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 …

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 …

In real-time traffic management and intelligent transportation systems (ITS) applications, an
accurate picture of the prevailing traffic state in terms of speeds and densities is critical, for …

Real-time estimation of the traffic state in urban signalized links is valuable information for
modern traffic control and management. In recent years, with the development of in-vehicle …

Traffic state estimation (TSE) is a critical component of the efficient intelligent transportation
systems (ITS) operations. In the literature, TSE methods are divided into model-driven …

Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …

Freeway traffic state estimation is a vital component of traffic management and information
systems. Macroscopic-model-based traffic state estimation methods are widely used in this …

Traffic state prediction is a key problem with considerable implications in modern traffic
management. Traffic flow theory has provided significant resources, including models based …

The rapid-growth of smartphones with embedded navigation systems such as GPS modules
provides new ways of monitoring traffic. These devices can register and send a great …

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 …