As autonomous cars are entering mainstream, new research directions are opening involving several domains, from hardware design to control systems, from energy efficiency to computer vision. An exciting direction of research is represented by the coordination of the different vehicles, moving the focus from the single one to a collective system. In this paper we propose some challenging examples thatshow the motivations for a coordination approach in autonomous driving. Moreover, we present some techniques borrowed from distributed artificial intelligence that can be exploited to tackle the previously mentioned challenges.
Adaptive coordination in autonomous driving: Motivations and perspectives / Bertogna, Marko; Burgio, Paolo; Cabri, Giacomo; Capodieci, Nicola. - (2017), pp. 15-17. (Intervento presentato al convegno 26th IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2017 tenutosi a Poznan, Poland nel 2017) [10.1109/WETICE.2017.45].
Adaptive coordination in autonomous driving: Motivations and perspectives
Bertogna, Marko;Burgio, Paolo;Cabri, Giacomo
;Capodieci, Nicola
2017
Abstract
As autonomous cars are entering mainstream, new research directions are opening involving several domains, from hardware design to control systems, from energy efficiency to computer vision. An exciting direction of research is represented by the coordination of the different vehicles, moving the focus from the single one to a collective system. In this paper we propose some challenging examples thatshow the motivations for a coordination approach in autonomous driving. Moreover, we present some techniques borrowed from distributed artificial intelligence that can be exploited to tackle the previously mentioned challenges.File | Dimensione | Formato | |
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