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 …

The development of real-time road condition systems will better monitor road network
operation status. However, the weak point of all these systems is their need for …

Traffic shockwaves demonstrate the formation and spreading of traffic fluctuation on roads.
Existing methods mainly detect the shockwaves and their propagation by estimating traffic …

Traffic density is a crucial indicator of traffic congestion, but measuring it directly is often
infeasible and hence, it is usually estimated based on other measurements. However, a …

Toll‐gates are crucial points of management and key congestion bottleneck for the freeway.
In order to avoid traffic deterioration and alleviate traffic congestion in advance, it is …

This paper proposes a methodology for estimating lane-level traffic state for freeways by
fusing data from intelligent connected vehicles (ICVs) with fixed detector data (FDD) and …

The increasing wealth of truck global positioning system (GPS) data has broadened the
opportunities for understanding freight logistics activities and enhancing research …

In this paper, we propose a new data-driven traffic state estimation model that estimates
traffic flow based on average speed data only. The model is devised to implement a cost …

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 …

Accurate traffic state estimation is essential for the successful application of intelligent
transportation systems (ITS). In the past, traffic state estimation methods based on the macro …