With the rapid development of the Intelligent Transportation System (ITS), accurate traffic
forecasting has emerged as a critical challenge. The key bottleneck lies in capturing the …

Forecasting traffic flow and speed in the urban is important for many applications, ranging
from the intelligent navigation of map applications to congestion relief of city management …

Traffic forecasting has emerged as a core component of intelligent transportation systems.
However, timely accurate traffic forecasting, especially long-term forecasting, still remains an …

Urban traffic forecasting is the cornerstone of the intelligent transportation system (ITS).
Existing methods focus on spatial-temporal dependency modeling, while two intrinsic …

Accurate real-time traffic forecast is critical for intelligent transportation systems (ITS) and it
serves as the cornerstone of various smart mobility applications. Though this research area …

Traffic forecasting can be highly challenging due to complex spatial-temporal correlations
and non-linear traffic patterns. Existing works mostly model such spatial-temporal …

The rapid development of road traffic networks has provided a wealth of research data for
intelligent transportation systems. We are faced with vast high-dimensional traffic flow data …

Traffic forecasting is a complex multivariate time-series regression task of paramount
importance for traffic management and planning. However, existing approaches often …

Traffic forecasting has attracted considerable attention due to its importance in proactive
urban traffic control and management. Scholars and engineers have exerted considerable …

Traffic forecasting is a challenging problem due to the complexity of jointly modeling spatio‐
temporal dependencies at different scales. Recently, several hybrid deep learning models …