May 19, 2023 · This paper proposes a novel modeling method for urban spaces to support the topological trajectory definition of vehicles which can be useful ...
Firstly, this model discretizes the production and attraction units of transportation, combining them with key nodes in the road network to form ...
May 4, 2023 · Firstly, this model discretizes the production and attraction units of transportation, combining them with key nodes in the road network to form ...
Deep neural network models that jointly predict the next location and arrival time of a vehicle. ... Learns sequential patterns in trajectory data using LSTM ...
May 31, 2024 · The experimental results show that the proposed trajectory prediction model can adapt to different driving scenarios and predict trajectories ...
Firstly, this model discretizes the production and attraction units of transportation, combining them with key nodes in the road network to form an urban ...
This paper proposes a deep learning approach to learning and predicting network-wide vehicle movement patterns in urban networks. Inspired by recent success ...
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In this proposed model, we use attention mechanism to incorporate network traffic state data into urban vehicle trajectory prediction. The model is evaluated by ...
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Apr 19, 2024 · Reliable prediction of vehicle trajectories at signalized intersections is crucial to urban traffic management and.
This paper proposes a deep learning approach to learning and predicting network-wide vehicle movement patterns in urban networks and trains an RNN model to ...