Unveiling Self-Organization and Emergent Phenomena in Urban Transportation Systems via Multilayer Network Analysis
Hongqing Bao, Xia Luo, Xuan Li, Yiyang Zhao
TL;DR
This study explores how ride-hailing and metro systems interact to form self-organized patterns in urban transportation without central planning.
Contribution
The paper introduces a four-layer temporal network model and two new indicators to analyze emergent intermodal phenomena in urban transport.
Findings
A spontaneously emergent intermodal phenomenon between ride-hailing and metro networks was revealed.
Intermodal patterns can occur on non-working days with large and homogeneous demand cohorts.
A time-varying multicentric hierarchical structure was identified in the metro network.
Abstract
In the absence of system-wide planning and coordination, emerging mobility services have been integrated into urban transportation systems as independent network layers. Meanwhile, their interactions with traditional public transit give rise to complex self-organizing patterns in population mobility, manifested as coopetitive dynamics. To systematically analyze this phenomenon, this study constructs a four-layer temporal network—consisting of ride-hailing, metro, combined, and potential layers—based on a vectorized multilayer network model and inter-layer mapping relationships. An analytical framework is then developed using node strength, cosine similarity, and rich-club coefficients, along with two newly proposed indicators: the intermodal index and the node importance coefficient. The results reveal, for the first time, a spontaneously emergent intermodal phenomenon between…
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Taxonomy
TopicsTransportation and Mobility Innovations · Transportation Planning and Optimization · Urban Transport and Accessibility