Traffic state estimation and forecasting are central components in dynamic traffic
management and information applications. This paper proposes a traffic state estimation …

Traffic and transport research is truly attractive to me. To explore the problem that relates
closely to our life also motivates me. This is the reason why I dive into the field of traffic …

Freeway traffic state estimation is crucial for dynamic traffic management (DTM), Advanced
Traveler Information Systems (ATIS) and highway performance analyses. Raw data …

Real-time traffic condition is a critical input for modern intelligent transportation systems
(ITS). However, current real-time traffic state estimators are all link-based with the …

Real-time freeway traffic state estimation plays an important role in Dynamic Traffic
Management (DTM) and Advanced Traveler Information Systems (ATIS). One of the model …

This paper proposes a new model-based traffic state estimation framework using the LWR
model formulated in vehicle number–space (Lagrangian–space) coordinates. This …

In the near future, vehicles will be equipped to receive and broadcast Basic Safety
Messages (BSMs), which includes the vehicle position, speed, heading, and acceleration, to …

Lagrangian Traffic model which follows a platoon of vehicle has the benefit of convenient
utilization of individual vehicle data and easy distribution of traffic information to the drivers …

There has been extensive research in traffic state estimation that accounts for the stochastic
nature of traffic flow models. However, these studies often exhibit limitations such as an …

An inverse modeling algorithm is developed to reconstruct the state of traffic (velocity field)
on highways from GPS measurements gathered from mobile phones traveling on-board …