Traffic forecasting has been regarded as the basis for many intelligent transportation system
(ITS) applications, including but not limited to trip planning, road traffic control, and vehicle …

This paper surveys the short-term road traffic forecast algorithms based on the long-short
term memory (LSTM) model of deep learning. The algorithms developed in the last three …

Traffic flow prediction methods commonly rely on historical traffic data, such as traffic volume
and speed, but may not be suitable for high-capacity expressways or during peak traffic …

To develop the most appropriate control strategy and monitor, maintain, and evaluate the
traffic performance of the freeway weaving areas, state and local Departments of …

The real-time crash potential prediction model is one of the important components of
proactive traffic management systems. Over the years numerous models have been …

Accurate prediction of road traffic conditions is essential for the effectiveness of Intelligent
Transportation Systems (ITS) and the advancement of smart cities. While existing …

Despite awareness campaigns and legal consequences, speeding is a significant cause of
road accidents and fatalities globally. To combat this issue, understanding the impact of a …

Performing accurate and efficient traffic data repair has become an essential task before
proceeding with other applications of intelligent transportation systems. However, existing …

Accurate monitoring and sensing network-wide traffic conditions under uncertainty is vital for
addressing urban transportation obstacles and promoting the evolution of intelligent …

Accurate short-term passenger flow prediction in urban rail transit is critical in ensuring the
stable operation of urban rail systems. However, accurate passenger flow prediction still …