At present, traffic state prediction primarily relies on purely data-driven methods, ignoring the
incorporation of physical constraints within the field of traffic flow. Taking this as a starting …

Accurate traffic flow prediction can provide effective decision-making support for traffic
management, alleviate traffic congestion, and improve road traffic efficiency. Traffic flow data …

Reliable and accurate traffic flow prediction is crucial for the construction and operation of
smart highways, supporting scientific traffic management and planning. However, accurately …

This paper proposes a dynamic multi-scale spatial-temporal graph convolutional network
(DS-STGCN) for traffic flow prediction. The network aims to comprehensively extract global …

Because of the random volatility of traffic data, short-term traffic flow forecasting has always
been a problem that needs to be further researched. We developed a short-term traffic flow …

Origin–destination (OD) flow prediction is crucial for predicting inter-station passenger flows
in intelligent transport systems. However, previous OD prediction methods have ignored the …

Spatial prediction models hold significant application value in fields such as environmental
science, economic development, and geological exploration. With advancements in deep …

Rapid urbanization and population growth raise significant challenges in modern traffic
management, where traffic prediction is essential for intelligent transportation systems …

Enhancing the efficiency and safety of the Intelligent Transportation System requires
effective modeling and prediction of citywide traffic dynamics. Most studies employ …

Accurate and timely traffic flow predictions are essential for effective traffic management and
congestion reduction. However, most traditional prediction methods often fail to capture the …