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 …

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 …

Traffic prediction is a core problem in the intelligent transportation system and has broad
applications in the transportation management and planning, and the main challenge of this …

We develop a Kalman filter for predicting traffic flow at urban arterials based on data
obtained from connected vehicles. The proposed algorithm is computationally efficient and …

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 …

The paper develops a non-parametric method for route travel time distribution estimation
using low-frequency floating car data (FCD). While most previous work has focused on link …

We present a macroscopic model-based approach for the estimation of the total density and
flow of vehicles, for the case of “mixed” traffic, ie, traffic comprising both ordinary and …

Observability and controllability are two critical requirements for a partially observable
transportation system. This paper proposes a stepwise signal optimization framework with …

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 …

Urban transport contributes more than a quarter of the global greenhouse gas emissionns
that drive climate change; it also produces significant air pollution emissions. Furthermore …