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Motorcycle That See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles.
Gil, Gustavo; Savino, Giovanni; Piantini, Simone; Pierini, Marco.
Affiliation
  • Gil G; Dipartimento di Ingegneria Industriale, Università degli Studi di Firenze, Santa Marta 3, 50139 Firenze, Italy. gil.gustavo@unifi.it.
  • Savino G; Dipartimento di Ingegneria Industriale, Università degli Studi di Firenze, Santa Marta 3, 50139 Firenze, Italy. giovanni.savino@unifi.it.
  • Piantini S; Accident Research Centre, Monash University, Melbourne, 21 Alliance Lane, Clayton, VIC 3800, Australia. giovanni.savino@unifi.it.
  • Pierini M; Dipartimento di Ingegneria Industriale, Università degli Studi di Firenze, Santa Marta 3, 50139 Firenze, Italy. simone.piantini@unifi.it.
Sensors (Basel) ; 18(1)2018 Jan 19.
Article de En | MEDLINE | ID: mdl-29351267
ABSTRACT
Advanced driver assistance systems, ADAS, have shown the possibility to anticipate crash accidents and effectively assist road users in critical traffic situations. This is not the case for motorcyclists, in fact ADAS for motorcycles are still barely developed. Our aim was to study a camera-based sensor for the application of preventive safety in tilting vehicles. We identified two road conflict situations for which automotive remote sensors installed in a tilting vehicle are likely to fail in the identification of critical obstacles. Accordingly, we set two experiments conducted in real traffic conditions to test our stereo vision sensor. Our promising results support the application of this type of sensors for advanced motorcycle safety applications.
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Sensors (Basel) Année: 2018 Type de document: Article Pays d'affiliation: Italie

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Sensors (Basel) Année: 2018 Type de document: Article Pays d'affiliation: Italie