Areas: Highways; Passenger Transportation; Planning and Forecasting;
Filing Info
- Accession Number: 01723692
- Record Type: Publication
- Files: TRIS, ASCE
- Created Date: Nov 26 2019 10:21AM