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dc.contributor.authorHidalgo, Carlos
dc.contributor.authorLattarulo, Ray
dc.contributor.authorFlores, Carlos
dc.contributor.authorPérez Rastelli, Joshué
dc.date.accessioned2021-04-19T09:27:26Z
dc.date.available2021-04-19T09:27:26Z
dc.date.issued2021-04-08
dc.identifier.citationHidalgo, Carlos; Lattarulo, Ray; Flores, Carlos; Pérez Rastelli, Joshué. 2021. "Platoon Merging Approach Based on Hybrid Trajectory Planning and CACC Strategies" Sensors 21, no. 8: 2626. https://doi.org/10.3390/s21082626en
dc.identifier.issn14248220en
dc.identifier.urihttp://hdl.handle.net/11556/1116
dc.description.abstractCurrently, the increase of transport demands along with the limited capacity of the road network have increased traffic congestion in urban and highway scenarios. Technologies such as Cooperative Adaptive Cruise Control (CACC) emerge as efficient solutions. However, a higher level of cooperation among multiple vehicle platoons is needed to improve, effectively, the traffic flow. In this paper, a global solution to merge two platoons is presented. This approach combines: (i) a longitudinal controller based on a feed-back/feed-forward architecture focusing on providing CACC capacities and (ii) hybrid trajectory planning to merge platooning on straight paths. Experiments were performed using Tecnalia’s previous basis. These are the AUDRIC modular architecture for automated driving and the highly reliable simulation environment DYNACAR. A simulation test case was conducted using five vehicles, two of them executing the merging and three opening the gap to the upcoming vehicles. The results showed the good performance of both domains, longitudinal and lateral, merging multiple vehicles while ensuring safety and comfort and without propagating speed changes.en
dc.description.sponsorshipThis research was supported by the European Project SHOW from the Horizon 2020 program under Grant Agreement No. 875530.en
dc.language.isoengen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titlePlatoon Merging Approach Based on Hybrid Trajectory Planning and CACC Strategiesen
dc.typearticleen
dc.identifier.doi10.3390/s21082626en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/875530/EU/SHared automation Operating models for Worldwide adoption/SHOWen
dc.rights.accessRightsopenAccessen
dc.subject.keywordsHybrid trajectory planning approachen
dc.subject.keywordsCACCen
dc.subject.keywordsCooperative mergingen
dc.identifier.essn1424-8220en
dc.issue.number8en
dc.journal.titleSensorsen
dc.page.initial2626en
dc.volume.number21en


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    Attribution 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution 4.0 International