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LoRa Network based Parking Dispatching System : Queuing Theory and Q-learning ApproachLoRa Network based Parking Dispatching System : Queuing Theory and Q-learning Approach

Other Titles
LoRa Network based Parking Dispatching System : Queuing Theory and Q-learning Approach
Authors
조영호서영건정대율
Issue Date
2017
Publisher
한국디지털콘텐츠학회
Keywords
Parking; LoRa; IoT; Queuing Theory; Q-learning system; 주차; LoRa; 사물통신; 큐잉 이론; 큐러닝 시스템
Citation
디지털콘텐츠학회논문지, v.18, no.7, pp 1443 - 1450
Pages
8
Indexed
KCI
Journal Title
디지털콘텐츠학회논문지
Volume
18
Number
7
Start Page
1443
End Page
1450
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/14334
DOI
10.9728/dcs.2017.18.7.1443
ISSN
1598-2009
2287-738X
Abstract
The purpose of this study is to develop an intelligent parking dispatching system based on LoRa network technology. During the local festival, many tourists come into the festival site simultaneously after sunset. To handle the traffic jam and parking dispatching, many traffic management staffs are engaged in the main road to guide the cars to available parking lots. Nevertheless, the traffic problems are more serious at the peak time of festival. Such parking dispatching problems are complex and real-time traffic information dependent. We used Queuing theory to predict inbound traffics and to measure parking service performance. Q-learning algorithm is used to find fastest routes and dispatch the vehicles efficiently to the available parking lots.
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Jeong, Dae Yul
경영대학 (경영정보학과)
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