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Big data-driven public transportation network: a simulation approach
Complex & Intelligent Systems ( IF 5.0 ) Pub Date : 2021-07-27 , DOI: 10.1007/s40747-021-00462-2
Zhaohua Wang 1 , Xuewei Li 1, 2 , Jing Li 1 , Fan Wang 1 , Fei Wang 1 , Xin Zhu 2
Affiliation  

With the maturity of big data technology, analyzing residents’ travel habits and tracks has become an important research direction in the field of intelligent transportation study. In this paper, based on the subway and bus ride data, a subway-bus double-layer network model was established using complex network theory, taking the optimal traffic efficiency as the goal, the structure of intelligent bus network optimization method is proposed, and an empirical study is conducted on the Beijing bus network. In the empirical study, by adding or deleting bus station in the network, obtain an efficient network structure, the goal of optimal operation efficiency of the bus network was realized, and the theoretical and practical research on solving the problem of transportation line network planning with big data of traffic travel was enriched.

更新日期:2021-07-27
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