Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter

1 May 2019 Xi Xiong Kaan Ozbay Li Jin Chen Feng

Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of prediction of dynamic Origin-Destination (O-D) demand matrices is that demands cannot be directly measured by traffic sensors; instead, they have to be inferred from aggregate traffic flow data on traffic links... (read more)

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