In many driving situations, human mobility is an important topic in trajectory prediction. Considering the pedestrian trajectory as a sequence generative task, a prediction algorithm based on Social Long Short-Term Me...
详细信息
High-speed train possesses high capacity, high speed, low consumption, low pollution, and it has become the development tendency of rail transportations. Parallel high-speed train provides the basic idea for construct...
详细信息
High-speed train possesses high capacity, high speed, low consumption, low pollution, and it has become the development tendency of rail transportations. Parallel high-speed train provides the basic idea for construct...
详细信息
ISBN:
(纸本)9781665426480
High-speed train possesses high capacity, high speed, low consumption, low pollution, and it has become the development tendency of rail transportations. Parallel high-speed train provides the basic idea for constructing the transportation scenes for evaluation experiments and provides feasible approaches for carrying out experiments for evaluating the control plans of high-speed trains. The simulation test based on parallel high-speed train systems is proposed. First, the rule base is set up to model the influence of the environment for parallel high-speed train systems based on the simple-is-consistent principle. Second, the typical functions and the relations between the elements of the control system of the trains are analyzed. Third, the models of the typical operating scenes of the controlsystems of high-speed trains are established. Finally, the method for designing experiments for parallel high-speed train systems are studied and the operational mechanisms of parallel high-speed train systems are established.
In many driving situations, human mobility is an important topic in trajectory prediction. Considering the pedestrian trajectory as a sequence generative task, a prediction algorithm based on Social Long Short-Term Me...
详细信息
In many driving situations, human mobility is an important topic in trajectory prediction. Considering the pedestrian trajectory as a sequence generative task, a prediction algorithm based on Social Long Short-Term Memory (Social LSTM) is implemented. In order to simulate the social interaction between pedestrians, Social Pooling (S-Pooling) is used to aggregate the hidden state of pedestrians, while the attention mechanism is utilized to aggregate information differently according to the importance of surrounding pedestrians. Furthermore, Convolutional Neural Networks (CNN) is introduced into Social LSTM model to consider both the interaction between people and the characteristic of scene scale in the prediction process. Experiments are carried out against baseline methods, and the results demonstrated that combining Social LSTM with attention mechanism or CNN can improve the performance of pedestrian trajectory prediction.
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