Urban traffic signal control under mixed traffic flows: Literature review
Mixed traffic flows are opening up new areas for research and are seen as key drivers in the
field of data and services that will make roads safer and more environmentally friendly …
field of data and services that will make roads safer and more environmentally friendly …
QoS-aware offloading based on communication-computation resource coordination for 6G edge intelligence
Driven by the demands of diverse artificial intelligence (AI)-enabled application, Mobile
Edge Computing (MEC) is considered one of the key technologies for 6G edge intelligence …
Edge Computing (MEC) is considered one of the key technologies for 6G edge intelligence …
A Novel Traffic Flow Forecasting Method Based on RNN‐GCN and BRB
H Zhu, Y Xie, W He, C Sun, K Zhu… - Journal of Advanced …, 2020 - Wiley Online Library
As an important part of a smart city, intelligent transport can effectively reduce energy
consumption and environmental pollution. Traffic flow forecasting provides a reliable traffic …
consumption and environmental pollution. Traffic flow forecasting provides a reliable traffic …
Fine-grained traffic flow prediction of various vehicle types via fusion of multisource data and deep learning approaches
P Wang, W Hao, Y Jin - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Both road users and road administrators are keen to know traffic flow of fine-grained vehicle
type. Successful prediction on the traffic flow of heavy, medium and small vehicle could …
type. Successful prediction on the traffic flow of heavy, medium and small vehicle could …
On the deployment of V2X roadside units for traffic prediction
In this paper, we evaluate the ability of connected roadside infrastructure to provide traffic
predictions on highways based on the motion of connected vehicles. In particular, we …
predictions on highways based on the motion of connected vehicles. In particular, we …
An optimal dynamic lane reversal and traffic control strategy for autonomous vehicles
This paper studies an optimal dynamic lane reversal and traffic control (DLRTC) strategy in
the presence of autonomous vehicles (AVs). A centralized controller is set to change lane …
the presence of autonomous vehicles (AVs). A centralized controller is set to change lane …
A novel mixed method of machine learning based models in vehicular traffic flow prediction
How to effectively improve the efficiency of vehicle traffic in the road system will play an
essential role in improving the operational efficiency of the traffic system while eliminating …
essential role in improving the operational efficiency of the traffic system while eliminating …
An ensemble-based machine learning model for forecasting network traffic in VANET
Vehicular Ad-hoc Networks (VANETs), as the most significant element of the Intelligent
Transportation Systems (ITS), have the potential to enhance traffic efficiency and road safety …
Transportation Systems (ITS), have the potential to enhance traffic efficiency and road safety …
Spatiotemporal residual graph attention network for traffic flow forecasting
Q Zhang, C Li, F Su, Y Li - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Accurate spatiotemporal traffic flow forecasting is significant for the modern traffic
management and control. In order to capture the spatiotemporal characteristics of the traffic …
management and control. In order to capture the spatiotemporal characteristics of the traffic …
Modeling aggressive driving behavior based on graph construction
J Wang, W Xu, T Fu, H Gong, Q Shangguan… - … Research Part C …, 2022 - Elsevier
The occurrence of aggressive driving behavior is a random process among time-varying
transversion. For modeling aggressive driving behavior, previous studies have typically …
transversion. For modeling aggressive driving behavior, previous studies have typically …