Spatiotemporal capsule neural network for vehicle trajectory prediction

Spatiotemporal capsule neural network for vehicle trajectory prediction

Through advancement of the Vehicle-to-Everything (V2X) network, road safety, energy consumption, and traffic efficiency can be significantly improved. An accurate vehicle trajectory prediction benefits communication traffic management and network resource allocation for the real-time application of...

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Dades bibliogràfiques
Autors principals: Qin, Yan, Guan, Yong Liang, Yuen, Chau
Altres autors: School of Electrical and Electronic Engineering
Format: Journal Article
Idioma:English
Publicat: 2023
Matèries:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Trajectory
Vehicle-to-Everything
Global Positioning System
Task Analysis
Predictive Models
Real-Time Systems
Hidden Markov Models
Accés en línia:https://hdl.handle.net/10356/166621

Internet

https://hdl.handle.net/10356/166621

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