A Physical Law Constrained Deep Learning Model for Vehicle Trajectory Prediction

Vehicle trajectory prediction is crucial and indispensable for ensuring the safe and efficient operation of autonomous vehicles in complex traffic environments. The application of IoT technology in the collaborative automated driving system (CADS) has established a robust data foundation for vehicle...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE internet of things journal Jg. 10; H. 24; S. 1
Hauptverfasser:	Li, Hanchu, Liao, Ziyi, Rui, Yikang, Li, Linchao, Ran, Bin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 15.12.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Behavioral sciences Data models Data-driven Deep learning Driving Force GRU encoder-decoder framework Internet of Things Mathematical models Physical-driven Predictive models Social force rules Trajectories Trajectory Vehicle trajectory prediction Vehicles
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!