Traffic state estimation on highway: A comprehensive survey
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 …
(ie, flow, density, speed and other equivalent variables) on road segments using partially …
[HTML][HTML] Traffic state estimation of urban road networks by multi-source data fusion: Review and new insights
Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …
information for urban traffic control and management strategies. However, due to the …
Dynamic Bayesian network for aircraft wing health monitoring digital twin
Current airframe health monitoring generally relies on deterministic physics models and
ground inspections. This paper uses the concept of a dynamic Bayesian network to build a …
ground inspections. This paper uses the concept of a dynamic Bayesian network to build a …
Physics-informed neural networks for integrated traffic state and queue profile estimation: A differentiable programming approach on layered computational graphs
This paper presents an integrated framework for physics-informed joint traffic state and
queue profile estimation (JSQE) on freeway corridors, utilizing heterogeneous data sources …
queue profile estimation (JSQE) on freeway corridors, utilizing heterogeneous data sources …
Short-term speed predictions exploiting big data on large urban road networks
Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the
road network and provide great opportunities for enhanced short-term traffic predictions …
road network and provide great opportunities for enhanced short-term traffic predictions …
Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment
The paper proposes a first-order macroscopic stochastic dynamic traffic model, namely the
stochastic cell transmission model (SCTM), to model traffic flow density on freeway …
stochastic cell transmission model (SCTM), to model traffic flow density on freeway …
Distributed scheduling and cooperative control for charging of electric vehicles at highway service stations
The increasing number of electric vehicles (EVs) on highways calls for the installment of
adequate charging infrastructure. Since charging infrastructure has limited capacity, EVs …
adequate charging infrastructure. Since charging infrastructure has limited capacity, EVs …
Highway traffic state estimation with mixed connected and conventional vehicles
We present a macroscopic model-based approach for the estimation of the total density and
flow of vehicles, for the case of “mixed” traffic, ie, traffic comprising both ordinary and …
flow of vehicles, for the case of “mixed” traffic, ie, traffic comprising both ordinary and …
Data fusion for multi-source sensors using GA-PSO-BP neural network
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 …
operation status. However, the weak point of all these systems is their need for …
Highway traffic state estimation with mixed connected and conventional vehicles: Microscopic simulation-based testing
This paper presents a thorough microscopic simulation investigation of a recently proposed
methodology for highway traffic estimation with mixed traffic, ie, traffic comprising both …
methodology for highway traffic estimation with mixed traffic, ie, traffic comprising both …