An attention‐based deep learning model for traffic flow prediction using spatiotemporal features towards sustainable smart city
In the development of smart cities, the intelligent transportation system (ITS) plays a major
role. The dynamic and chaotic nature of the traffic information makes the accurate …
role. The dynamic and chaotic nature of the traffic information makes the accurate …
Statistical evaluation of data requirement for ramp metering performance assessment
Ramp metering is known to be an effective freeway control measure that ensures the overall
efficiency and safety of a highway system by regulating the inflow traffic on-ramps …
efficiency and safety of a highway system by regulating the inflow traffic on-ramps …
[HTML][HTML] A distributed WND-LSTM model on MapReduce for short-term traffic flow prediction
Building data-driven intelligent transportation is a significant task for establishing data-
centric smart cities, and exceptionally efficient and accurate traffic flow prediction (TFP) is a …
centric smart cities, and exceptionally efficient and accurate traffic flow prediction (TFP) is a …
Proposal of an integrated platoon‐based Round‐Robin algorithm with priorities for intersections with mixed traffic flows
The growth of vehicle ownership has necessitated the adoption of new approaches to cope
with the arising problems. In this regard, while technological advancement in connected and …
with the arising problems. In this regard, while technological advancement in connected and …
[HTML][HTML] A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a Markovian model with deep learning
Accurate traffic congestion estimation and prediction are critical building blocks for smart trip
planning and rerouting decisions in transportation systems. Over the decades, there have …
planning and rerouting decisions in transportation systems. Over the decades, there have …
Short-term traffic flow prediction based on faded memory Kalman Filter fusing data from connected vehicles and Bluetooth sensors
A Emami, M Sarvi, SA Bagloee - Simulation Modelling Practice and Theory, 2020 - Elsevier
This paper proposes a Kalman Filter (KF) technique to predict the short-term flow at urban
arterials based on the information of connected and Bluetooth equipped vehicles. Online …
arterials based on the information of connected and Bluetooth equipped vehicles. Online …
Road section traffic flow prediction method based on the traffic factor state network
Large-scale and diversified traffic data resources strongly support research into estimating
urban traffic states and predicting traffic flow. There are many studies on traffic prediction, but …
urban traffic states and predicting traffic flow. There are many studies on traffic prediction, but …
[HTML][HTML] Deep traffic congestion prediction model based on road segment grouping
Y Tu, S Lin, J Qiao, B Liu - Applied Intelligence, 2021 - Springer
Abstract Intelligent Transportation System (ITS) is now being widely built all over the world.
Traffic congestion prediction, as a major part of ITS, not only provides reliable traffic …
Traffic congestion prediction, as a major part of ITS, not only provides reliable traffic …
The contribution of connected vehicles to network traffic control: A hierarchical approach
Connected vehicles (CVs) can considerably contribute to traffic control in the near future by
providing real-time information. Such information can be exploited to identify the current …
providing real-time information. Such information can be exploited to identify the current …
Temporal pattern mining of urban traffic volume data: A pairwise hybrid clustering method
Multiple pattern analyses of traffic data have been conducted previously; however, it has yet
to be explored with an awareness of temporal factors in big real-world traffic data. In this …
to be explored with an awareness of temporal factors in big real-world traffic data. In this …