한국해양대학교

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가중이동평균법을 이용한 그룹별 버스노선 DB의 버스정류장 서비스시간 예측에 관한 연구

Title
가중이동평균법을 이용한 그룹별 버스노선 DB의 버스정류장 서비스시간 예측에 관한 연구
Alternative Title
Predicting the Time-Series BSST of Grouped Route DB using the Weighted Moving Average Method
Author(s)
허인석
Publication Year
2008
Publisher
한국해양대학교 대학원
URI
http://kmou.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002174514
http://repository.kmou.ac.kr/handle/2014.oak/8556
Abstract
Generally, the bus stop service time (BSST) means the

time which the bus spends at the bus stop from the time when the bus arrives at the bus stop to the time when the bus departs the bus stop. However, the BSST shows

different depending on the bus stop, the time period, or the bus route, because the number of the bus users is changing. So it is very important to predict accurately the BSST for consideration or the bus information system(BIS), one of the most advanced public transportation systems which provide the real-time bus traffic information for the users waiting the buses at the bus stop.

Since 2000’s the bus information system(BIS) has been continuously introduced into the bus transportation systems the year of since 2000 in the cities, and also its extension taken into consideration in some of the cities which already imported the bus information system. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc., have not been provided for the bus users because the proper BSST are not predicted yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan.

Thus, the purposes in this study are to analyze the real-time BSST data for identifying the bus travel characteristics at the bus stop under the study in the metropolitan City of Ulsan, to compare the BSST of time-series DB by the weighted moving average method(WMAM1) with that of grouped route DB by the weighted moving average method(WMAM2), and finally to suggest the weighted moving average method for more accurately predicting the time-series BSST at the bus stop of the arterial under the study.

As a result, the weighted moving average method(WMAM2) which had been uses to predict the BSST of the grouped route DB depending on the grouped route service time was found to be better than the method(WMAM1) for predicted the BSST of existing DB depending on the time-series sequence.
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토목환경공학과 > Thesis
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