TY - GEN
T1 - Exploring the Complexity of Urban Bus Network, a Perspective from the Bus Frequency Data
AU - Ma, Ke
AU - Qiu, Zhenyang
AU - Hu, Xiaowei
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - The topology and properties of public transport networks (PTNs) are an important focus of public transportation planning, but the bus frequency data is rarely considered in the study of PTN. This paper builds bus stop network and bus transit network with a new perspective: time-varying bus lines’ frequency. Based on these two types of network model, we investigate Nanjing PTN, analyzing the static topological properties and time-varying characteristics of it. Both networks, especially bus stop network, are small-world networks. The weighted bus stop network has 1581 nodes and 2355 edges. The weighted bus transit network has 50352 edges, which shows that the average transfer time of Nanjing PTN is 1.9. This network also reveals that although the average waiting time varies by 8.9 min at the most, the travel plan of passengers at different times does not change significantly. 92% of the nodes have no significant change in the betweenness centrality at different times. We take bus frequency into the consideration of evaluation and optimization of PTN, and it is exemplified that the bus frequency data plays an important role in it.
AB - The topology and properties of public transport networks (PTNs) are an important focus of public transportation planning, but the bus frequency data is rarely considered in the study of PTN. This paper builds bus stop network and bus transit network with a new perspective: time-varying bus lines’ frequency. Based on these two types of network model, we investigate Nanjing PTN, analyzing the static topological properties and time-varying characteristics of it. Both networks, especially bus stop network, are small-world networks. The weighted bus stop network has 1581 nodes and 2355 edges. The weighted bus transit network has 50352 edges, which shows that the average transfer time of Nanjing PTN is 1.9. This network also reveals that although the average waiting time varies by 8.9 min at the most, the travel plan of passengers at different times does not change significantly. 92% of the nodes have no significant change in the betweenness centrality at different times. We take bus frequency into the consideration of evaluation and optimization of PTN, and it is exemplified that the bus frequency data plays an important role in it.
KW - Bus frequency
KW - Public transport network
KW - Topological analysis
KW - Weighted complex network analysis
UR - https://www.scopus.com/pages/publications/85131946446
U2 - 10.1007/978-981-19-2259-6_7
DO - 10.1007/978-981-19-2259-6_7
M3 - 会议稿件
AN - SCOPUS:85131946446
SN - 9789811922589
T3 - Lecture Notes in Electrical Engineering
SP - 72
EP - 85
BT - 2021 6th International Conference on Intelligent Transportation Engineering, ICITE 2021
A2 - Zhang, Zhenyuan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Intelligent Transportation Engineering, ICITE 2021
Y2 - 29 October 2021 through 31 October 2021
ER -