Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China

In the bus network, key bus station failure can interrupt transfer lines, which leads to the low effectiveness of the whole network, especially during peak hours. Thus, identifying key stations in the bus network before the emergency occurs has a great significance to improve the response speed. In...

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Main Authors: Jia, Jianlin, Chen, Yanyan, Chen, Ning, Yao, Hui, Li, Yongxing, Liu, Zhuo
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/146035
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1460352021-01-21T08:45:35Z Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China Jia, Jianlin Chen, Yanyan Chen, Ning Yao, Hui Li, Yongxing Liu, Zhuo School of Civil and Environmental Engineering Engineering::Civil engineering Transportation Networks Passenger Flow In the bus network, key bus station failure can interrupt transfer lines, which leads to the low effectiveness of the whole network, especially during peak hours. Thus, identifying key stations in the bus network before the emergency occurs has a great significance to improve the response speed. In this paper, we proposed a new method considering station hybrid influence and passenger flow to identify key stations in the whole bus network. This method aims to measure the influence of bus stations while combining the topological structure of the bus network and dynamic bus stations passenger flow. The influence of bus stations was calculated based on the local structure of the network, which refines from finding the shortest paths with high computational complexity. To evaluate the performance of the method, we used the efficiency of the network and vehicle average speed at the station to examine the accuracy. The results show that the new method can rank the influence of bus stations more accurately and more efficiently than other complex network methods such as degree, H-index, and betweenness. On this basis, the key stations of the bus network of Beijing in China are identified out and the distribution characteristics of the key bus stations are analyzed. Published version 2021-01-21T08:45:35Z 2021-01-21T08:45:35Z 2020 Journal Article Jia, J., Chen, Y., Chen, N., Yao, H., Li, Y., & Liu, Z. (2020). Identifying Key Bus Stations Based on Complex Network Theory considering the Hybrid Influence and Passenger Flow: A Case Study of Beijing, China. Advances in Civil Engineering, 2020, 8824797-. doi:10.1155/2020/8824797 1687-8086 0000-0002-4033-1934 0000-0002-7068-4669 0000-0002-3786-8730 https://hdl.handle.net/10356/146035 10.1155/2020/8824797 2-s2.0-85098505924 2020 en Advances in Civil Engineering © 2020 Jianlin Jia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Civil engineering
Transportation Networks
Passenger Flow
spellingShingle Engineering::Civil engineering
Transportation Networks
Passenger Flow
Jia, Jianlin
Chen, Yanyan
Chen, Ning
Yao, Hui
Li, Yongxing
Liu, Zhuo
Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China
description In the bus network, key bus station failure can interrupt transfer lines, which leads to the low effectiveness of the whole network, especially during peak hours. Thus, identifying key stations in the bus network before the emergency occurs has a great significance to improve the response speed. In this paper, we proposed a new method considering station hybrid influence and passenger flow to identify key stations in the whole bus network. This method aims to measure the influence of bus stations while combining the topological structure of the bus network and dynamic bus stations passenger flow. The influence of bus stations was calculated based on the local structure of the network, which refines from finding the shortest paths with high computational complexity. To evaluate the performance of the method, we used the efficiency of the network and vehicle average speed at the station to examine the accuracy. The results show that the new method can rank the influence of bus stations more accurately and more efficiently than other complex network methods such as degree, H-index, and betweenness. On this basis, the key stations of the bus network of Beijing in China are identified out and the distribution characteristics of the key bus stations are analyzed.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Jia, Jianlin
Chen, Yanyan
Chen, Ning
Yao, Hui
Li, Yongxing
Liu, Zhuo
format Article
author Jia, Jianlin
Chen, Yanyan
Chen, Ning
Yao, Hui
Li, Yongxing
Liu, Zhuo
author_sort Jia, Jianlin
title Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China
title_short Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China
title_full Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China
title_fullStr Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China
title_full_unstemmed Identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of Beijing, China
title_sort identifying key bus stations based on complex network theory considering the hybrid influence and passenger flow : a case study of beijing, china
publishDate 2021
url https://hdl.handle.net/10356/146035
_version_ 1690658409968304128