Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5103143 | Physica A: Statistical Mechanics and its Applications | 2017 | 18 Pages |
Abstract
In recent years, complex network theory has become an important approach to the study of the structure and dynamics of traffic networks. However, because traffic data is difficult to collect, previous studies have usually focused on the physical topology of subway systems, whereas few studies have considered the characteristics of traffic flows through the network. Therefore, in this paper, we present a multi-layer model to analyze traffic flow patterns in subway networks, based on trip data and an operation timetable obtained from the Beijing Subway System. We characterize the patterns in terms of the spatiotemporal flow size distributions of both the train flow network and the passenger flow network. In addition, we describe the essential interactions between these two networks based on statistical analyses. The results of this study suggest that layered models of transportation systems can elucidate fundamental differences between the coexisting traffic flows and can also clarify the mechanism that causes these differences.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Jia Feng, Xiamiao Li, Baohua Mao, Qi Xu, Yun Bai,