SParking: A win-win data-driven contract parking sharing system

Xin Zhu, Shuai Wang, Baoshen Guo, Taiwei Ling, Ziyi Zhou, Lai Tu, Tian He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With a rapid growth of vehicles in modern cities, searching for a parking space becomes difficult for drivers especially in rush hours. To alleviate parking difficulties and make the most of urban parking resources, contract parking sharing services allow drivers to pay for parking under the consent of owners, reaching a win-win situation. Contract parking sharing services, however, have not yet been prevailingly adopted due to the dynamic parking time which leads to uncertainties for sharing. Thanks to the Internet of things technique, most of modern parking lots record vehicles' fine-grained parking data including entry and exit timestamps for billing purposes. Leveraging the parking data, we analyze and exploit available vacant contract parking spaces. We propose SParking, a <u>s</u>hared contract <u>parking</u> system with a win-win data-driven scheduling. SParking consists of (i) a parking time prediction model to exploit reliable periods of free parking spaces and (ii) an optimal scheduling model to allocate free parking spaces to drivers. To verify the effectiveness of SParking, we evaluate our design on seven-month real-world parking data involved with 368 parking lots and 14,704 parking spaces in Wuhan, China. The experimental results show that SParking achieves more than 90% of accuracy in parking time prediction and the average utilization rate of contract parking spaces is improved by 35%.

Original languageEnglish (US)
Title of host publicationUbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery
Pages596-604
Number of pages9
ISBN (Electronic)9781450380768
DOIs
StatePublished - Sep 10 2020
Event2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2020 - Virtual, Online, Mexico
Duration: Sep 12 2020Sep 17 2020

Publication series

NameUbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers

Conference

Conference2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2020
CountryMexico
CityVirtual, Online
Period9/12/209/17/20

Bibliographical note

Funding Information:
This work was supported in part by National Natural Science Foundation of China under Grant No. 6167219, Natural Science Foundation of Jiangsu Province under Grant No. BK20190336, and China National Key R&D Program 2018YFB2100302.

Keywords

  • online scheduling
  • parking sharing
  • usage prediction

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