Vehicle track destination prediction method considering space-time semantics and driving state
A driving state, spatiotemporal semantic technology, applied in the field of vehicle trajectory destination prediction, can solve problems such as low accuracy, achieve the effect of improving accuracy and realizing refined expression
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[0079] The purpose of the present invention is to solve the problem that the existing individual trajectory destination prediction model ignores the travel spatio-temporal context information, and cannot learn the user's travel preferences and behavior habits in the specific spatio-temporal context, while ignoring the impact of driving state information on travel key spatio-temporal features. The important role of detection and learning is difficult to describe the entire travel process in a fine-grained manner, which leads to the technical problem of low accuracy of travel destination prediction results. A vehicle trajectory destination prediction method that takes into account space-time semantics and driving status is provided, thereby improving Forecast accuracy purposes.
[0080] In order to achieve the above object, the main idea of the present invention is as follows:
[0081] Firstly, the type distribution information of POIs that are closely related to travel behavi...
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