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

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

초록

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.

키워드

Parking; LoRa; IoT; Queuing Theory; Q-learning system; 주차; LoRa; 사물통신; 큐잉 이론; 큐러닝 시스템
제목
LoRa Network based Parking Dispatching System : Queuing Theory and Q-learning Approach
제목 (타언어)
LoRa Network based Parking Dispatching System : Queuing Theory and Q-learning Approach
저자
조영호; 서영건; 정대율
DOI
10.9728/dcs.2017.18.7.1443
발행일
2017
저널명
디지털콘텐츠학회논문지
권
18
호
7
페이지
1443 ~ 1450