Spatiotemporal Clustering of Parking Lots at the City Level for Efficiently Sharing Occupancy Forecasting Models

This study aims to address the challenge of developing accurate and efficient parking occupancy forecasting models at the city level for autonomous vehicles. Although deep learning techniques have been successfully employed to develop such models for individual parking lots, it is a resource-intensi...

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Detalles Bibliográficos
Autores principales: Mufida, Miratul Khusna, Ait El Cadi, Abdessamad, Delot, Thierry, Trépanier, Martin, Zekri, Dorsaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256105/
https://www.ncbi.nlm.nih.gov/pubmed/37299974
http://dx.doi.org/10.3390/s23115248

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256105/
https://www.ncbi.nlm.nih.gov/pubmed/37299974
http://dx.doi.org/10.3390/s23115248

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