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Communication Network Architectures for Driver Assistance Systems

Autonomous Driver Assistance Systems (ADAS) are of increasing importance to warn vehicle drivers of potential dangerous situations. In this paper, we propose one system to warn drivers of the presence of pedestrians crossing the road. The considered ADAS adopts a CNN-based pedestrian detector (PD) u...

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Autores principales: Giuliano, Romeo, Mazzenga, Franco, Innocenti, Eros, Fallucchi, Francesca, Habib, Ibrahim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8537193/
https://www.ncbi.nlm.nih.gov/pubmed/34696080
http://dx.doi.org/10.3390/s21206867
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author Giuliano, Romeo
Mazzenga, Franco
Innocenti, Eros
Fallucchi, Francesca
Habib, Ibrahim
author_facet Giuliano, Romeo
Mazzenga, Franco
Innocenti, Eros
Fallucchi, Francesca
Habib, Ibrahim
author_sort Giuliano, Romeo
collection PubMed
description Autonomous Driver Assistance Systems (ADAS) are of increasing importance to warn vehicle drivers of potential dangerous situations. In this paper, we propose one system to warn drivers of the presence of pedestrians crossing the road. The considered ADAS adopts a CNN-based pedestrian detector (PD) using the images captured from a local camera and to generate alarms. Warning messages are then forwarded to vehicle drivers approaching the crossroad by means of a communication infrastructure using public radio networks and/or local area wireless technologies. Three possible communication architectures for ADAS are presented and analyzed in this paper. One format for the alert message is also presented. Performance of the PDs are analyzed in terms of accuracy, precision, and recall. Results show that the accuracy of the PD varies from [Formula: see text] to [Formula: see text] depending on the resolution of the videos. The effectiveness of each of the considered communication solutions for ADAS is evaluated in terms of the time required to forward the alert message to drivers. The overall latency including the PD processing and the alert communication time is then used to define the vehicle braking curve, which is required to avoid collision with the pedestrian at the crossroad.
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spelling pubmed-85371932021-10-24 Communication Network Architectures for Driver Assistance Systems Giuliano, Romeo Mazzenga, Franco Innocenti, Eros Fallucchi, Francesca Habib, Ibrahim Sensors (Basel) Article Autonomous Driver Assistance Systems (ADAS) are of increasing importance to warn vehicle drivers of potential dangerous situations. In this paper, we propose one system to warn drivers of the presence of pedestrians crossing the road. The considered ADAS adopts a CNN-based pedestrian detector (PD) using the images captured from a local camera and to generate alarms. Warning messages are then forwarded to vehicle drivers approaching the crossroad by means of a communication infrastructure using public radio networks and/or local area wireless technologies. Three possible communication architectures for ADAS are presented and analyzed in this paper. One format for the alert message is also presented. Performance of the PDs are analyzed in terms of accuracy, precision, and recall. Results show that the accuracy of the PD varies from [Formula: see text] to [Formula: see text] depending on the resolution of the videos. The effectiveness of each of the considered communication solutions for ADAS is evaluated in terms of the time required to forward the alert message to drivers. The overall latency including the PD processing and the alert communication time is then used to define the vehicle braking curve, which is required to avoid collision with the pedestrian at the crossroad. MDPI 2021-10-16 /pmc/articles/PMC8537193/ /pubmed/34696080 http://dx.doi.org/10.3390/s21206867 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Giuliano, Romeo
Mazzenga, Franco
Innocenti, Eros
Fallucchi, Francesca
Habib, Ibrahim
Communication Network Architectures for Driver Assistance Systems
title Communication Network Architectures for Driver Assistance Systems
title_full Communication Network Architectures for Driver Assistance Systems
title_fullStr Communication Network Architectures for Driver Assistance Systems
title_full_unstemmed Communication Network Architectures for Driver Assistance Systems
title_short Communication Network Architectures for Driver Assistance Systems
title_sort communication network architectures for driver assistance systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8537193/
https://www.ncbi.nlm.nih.gov/pubmed/34696080
http://dx.doi.org/10.3390/s21206867
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