3.4k citations · 4.2k across the 6 of their papers we have counts for
7 papers
AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting
Jiawei Zhu, Chao Tao, Hanhan Deng +4
Traffic forecasting is a fundamental and challenging task in the field of intelligent transportation. Accurate forecasting not only depends on the historical traffic flow informati…
KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting
Jiawei Zhu, Xin Han, Hanhan Deng +5
While considering the spatial and temporal features of traffic, capturing the impacts of various external factors on travel is an essential step towards achieving accurate traffic…
T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
Ling Zhao, Yujiao Song, Chao Zhang +5
Accurate and real-time traffic forecasting plays an important role in the Intelligent Traffic System and is of great significance for urban traffic planning, traffic management, an…
Measuring Road Network Topology Vulnerability by Ricci Curvature
Lei Gao, Xingquan Liu, Yu Liu +4
Describing the basic properties of road network systems, such as their robustness, vulnerability, and reliability, has been a very important research topic in the field of urban tr…
On the role of spatial dynamics and topology on network flows
Serdar Colak, Christian M. Schneider, Pu Wang +1
Particle flows in spatial networks are susceptible to congestion. In this paper, we analyze the phase transitions of these networks to a state of congested transport and the influe…
Predicting commuter flows in spatial networks using a radiation model based on temporal ranges
Yihui Ren, Mária Ercsey-Ravasz, Pu Wang +2
Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and of…