Area-wide measurements of traffic flow are usually not possible with today's common sensor technologies. However, such information is essential for (urban) traffic planning and control. Hence, in ...

Traffic congestion and its inherent stochasticity continue to challenge urban mobility worldwide. Addressing this, researchers have introduced a groundbreaking framework for modeling the Stochastic ...

MaTE is a data-driven macroscopic model for estimating traffic flow and travel times across the entire transportation networks.MaTE leverages large-scale traffic data to offer accurate, wide-range ...

I am excited to see our new article "A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a Markovian model with deep learning" published ...

Bridging microscopic interactions and macroscopic traffic patterns: a novel approach to stochastic fundamental diagram modeling Peer-Reviewed Publication ...

ABSTRACT: A fluid dynamic traffic flow model based on a non-linear velocity-density function is considered. The model provides a quasi-linear first order hyperbolic partial differential equation which ...