A Forward-Collision Warning System for Electric Vehicles: Experimental Validation in Virtual and Real Environment

Nicola Albarella, Francesco Masuccio, Luigi Novella, Manuela Tufo and Giovanni Fiengo
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Nicola Albarella: Department of Electrical Engineering and Information Technology, University of Napoli Federico II, 80125 Naples, Italy
Francesco Masuccio: Kineton S.r.l., 80146 Napoli, Italy
Luigi Novella: Kineton S.r.l., 80146 Napoli, Italy
Manuela Tufo: Kineton S.r.l., 80146 Napoli, Italy
Giovanni Fiengo: Kineton S.r.l., 80146 Napoli, Italy

Energies, 2021, vol. 14, issue 16, 1-12

Abstract: Driver behaviour and distraction have been identified as the main causes of rear end collisions. However a promptly issued warning can reduce the severity of crashes, if not prevent them completely. This paper proposes a Forward Collision Warning System (FCW) based on information coming from a low cost forward monocular camera for low end electric vehicles. The system resorts to a Convolutional Neural Network (CNN) and does not require the reconstruction of a complete 3D model of the surrounding environment. Moreover a closed-loop simulation platform is proposed, which enables the fast development and testing of the FCW and other Advanced Driver Assistance Systems (ADAS). The system is then deployed on embedded hardware and experimentally validated on a test track.

Keywords: ADAS; forward collision warning; active safety; hardware-in-the-loop; experimental tests (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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