Residential College | false |
Status | 已發表Published |
Community based parking: Finding and predicting available parking spaces based on the Internet of Things and crowdsensing | |
Li, Bo1; Hou, Fen2; Ding, Hongwei1; Wu, Hao1 | |
2021-12-01 | |
Source Publication | Computers and Industrial Engineering |
ABS Journal Level | 2 |
ISSN | 0360-8352 |
Volume | 162Pages:107755 |
Abstract | In smart parking guidance systems, the ability to estimate the availability of vacant parking spaces is important to make effective guidance. In this paper, we propose a general architecture for building crowdsensing-based parking guiding system, in which the occupancy state of parking lots can be detected by smart vehicles equipped with sensors and wireless communication devices, or by parking meters and parking fee-paying terminals, and the state information can be used to estimate the probability of finding available spaces for incoming smart vehicles. Five representative scenarios that can be used in such a framework were investigated. The problem to estimate the availability of parking spaces in each scenario was modeled as an M/M/c/c queuing problem with closed-form analytical solutions. The scenarios were validated in a simulation platform and their performance in various parking environments was investigated. Experimental results revealed that the crowdsensing-based parking prediction method can lead to 30.91% or more relative improvement on average estimation error than steady-state prediction in typical parking environments. |
Keyword | Crowd Sensing Queuing Model Simulation Smart Parking Guidance System |
DOI | 10.1016/j.cie.2021.107755 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Computer Science ; Engineering |
WOS Subject | Computer Science, Interdisciplinary Applications ; Engineering, Industrial |
WOS ID | WOS:000720348400014 |
Publisher | PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND |
Scopus ID | 2-s2.0-85118180637 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING Faculty of Science and Technology |
Corresponding Author | Li, Bo |
Affiliation | 1.School of Information Science and Engineering, Yunnan University, Kunming, 650091, China 2.Department of Electrical and Computer Engineering, University of Macau, Macau, China |
Recommended Citation GB/T 7714 | Li, Bo,Hou, Fen,Ding, Hongwei,et al. Community based parking: Finding and predicting available parking spaces based on the Internet of Things and crowdsensing[J]. Computers and Industrial Engineering, 2021, 162, 107755. |
APA | Li, Bo., Hou, Fen., Ding, Hongwei., & Wu, Hao (2021). Community based parking: Finding and predicting available parking spaces based on the Internet of Things and crowdsensing. Computers and Industrial Engineering, 162, 107755. |
MLA | Li, Bo,et al."Community based parking: Finding and predicting available parking spaces based on the Internet of Things and crowdsensing".Computers and Industrial Engineering 162(2021):107755. |
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