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Found 3 papers, 2 papers with code
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes
However, the lack of sensors often results in incomplete traffic state data, making it challenging to obtain reliable information for decision-making.
Laplacian Convolutional Representation for Traffic Time Series Imputation
In this study, we first introduce a Laplacian kernel to temporal regularization for characterizing local trends in traffic time series, which can be formulated in the form of circular convolution.
Individual Mobility Prediction via Attentive Marked Temporal Point Processes
Individual mobility prediction is an essential task for transportation demand management and traffic system operation.
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