Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/49525
Title: Autonomous Vehicles Management in Agriculture with Bluetooth Low Energy (BLE) and Passive Radio Frequency Identification (RFID) for Obstacle Avoidance
Authors: Monarca, Danilo 
Rossi, Pierluigi
Alemanno, Riccardo
Cossio, Filippo
Nepa, Paolo
Motroni, Andrea
Gabbrielli, Roberto
Pirozzi, Marco
Console, Carla
Cecchini, Massimo 
Journal: SUSTAINABILITY 
Issue Date: 2022
Abstract: 
Obstacle avoidance is a key aspect for any autonomous vehicles, and their usage in agriculture must overcome additional challenges such as handling interactions with agricultural workers and other tractors in order to avoid severe accidents. The simultaneous presence of autonomous vehicles and workers on foot definitely calls for safer designs, vehicle management systems and major developments in personal protective equipment (PPE). To cope with these present and future challenges, the “SMARTGRID” project described in this paper deploys an integrated wireless safety network infrastructure based on the integration of Bluetooth Low Energy (BLE) devices and passive radio frequency identification (RFID) tags designed to identify obstacles, workers, nearby vehicles and check if the right PPE is in use. With the aim of detecting workers at risk by scanning for passive RFID-integrated into PPE in danger areas, transmitting alerts to workers who wear them, tracking of near-misses and activating emergency stops, a deep analysis of the safety requirements of the obstacle detection system is shown in this study. Test programs have also been carried out on an experimental farm with detection ranging from 8 to 12 meters, proving that the system might represent a good solution for collision avoidance between autonomous vehicles and workers on foot.
URI: http://hdl.handle.net/2067/49525
ISSN: 2071-1050
DOI: https://doi.org/10.3390/su14159393
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:A1. Articolo in rivista

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