Car driving safety represents one of the major targets of the ADAS (Advanced Driver Assistance Systems) technologies deeply investigated by the scientific community and car makers. From intelligent suspension control systems to adaptive braking systems, the ADAS solutions allows to significantly improve both driving comfort and safety. The aim of this contribution is to propose a driving safety assessment system based on deep networks equipped with self-attention Criss-Cross mechanism to classify the driving road surface combined with a physio-based drowsiness monitoring of the driver. The retrieved driving safety assessment performance confirmed the effectiveness of the proposed pipeline.
Intelligent road surface deep embedded classifier for an efficient physio-based car driver assistance / F. Rundo, R. Leotta, V. Piuri, A. Genovese, F. Scotti, S. Battiato - In: 2021 IEEE International Conference on Autonomous Systems (ICAS)[s.l] : IEEE, 2021. - ISBN 978-1-7281-7289-7. - pp. 1-5 (( Intervento presentato al 1. convegno ICAS 2021 tenutosi a Montreal nel 2021 [10.1109/ICAS49788.2021.9551124].
Intelligent road surface deep embedded classifier for an efficient physio-based car driver assistance
V. Piuri;A. Genovese;F. Scotti;
2021
Abstract
Car driving safety represents one of the major targets of the ADAS (Advanced Driver Assistance Systems) technologies deeply investigated by the scientific community and car makers. From intelligent suspension control systems to adaptive braking systems, the ADAS solutions allows to significantly improve both driving comfort and safety. The aim of this contribution is to propose a driving safety assessment system based on deep networks equipped with self-attention Criss-Cross mechanism to classify the driving road surface combined with a physio-based drowsiness monitoring of the driver. The retrieved driving safety assessment performance confirmed the effectiveness of the proposed pipeline.
| File | Dimensione | Formato | |
|---|---|---|---|
|
icas21st.pdf
accesso aperto
Tipologia:
Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione
2.01 MB
Formato
Adobe PDF
|
2.01 MB | Adobe PDF | Visualizza/Apri |
|
Intelligent_Road_Surface_Deep_Embedded_Classifier_for_an_Efficient_Physio-Based_Car_Driver_Assistance.pdf
accesso riservato
Tipologia:
Publisher's version/PDF
Dimensione
916.88 kB
Formato
Adobe PDF
|
916.88 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
