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CrowdParking: Crowdsourcing based parking navigation in autonomous driving era

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Zhu, Chao
dc.contributor.author Mehrabi, Abbas
dc.contributor.author Xiao, Yu
dc.contributor.author Wen, Yinghong
dc.date.accessioned 2020-01-02T14:04:25Z
dc.date.available 2020-01-02T14:04:25Z
dc.date.issued 2019-09-01
dc.identifier.citation Zhu , C , Mehrabi , A , Xiao , Y & Wen , Y 2019 , CrowdParking: Crowdsourcing based parking navigation in autonomous driving era . in Proceedings of the 2019 21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019 . , 8879201 , IEEE , pp. 1401-1405 , International Conference on Electromagnetics in Advanced Applications , Granada , Spain , 09/09/2019 . https://doi.org/10.1109/ICEAA.2019.8879201 en
dc.identifier.isbn 9781728105635
dc.identifier.other PURE UUID: 940120d4-0f6c-41dc-b43b-0feb3ec2f29d
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/crowdparking-crowdsourcing-based-parking-navigation-in-autonomous-driving-era(940120d4-0f6c-41dc-b43b-0feb3ec2f29d).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85074905959&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/38942515/SCI_Zhu_et.al_CrowdParking.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/42133
dc.description.abstract Finding a free road side parking in urban area is considered as one of the most challenging driving tasks, especially for the autonomous vehicles with limited sight (e.g. short range sensing) and brain (compared with human beings). To assist autonomous vehicle parking in urban area, we propose a novel parking scheme CrowdParking, which applies crowdsourcing and vehicular fog computing to collect parking information from vehicles, locate free parking spaces from crowdsourced data. We also explore the variation of parking availability from a real world data set and find that the availability of specific parking lot has certain relationship with the traffic condition of nearby roads. Based on the observations, we propose the vision of estimating the parking availability with taking into account the traffic condition in neighborhood. en
dc.format.extent 5
dc.format.extent 1401-1405
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartof International Conference on Electromagnetics in Advanced Applications en
dc.relation.ispartofseries Proceedings of the 2019 21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019 en
dc.rights openAccess en
dc.subject.other Radiation en
dc.subject.other Modelling and Simulation en
dc.subject.other Statistics and Probability en
dc.subject.other Instrumentation en
dc.subject.other Computer Networks and Communications en
dc.subject.other Geophysics en
dc.subject.other 113 Computer and information sciences en
dc.title CrowdParking: Crowdsourcing based parking navigation in autonomous driving era en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department Mobile Cloud Computing
dc.contributor.department Professorship Ylä-Jääski Antti
dc.contributor.department Beijing Jiaotong University
dc.contributor.department Department of Communications and Networking en
dc.contributor.department Department of Computer Science en
dc.subject.keyword Radiation
dc.subject.keyword Modelling and Simulation
dc.subject.keyword Statistics and Probability
dc.subject.keyword Instrumentation
dc.subject.keyword Computer Networks and Communications
dc.subject.keyword Geophysics
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-202001021244
dc.identifier.doi 10.1109/ICEAA.2019.8879201
dc.type.version acceptedVersion


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