Traffic state estimation (TSE) reconstructs the traffic variables (eg, density or average
velocity) on road segments using partially observed data, which is important for traffic …

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 …

Numerous continuum models have been proposed for freeway traffic, but their performance
for real-world traffic flows has not been rigorously evaluated and compared in the literature …

This paper proposes the TrafficFlowGAN, a physics-informed flow based generative
adversarial network (GAN), for uncertainty quantification (UQ) of dynamical systems …

Three filtering-based approaches to freeway traffic state estimation are studied using
measurements from connected vehicles and also a minimum number of fixed detectors …

Inference of detailed vehicle trajectories is crucial for applications such as traffic flow
modeling, energy consumption estimation, and traffic flow optimization. Static sensors can …

Vehicle trajectories can offer the most precise and detailed depiction of traffic flow and serve
as a critical component in traffic management and control applications. Various technologies …

This paper addresses model-based approach considering online model parameters
estimation to estimate the real-time freeway traffic state for inhomogeneous traffic flow. Its …

This paper addresses the problem of traffic state estimation (TSE) in the presence of
heterogeneous sensors which include both fixed and moving sensors. Traditional fixed …

Accurate bus travel time prediction in real-time is challenging, as numerous factors such as
fluctuating travel demand, incidents, signals, bus stops, dwell times, and seasonal variations …