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Pedestrian Trajectory Prediction for Real-Time Autonomous Systems via Context-Augmented Transformer Networks

Forecasting the trajectory of pedestrians in shared urban traffic environments from non-invasive sensor modalities is still considered one of the challenging problems facing the development of autonomous vehicles (AVs). In the literature, this problem is often tackled using recurrent neural networks...

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Detalles Bibliográficos
Autor principal: Saleh, Khaled
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572723/
https://www.ncbi.nlm.nih.gov/pubmed/36236592
http://dx.doi.org/10.3390/s22197495