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 …

Recently, development in intelligent transportation systems (ITS) requires the input of
various kinds of data in real-time and from multiple sources, which imposes additional …

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 …

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

For its robust predictive power (compared to pure physics-based models) and sample-
efficient training (compared to pure deep learning models), physics-informed deep learning …

The fundamental diagram (FD), also known as the flow–density relation, is one of the most
fundamental concepts in the traffic flow theory. Conventionally, FDs are estimated by using …

Traffic state in the urban network is a direct reflection of the operational efficiency of the
urban transportation system. As the busiest period of the day, traffic states during evening …

Connected and autonomous vehicles (CAVs) are on the way to the field application. In the
beginning stage, there will be a mixed traffic flow, containing the regular human‐driven …

Recent decades have witnessed the breakthrough of autonomous vehicles (AVs), and the
sensing capabilities of AVs have been dramatically improved. Various sensors installed on …

Real‐time traffic state estimation is of importance for efficient traffic management. This is
especially the case for traffic management systems that require fast detection of changes in …