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 …

Traffic prediction is a major component of any traffic management system. With the increase
in data sources and advancement in connectivity, data analysis and machine learning …

Previous controlled experiments on single-lane ring roads have shown that a single partially
autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the …

Higher-order traffic flow models describe the dynamics of non-equilibrium traffic (eg,
capacity drop, traffic oscillation). Therefore, a traffic state estimation (TSE) method based on …

Traffic state observers derived from the cell transmission model (CTM) are vulnerable to
incorrect information and time variation of traffic flow parameters, in particular the critical …

Real-Time Joint Estimation of Traffic States and Parameters Using Cell Transmission Model
and Considering Capacity Drop Page 1  Abstract—This paper contributes to an understudied …

We consider the online filtering problem for a graph-coupled hidden Markov model (GHMM)
with the Anonymous Influence property. Large-scale spatial processes such as forest res …

Accurate prediction of traffic flow dynamics is a key step towards effective congestion
mitigation strategies. The dynamic nature of traffic flow and lack of comprehensive data …

This thesis derives a series of algorithms to enable the use of a class of structured models,
known as graph-based Markov decision processes (GMDPs), for applications involving a …

Accurate traffic state prediction is critical to implementing an effective traffic management
strategy. Unfortunately, the dynamic nature of traffic flow and the limitations of conventional …