TY - GEN
T1 - Characteristic Analysis of the High-speed Railway Network
T2 - 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021
AU - Yang, Mingkun
AU - Wu, Xingtang
AU - Wang, Hongwei
AU - Lu, Jinhu
AU - Dong, Hairong
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/9/19
Y1 - 2021/9/19
N2 - High-Speed Railway(HSR), due to its advantages of high-velocity, large capacity, punctuality, et al., developed rapidly in recent years, forming a networked operation scale. The connectivity status for different Origin-Destination(OD) pairs varied with time according to train timetables. To reveal the dynamic characteristics of the HSR network resulted from the changing connection status of OD pairs, this paper proposed an HSR Spatio-temporal Network(SN) model to analyze the dynamic characteristics of the HSR network. Then the spatiotemporal characteristic path length and the spatio-temporal betweenness centrality are studied by transforming the SN network into a Spatio-temporal Nodes based Network(SNN). Moreover, an indicator named spatio-temporal connectivity is proposed to derive the connectivity status variation of the HSR. Cases study reveal the quantitative relationship between the train timetable and the transportation performance and the evolution law of the network characteristics. The results could be used further to optimize the organization of trains from a network perspective.
AB - High-Speed Railway(HSR), due to its advantages of high-velocity, large capacity, punctuality, et al., developed rapidly in recent years, forming a networked operation scale. The connectivity status for different Origin-Destination(OD) pairs varied with time according to train timetables. To reveal the dynamic characteristics of the HSR network resulted from the changing connection status of OD pairs, this paper proposed an HSR Spatio-temporal Network(SN) model to analyze the dynamic characteristics of the HSR network. Then the spatiotemporal characteristic path length and the spatio-temporal betweenness centrality are studied by transforming the SN network into a Spatio-temporal Nodes based Network(SNN). Moreover, an indicator named spatio-temporal connectivity is proposed to derive the connectivity status variation of the HSR. Cases study reveal the quantitative relationship between the train timetable and the transportation performance and the evolution law of the network characteristics. The results could be used further to optimize the organization of trains from a network perspective.
UR - https://www.scopus.com/pages/publications/85118444991
U2 - 10.1109/ITSC48978.2021.9565028
DO - 10.1109/ITSC48978.2021.9565028
M3 - 会议稿件
AN - SCOPUS:85118444991
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 3640
EP - 3645
BT - 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 September 2021 through 22 September 2021
ER -