Network-scale traffic prediction via knowledge transfer and regional MFD analysis
Network traffic flow prediction on a fine-grained spatio-temporal scale is essential for
intelligent transportation systems, and extensive studies have been carried out in this area …
intelligent transportation systems, and extensive studies have been carried out in this area …
Transfer learning with spatial–temporal graph convolutional network for traffic prediction
Z Yao, S Xia, Y Li, G Wu, L Zuo - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate spatial-temporal traffic modeling and prediction play an important role in intelligent
transportation systems (ITS). Recently, various deep learning methods such as graph …
transportation systems (ITS). Recently, various deep learning methods such as graph …
A Transfer Learning-Based Approach to Estimating Missing Pairs of On/Off Ramp Flows
J Zhang, C Song, Z Mo, S Cao - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Each freeway stretch's traffic states are indispensable in freeway traffic modeling,
surveillance, and control. However, the unmeasured ramp pairs always exist in real-world …
surveillance, and control. However, the unmeasured ramp pairs always exist in real-world …
Physics-Guided Multi-Source Transfer Learning for Network-Scale Traffic Flow Prediction
Recent research has shown that some network traffic flow patterns are similar across
multiple traffic regions. Identifying and transferring these domain-invariant features can …
multiple traffic regions. Identifying and transferring these domain-invariant features can …
Spatiotemporal Ego-Graph Domain Adaptation for Traffic Prediction With Data Missing
As an important research field in time series processing, traffic prediction has a profound
impact on people's daily lives and social development. Conventional traffic prediction relies …
impact on people's daily lives and social development. Conventional traffic prediction relies …
Unsupervised knowledge adaptation for passenger demand forecasting
Considering the multimodal nature of transport systems and potential cross-modal
correlations, there is a growing trend of enhancing demand forecasting accuracy by learning …
correlations, there is a growing trend of enhancing demand forecasting accuracy by learning …