CrowdParking: Crowdsourcing based parking navigation in autonomous driving era

Chao Zhu, Abbas Mehrabi, Yu Xiao, Yinghong Wen

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

225 Lataukset (Pure)

Abstrakti

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.

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 2019 21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019
KustantajaIEEE
Sivut1401-1405
Sivumäärä5
ISBN (elektroninen)9781728105635
DOI - pysyväislinkit
TilaJulkaistu - 1 syysk. 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Electromagnetics in Advanced Applications - Granada, Espanja
Kesto: 9 syysk. 201913 syysk. 2019
Konferenssinumero: 21

Conference

ConferenceInternational Conference on Electromagnetics in Advanced Applications
LyhennettäICEAA
Maa/AlueEspanja
KaupunkiGranada
Ajanjakso09/09/201913/09/2019

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