Graph neural network for traffic forecasting: A survey
Traffic forecasting is important for the success of intelligent transportation systems. Deep
learning models, including convolution neural networks and recurrent neural networks, have …
learning models, including convolution neural networks and recurrent neural networks, have …
A survey of traffic prediction: from spatio-temporal data to intelligent transportation
H Yuan, G Li - Data Science and Engineering, 2021 - Springer
Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …
efficient. With the development of mobile Internet and position technologies, it is reasonable …
Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction
As a core technology of Intelligent Transportation System, traffic flow prediction has a wide
range of applications. The fundamental challenge in traffic flow prediction is to effectively …
range of applications. The fundamental challenge in traffic flow prediction is to effectively …
Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities
Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …
critical problem globally, resulting in negative consequences such as lost hours of additional …
[HTML][HTML] A review of spatially-explicit GeoAI applications in Urban Geography
Urban Geography studies forms, social fabrics, and economic structures of cities from a
geographic perspective. Catalysed by the increasingly abundant spatial big data, Urban …
geographic perspective. Catalysed by the increasingly abundant spatial big data, Urban …
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 …
A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highways
H Dou, Y Liu, S Chen, H Zhao, H Bilal - Soft Computing, 2023 - Springer
Many highways are acquiring smart transportation systems to improve traffic efficiency,
safety and management. Intelligent transportation systems can monitor traffic congestion by …
safety and management. Intelligent transportation systems can monitor traffic congestion by …
Graph neural network for traffic forecasting: The research progress
Traffic forecasting has been regarded as the basis for many intelligent transportation system
(ITS) applications, including but not limited to trip planning, road traffic control, and vehicle …
(ITS) applications, including but not limited to trip planning, road traffic control, and vehicle …
A survey on time-series pre-trained models
Time-Series Mining (TSM) is an important research area since it shows great potential in
practical applications. Deep learning models that rely on massive labeled data have been …
practical applications. Deep learning models that rely on massive labeled data have been …
ESTNet: embedded spatial-temporal network for modeling traffic flow dynamics
Accurate spatial-temporal prediction is a fundamental building block of many real-world
applications such as traffic scheduling and management, environment policy making, and …
applications such as traffic scheduling and management, environment policy making, and …