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26 de abr. de 2024 · Traffic flow prediction. Traffic flow prediction is to use the spatial–temporal data collected by road sensors to make as accurate a prediction as possible for the traffic state in...
23 de abr. de 2024 · On PeMS04 dataset, compared with the best results achieved by baselines, MVC-STNet reduces RMSE of the traffic flow prediction from 39.45 achieved by T-GCN to 37.61, and MAE from 26.78 achieved by DCRNN to 23.83. MVC-STNet reduces the RMSE from 33.62 to 32.88, and MAE from 24.92 to 21.40.
26 de abr. de 2024 · The core objective of traffic flow prediction is to establish a mapping relationship using prior knowledge to predict future traffic conditions. More specifically, it is based on graph signal data spanning T time steps, aiming to learn a mapping function F that accurately predicts the temporal signal data for the next \(T'\) time steps.
16 de abr. de 2024 · INTRODUCTION. Trafic flow prediction is a critical component of transportation management systems, aiming to forecast future trafic conditions such as congestion, trafic volume, and travel time. It plays a vital role in various applications, including route planning, trafic management, and intelligent trans-portation systems (ITS) (1).
Hace 2 días · Accurate traffic flow prediction plays a crucial role in the development of intelligent traffic management. Despite numerous investigations into spatio-temporal methods, achieving high accuracy in traffic flow prediction remains challenging. This challenge arises from the complex dynamic spatio-temporal correlations within the traffic road network and the limitations imposed by the selection ...
23 de abr. de 2024 · Deep Multi-View Channel-Wise Spatio-Temporal Network for Traffic Flow Prediction. Hao Miao, Senzhang Wang, Meiyue Zhang, Diansheng Guo, Funing Sun, Fan Yang. Accurately forecasting traffic flows is critically important to many real applications including public safety and intelligent transportation systems.
29 de abr. de 2024 · Traffic flow prediction using big data and deep learning attracts great attentions in recent years. Researchers show that DNN models can provide better traffic prediction accuracy than the traditional shallow models. Since the traffic flow reveals both ...
