A survey on modern deep neural network for traffic prediction: Trends, methods and challenges
In this modern era, traffic congestion has become a major source of severe negative
economic and environmental impact for urban areas worldwide. One of the most efficient …
economic and environmental impact for urban areas worldwide. One of the most efficient …
Traffic flow prediction models–A review of deep learning techniques
AA Kashyap, S Raviraj, A Devarakonda… - Cogent …, 2022 - Taylor & Francis
Traffic flow prediction is an essential part of the intelligent transport system. This is the
accurate estimation of traffic flow in a given region at a particular interval of time in the future …
accurate estimation of traffic flow in a given region at a particular interval of time in the future …
A survey of hybrid deep learning methods for traffic flow prediction
Y Shi, H Feng, X Geng, X Tang, Y Wang - Proceedings of the 2019 3rd …, 2019 - dl.acm.org
Traffic flow prediction using big data and deep learning attracts great attentions in recent
years. Researchers show that DNN models can provide better traffic prediction accuracy …
years. Researchers show that DNN models can provide better traffic prediction accuracy …
[HTML][HTML] Gap, techniques and evaluation: traffic flow prediction using machine learning and deep learning
The development of the Internet of Things (IoT) has produced new innovative solutions, such
as smart cities, which enable humans to have a more efficient, convenient and smarter way …
as smart cities, which enable humans to have a more efficient, convenient and smarter way …
A graph and attentive multi-path convolutional network for traffic prediction
Traffic prediction is an important and yet highly challenging problem due to the complexity
and constantly changing nature of traffic systems. To address the challenges, we propose a …
and constantly changing nature of traffic systems. To address the challenges, we propose a …
Deep learning on traffic prediction: Methods, analysis, and future directions
X Yin, G Wu, J Wei, Y Shen, H Qi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
Traffic flow prediction with big data: A deep learning approach
Accurate and timely traffic flow information is important for the successful deployment of
intelligent transportation systems. Over the last few years, traffic data have been exploding …
intelligent transportation systems. Over the last few years, traffic data have been exploding …
A hybrid deep learning based traffic flow prediction method and its understanding
Deep neural networks (DNNs) have recently demonstrated the capability to predict traffic
flow with big data. While existing DNN models can provide better performance than shallow …
flow with big data. While existing DNN models can provide better performance than shallow …
Trafficgan: Network-scale deep traffic prediction with generative adversarial nets
Traffic flow prediction has received rising research interest recently since it is a key step to
prevent and relieve traffic congestion in urban areas. Existing methods mostly focus on road …
prevent and relieve traffic congestion in urban areas. Existing methods mostly focus on road …
MF-CNN: traffic flow prediction using convolutional neural network and multi-features fusion
D Yang, S Li, Z Peng, P Wang, J Wang… - … on Information and …, 2019 - search.ieice.org
Accurate traffic flow prediction is the precondition for many applications in Intelligent
Transportation Systems, such as traffic control and route guidance. Traditional data driven …
Transportation Systems, such as traffic control and route guidance. Traditional data driven …