CrowdParking: Crowdsourcing based parking navigation in autonomous driving era

Chao Zhu, Abbas Mehrabi, Yu Xiao, Yinghong Wen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 2019 21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1401-1405
Number of pages5
ISBN (Electronic)9781728105635
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes
Event21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019 - Granada, Spain
Duration: 9 Sept 201913 Sept 2019

Publication series

NameProceedings of the 2019 21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019

Conference

Conference21st International Conference on Electromagnetics in Advanced Applications, ICEAA 2019
Country/TerritorySpain
CityGranada
Period9/09/1913/09/19

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