Traffic state estimation (TSE) refers to the process of the inference of traffic state variables
(ie, flow, density, speed and other equivalent variables) on road segments using partially …

Freeway traffic state estimation and prediction are central components in real-time traffic
management and information applications. Model-based traffic state estimators consist of a …

In recent years, rapid advances in information technology have led to various data collection
systems which are enriching the sources of empirical data for use in transport systems …

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 …

Holiday passenger flow forecasting is essential to transportation plan-making and
passenger flow organization in metro systems during holidays. Usually, daily passenger flow …

The paper proposes a model-based framework for estimating traffic states from Eulerian
(loop) and/or Lagrangian (probe) data. Lagrangian-Space formulation of the LWR model …

Freeway traffic state information from multiple sources provides sufficient support to the
traffic surveillance but also brings challenges. This paper made an investigation into the …

This paper proposes alternative approaches for the prediction of short‐term traffic flow using
three branches of computational intelligence techniques, namely linear genetic …

This paper proposes a new model-based traffic state estimation framework using the LWR
model formulated in vehicle number–space (Lagrangian–space) coordinates. This …

This paper presents a novel approach for freeway traffic state estimation. Although there is
currently a wide variety of estimation methods, new designs and technologies can still be …