Traffic state estimation is a crucial elemental function in Intelligent Transportation Systems
(ITS). However, the collected traffic state data are often incomplete in the real world. In this …

Accurate and real-time traffic flow prediction plays a central role for efficient traffic
management. Software Defined Networking (SDN) is one of the key concerns in networking …

Traffic flow prediction remains an ongoing hot topic in the field of Intelligent Transportation
System. The state-of-the-art traffic flow prediction models can effectively extract both spatial …

This paper addresses real-time joint traffic state and model parameter estimation on
freeways using data from fixed sensors and connected vehicles. It investigates how the …

In this paper, a new practice-ready method for the real-time estimation of traffic conditions
and travel times on highways is introduced. First, after a principal component analysis …

Short‐term traffic flow forecasting is a fundamental and challenging task since it is required
for the successful deployment of intelligent transportation systems and the traffic flow is …

For the purpose of overcoming the technical bottlenecks and limitations of autonomous
vehicles on the information perception, and improving the sensing range and performance …

Traffic state estimation is a fundamental task of Intelligent Transportation Systems (ITS).
Recent advances in sensor technology and emerging computer and vehicular …

The estimation of present passenger flow state plays a vital role in the urban rail transit
(URT) operation process and it is the basis of passenger flow control and train dispatching …

Fundamental diagrams (FDs) are the basis of traffic flow theory. Efficient model calibration
from noisy traffic data is essential to identify the parameters of FDs to describe the traffic flow …