• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.51-59
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• 2005

To improve the quality of bus service, providing bus ravel time information to passenger through station screen. Generally, bus travel time information predict by using previous bus data such as neural network, Kalman filtering, and moving average algorithms. However, when they got a difficulty about bus travel time information because of the missing previous bus data, they use pattern data. Generally, nevertheless the difference of range is big. Hence in this research to calculate the bus travel time information when the bus information is missed, use queue detector's data which set up in link. The application of several factors which influence in bus link travel time, we used CORSIM Version 5.1 simulation package.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.833-839
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• 2019

Bus Information System (BIS) collects information related to the operation of buses and provides information to users through predictive algorithms. Method of predicting through recent information in same section reflects the traffic situation of the section, but cannot reflect the characteristics of the target line. The method of predicting the historical data at the same time zone is limited in forecasting peak time with high volatility of traffic flow. Therefore, we developed a pattern recognition bus arrival time prediction algorithm which could be overcome previous limitation. This method recognize the traffic pattern of target flow and select the most similar past traffic pattern. The results of this study were compared with the BIS arrival forecast information history of Seoul. RMSE of travel time between estimated and observed was approximately 35 seconds (40 seconds in BIS) at the off-peak time and 40 seconds (60 seconds in BIS) at the peak time. This means that there is data that can represent the current traffic situation in other time zones except for the same past time zone.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.1-9
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• 2009

Bus information system(BIS), as a part of the intelligent transportation system(ITS), is 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. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc. are not provided for the bus users because the proper bus arrival time predictive models are not used yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan. Thus, the purpose in this study is to investigate real-time bus traffic characteristic data for identifying the bus operation characteristics on the arterial under the study in the metropolitan City of Ulsan, analyze real-time bus traffic characteristic data on the ID locations of the arterial under the study, construct the optimal unit segment models for the unit segments which are the bus stop, node and travel section using the exponential smoothing, weighted smoothing and Kalman Filter methods, respectively, and finally suggest the optimal integrated model for predicting the real-time bus arrival time at the bus stop of the arterial under the study.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.336-338
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• 2013

본 논문에서는 도착예정지를 지나치고, 버스노선 안내 시스템과 지하철 노선 안내 시스템이 서로 분리되어 있어 지하철에서 버스로 환승하거나 그 반대의 경우에 시스템 사용에 있어 번거로운 문제점을 개선하기 위해 LBS 기반 도착예정지 알람 서비스 시스템을 설계하였다. 이를 위하여 Open API와 LBS를 분석하고, 도착예정지를 지나치지 않도록 하기 위해 LBS를 이용하여 도착예정지 알람 서비스 시스템을 설계하였다.

• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.149-159
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• 2005

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.247-255
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• 2014

This study supplements the existing bus information system's weakness which is a text-based system, transmits GUI based user request contents, design and implements the bus information system using smart-phone GPS. The existing bus information system had to install the terminals on the bus and take enormous expenses on maintenance with setting up the direction board on each bus station. The proposed system provides bus route and user location using the smart-phone map screen, finds the nearest bus station, indicates the bus route on map screen, applies our algorithm which increases accuracy of the bus arriving time, and provides route construction of the inner-cycle bus. The accuracy of the estimated bus arriving time has increased to about 88.71% which is 22.71% more than the existing system whose accuracy is 67% and improved into GUI form that the existing system was on text and table UI. Consequently, the upgraded bus information system uses the smart-phone GPS to supplement the existing bus information system and satisfies different requests of users.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.135-142
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• 2010

The convenient techniques for predicting the bus arrival time have used the data obtained from the buses belong to the same company only. Consequently, the conventional techniques have often failed to predict the bus arrival time at the downstream bus stops due to the lack of the data during congestion time period. The primary objective of this study is to overcome the weakness of the conventional techniques. The estimation model developed based on the data obtained from Bus Information System(BIS) and Bus management System(BMS). The proposed model predicts the bus arrival time at bus stops by using the data of all buses travelling same roadway section during the same time period. In the tests, the proposed model had a good accuracy of predicting the bus arrival time at the bus stops in terms of statistical measurements (e.g., root mean square error). Overall, the empirical results were very encouraging: the model maintains a prediction job during the morning and evening peak periods and delivers excellent results for the severely congested roadways that are of the most practical interest.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.500-507
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• 2008

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.5
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• pp.45-54
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• 2011

Currently various applications related to bus route are used on smart devices to obtain bus arrival times, and route information. However, applications are unable to provide various ways for users to provide their destination. This study has designed an algorithm based on user's six patterns. An Android application and a server that communicate with each other have been based on the algorithm. The applications and the server use the Google Maps service and location-based information to provide users with possible routes from the starting place to the destination. They also provide user's with users' current position and any transfer information. They provide practical and efficient information, and are easy to use.