Urban traffic signal control with connected and automated vehicles: A survey
Inefficient traffic control is pervasive in modern urban areas, which would exaggerate traffic
congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we …
congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we …
Survey on traffic prediction in smart cities
The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …
makes it possible to examine and predict traffic conditions in smart cities more accurately …
Privacy-preserving blockchain-based federated learning for traffic flow prediction
Y Qi, MS Hossain, J Nie, X Li - Future Generation Computer Systems, 2021 - Elsevier
As accurate and timely traffic flow information is extremely important for traffic management,
traffic flow prediction has become a vital component of intelligent transportation systems …
traffic flow prediction has become a vital component of intelligent transportation systems …
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 …
Deep bidirectional and unidirectional LSTM recurrent neural network for network-wide traffic speed prediction
Short-term traffic forecasting based on deep learning methods, especially long short-term
memory (LSTM) neural networks, has received much attention in recent years. However, the …
memory (LSTM) neural networks, has received much attention in recent years. However, the …
Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach
Short-term passenger demand forecasting is of great importance to the on-demand ride
service platform, which can incentivize vacant cars moving from over-supply regions to over …
service platform, which can incentivize vacant cars moving from over-supply regions to over …
Short-term traffic flow prediction based on spatio-temporal analysis and CNN deep learning
Accurate short-term traffic flow forecasting facilitates active traffic control and trip planning.
Most existing traffic flow models fail to make full use of the temporal and spatial features of …
Most existing traffic flow models fail to make full use of the temporal and spatial features of …
Spatiotemporal recurrent convolutional networks for traffic prediction in transportation networks
H Yu, Z Wu, S Wang, Y Wang, X Ma - Sensors, 2017 - mdpi.com
Predicting large-scale transportation network traffic has become an important and
challenging topic in recent decades. Inspired by the domain knowledge of motion prediction …
challenging topic in recent decades. Inspired by the domain knowledge of motion prediction …
Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems
A Boukerche, Y Tao, P Sun - Computer networks, 2020 - Elsevier
In recent years, the Intelligent transportations system (ITS) has received considerable
attention, due to higher demands for road safety and efficiency in highly interconnected road …
attention, due to higher demands for road safety and efficiency in highly interconnected road …
Sensing data supported traffic flow prediction via denoising schemes and ANN: A comparison
Short-term traffic flow prediction plays a key role of Intelligent Transportation System (ITS),
which supports traffic planning, traffic management and control, roadway safety evaluation …
which supports traffic planning, traffic management and control, roadway safety evaluation …