Do traffic flow states follow Markov properties? A high-order spatiotemporal traffic state reconstruction approach for traffic prediction and imputation

Hu, Junjie; Hu, Cheng; Yang, Jiayu; Bai, Jun; Lee, Jaeyoung Jay

doi:10.1016/j.chaos.2024.114965

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Do traffic flow states follow Markov properties? A high-order spatiotemporal traffic state reconstruction approach for traffic prediction and imputation

Cited by 3 publications

References 41 publications

Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction

Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction

Crash risk prediction using sparse collision data: Granger causal inference and graph convolutional network approaches

CNN-BiGRU-Attention: A Time Series-Based Traffic Flow Prediction Model

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