Scalable cooperative perception for connected and automated driving

Cooperative perception (a.k.a. Collective perception or cooperative sensing) will allow Connected and Automated Vehicles (CAVs) to share information about detected objects. Cooperative perception improves the sensing accuracy, confidence and range of CAVs, and extends their perception of the driving...

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Detalles Bibliográficos
Autores: Thandavarayan, Gokulnath, Sepulcre, Miguel, Gozalvez, Javier, Coll-Perales, Baldomero
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad Miguel Hernández de Elche
Repositorio:REDIUMH. Depósito Digital de la UMH
OAI Identifier:oai:dspace.umh.es:11000/31368
Acceso en línea:https://hdl.handle.net/11000/31368
Access Level:acceso abierto
Palabra clave:Cooperative perception
Collective perception
Cooperative sensing
CPS
CPM
Connected automated vehicles
Autonomous vehicles
CAV
RSU
V2X
Vehicular networks
Congestion control
Redundancy mitigation
C-ITS
DCC
ETSI
CDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnología
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oai_identifier_str oai:dspace.umh.es:11000/31368
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repository_id_str
spelling Scalable cooperative perception for connected and automated drivingThandavarayan, GokulnathSepulcre, MiguelGozalvez, JavierColl-Perales, BaldomeroCooperative perceptionCollective perceptionCooperative sensingCPSCPMConnected automated vehiclesAutonomous vehiclesCAVRSUV2XVehicular networksCongestion controlRedundancy mitigationC-ITSDCCETSICDU::6 - Ciencias aplicadas::62 - Ingeniería. TecnologíaCooperative perception (a.k.a. Collective perception or cooperative sensing) will allow Connected and Automated Vehicles (CAVs) to share information about detected objects. Cooperative perception improves the sensing accuracy, confidence and range of CAVs, and extends their perception of the driving environment. First message generation rules based on the mobility and dynamics of detected objects have been proposed to decide when a cooperative perception message should be generated and what information it should include. Studies have shown that this type of generation rules can compromise the scalability of cooperative perception and vehicular networks, as they tend to transmit significant amounts of redundant information and generate small and frequent cooperative perception messages that increase the communications overhead. To combat these inefficiencies, this paper proposes and evaluates three techniques that combine, for the first time, baseline mobility-based generation rules for cooperative perception messages with mechanisms to control the redundancy and organize the information about detected objects in order to avoid the frequent transmission of small messages. This study demonstrates that the proposed techniques improve the perception of CAVs and reduce the information age. In addition, the techniques reduce the channel load and improve the scalability of cooperative perception services and vehicular networks. The study demonstrates that the most effective technique is based on: (1) first applying the generation rules to decide whether a cooperative perception message should be generated, (2) then applying redundancy control, and finally (3) organizing the information about all detected objects to avoid small and frequent messagesElsevierDepartamentos de la UMH::Ingeniería de Comunicaciones202420242023info:eu-repo/semantics/articleapplication/pdf14application/pdfhttps://hdl.handle.net/11000/31368reponame:REDIUMH. Depósito Digital de la UMHinstname:Universidad Miguel Hernández de ElcheIngléshttps://doi.org/10.1016/j.jnca.2023.103655info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/oai:dspace.umh.es:11000/313682026-05-27T13:36:21Z
dc.title.none.fl_str_mv Scalable cooperative perception for connected and automated driving
title Scalable cooperative perception for connected and automated driving
spellingShingle Scalable cooperative perception for connected and automated driving
Thandavarayan, Gokulnath
Cooperative perception
Collective perception
Cooperative sensing
CPS
CPM
Connected automated vehicles
Autonomous vehicles
CAV
RSU
V2X
Vehicular networks
Congestion control
Redundancy mitigation
C-ITS
DCC
ETSI
CDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnología
title_short Scalable cooperative perception for connected and automated driving
title_full Scalable cooperative perception for connected and automated driving
title_fullStr Scalable cooperative perception for connected and automated driving
title_full_unstemmed Scalable cooperative perception for connected and automated driving
title_sort Scalable cooperative perception for connected and automated driving
dc.creator.none.fl_str_mv Thandavarayan, Gokulnath
Sepulcre, Miguel
Gozalvez, Javier
Coll-Perales, Baldomero
author Thandavarayan, Gokulnath
author_facet Thandavarayan, Gokulnath
Sepulcre, Miguel
Gozalvez, Javier
Coll-Perales, Baldomero
author_role author
author2 Sepulcre, Miguel
Gozalvez, Javier
Coll-Perales, Baldomero
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamentos de la UMH::Ingeniería de Comunicaciones
dc.subject.none.fl_str_mv Cooperative perception
Collective perception
Cooperative sensing
CPS
CPM
Connected automated vehicles
Autonomous vehicles
CAV
RSU
V2X
Vehicular networks
Congestion control
Redundancy mitigation
C-ITS
DCC
ETSI
CDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnología
topic Cooperative perception
Collective perception
Cooperative sensing
CPS
CPM
Connected automated vehicles
Autonomous vehicles
CAV
RSU
V2X
Vehicular networks
Congestion control
Redundancy mitigation
C-ITS
DCC
ETSI
CDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnología
description Cooperative perception (a.k.a. Collective perception or cooperative sensing) will allow Connected and Automated Vehicles (CAVs) to share information about detected objects. Cooperative perception improves the sensing accuracy, confidence and range of CAVs, and extends their perception of the driving environment. First message generation rules based on the mobility and dynamics of detected objects have been proposed to decide when a cooperative perception message should be generated and what information it should include. Studies have shown that this type of generation rules can compromise the scalability of cooperative perception and vehicular networks, as they tend to transmit significant amounts of redundant information and generate small and frequent cooperative perception messages that increase the communications overhead. To combat these inefficiencies, this paper proposes and evaluates three techniques that combine, for the first time, baseline mobility-based generation rules for cooperative perception messages with mechanisms to control the redundancy and organize the information about detected objects in order to avoid the frequent transmission of small messages. This study demonstrates that the proposed techniques improve the perception of CAVs and reduce the information age. In addition, the techniques reduce the channel load and improve the scalability of cooperative perception services and vehicular networks. The study demonstrates that the most effective technique is based on: (1) first applying the generation rules to decide whether a cooperative perception message should be generated, (2) then applying redundancy control, and finally (3) organizing the information about all detected objects to avoid small and frequent messages
publishDate 2023
dc.date.none.fl_str_mv 2023
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/11000/31368
url https://hdl.handle.net/11000/31368
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1016/j.jnca.2023.103655
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv application/pdf
14
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:REDIUMH. Depósito Digital de la UMH
instname:Universidad Miguel Hernández de Elche
instname_str Universidad Miguel Hernández de Elche
reponame_str REDIUMH. Depósito Digital de la UMH
collection REDIUMH. Depósito Digital de la UMH
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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