Node Centrality Comparison between Bus Line and Passenger Flow Networks in Beijing
Teqi Dai,
Tiantian Ding,
Qingfang Liu () and
Bingxin Liu
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Teqi Dai: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Tiantian Ding: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Qingfang Liu: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Bingxin Liu: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Sustainability, 2022, vol. 14, issue 22, 1-14
Abstract:
In recent decades, complex network theory has become one of the most important approaches for exploring the structure and dynamics of traffic networks. Most studies mainly focus on the static topology features of the traffic networks, and there are also increasing literature focusing on passenger flow networks. However, not much work has been completed on comparing the static networks with dynamic flow networks from the perspective of supply and demand. Therefore, this study aimed to apply the complex network approach to explore the spatial relationship between bus line organization and bus flows in Beijing. Based on the bus route data and the passenger flow data obtained from the Beijing smart bus card, this study investigated the spatial characteristics of the bus line network and the temporal bus flow networks, and presented a comparison analysis on the spatial relationship between them by using the node centrality indices, namely degree centrality, betweenness centrality and closeness centrality. The results show that the overall spatial patterns of node centralities between the bus line network and the bus flow network were similar, while there were also some differences. For weekdays, the correlation between them is higher, as calculated by the degree of centrality. For weekends, the two networks have a greater correlation measured by degree centrality and betweenness centrality. The highest coefficients of correlation between the line network and traffic network appear in the morning peak, which implies that the congestion issues during the morning peak hours might receive the highest priority in Beijing’s bus-line network planning. Our study can provide implications for policymakers to improve the public urban transport network, and thus enhance residents’ happiness.
Keywords: complex network; smart card data; bus transport flows; weighted centrality; sustainable urban development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)
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