• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.7-18
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• 2002

To activate public transportation service, Bucheon City built Bus Information System based on Beacon type, and operates it for no.22 line. This research analyzes an effect of BIS operations, and mainly it analyzes far reliability evaluation of bus arrival time information and passenger satisfaction about BIS. As results of reliability evaluation of arrival time information service, it is proven to be practically inappropriate to use as arrival time data because it is not only travel time between each bus stop but also previous travel time history data. In order to improve this matter, neural network model was evaluated as the most outstanding one as result of experiment in applying current arrival time Prediction model. This research cannot help limiting for evaluation of operation effect in Bucheon City because there is no Bus Information System based on GPS type in Korea. For the future ITS model city, in the case of building ITS model city based on GPS type, it is possible to compare two systems relatively. In addition to that, fur the consideration of reliability of bus arrival time information, it is required to develop Predictable model and research factors that affect to bus operation.

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

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.24-29
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• 2023

In this paper, we propose a real-time bus arrival notification system using deep learning to guarantee movement rights for the visually impaired. In modern society, by using location information of public transportation, users can quickly obtain information about public transportation and use public transportation easily. However, since the existing public transportation information system is a visual system, the visually impaired cannot use it. In Korea, various laws have been amended since the 'Act on the Promotion of Transportation for the Vulnerable' was enacted in June 2012 as the Act on the Movement Rights of the Blind, but the visually impaired are experiencing inconvenience in using public transportation. In particular, from the standpoint of the visually impaired, it is impossible to determine whether the bus is coming soon, is coming now, or has already arrived with the current system. In this paper, we use deep learning technology to learn bus numbers and identify upcoming bus numbers. Finally, we propose a method to notify the visually impaired by voice that the bus is coming by using TTS technology.

• The Journal of the Korea Contents Association
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• v.6 no.5
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• pp.14-19
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• 2006

In this paper, we describe an arrival time guidance system of circular vehicles using GPS, CDMA and TCP/IP technology. The on-board equipment consists of a GPS receiver and a PDA phone. The on-board equipment sends the current position data of the vehicle to the positioning server via CDMA and Internet. The server predicts the arrival time to the next bus-stop. Any user can lookup the current position and the predicted arrival time of the vehicle utilizing his mobile phone, PDA phone, or Web.

• KIEAE Journal
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• v.3 no.4
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• pp.33-36
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• 2003

Bus station is a public space which many people use and various activities are occurred in urban life. Main activities are waiting for departure or passengers with the feelings of joys and sorrows. Also sound information including announcing message of arrival and departure are to be considered carefully. Considering these roles of bus station, creating acoustic amenity is a prerequisite to the spaces. In this study, the spaces of bus station were classified into 4 spaces such as approaching path, waiting palace, departure and arrival platform. Observation survey was conducted to extract various activities in the view point of sound in each space. And subjective response was analyzed before and after introducing prepared sounds.

• The Journal of Information Technology
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• v.8 no.1
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• pp.83-93
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• 2005

This paper again to present position of a bus that is running in bus government organization small grasp and Can instruct control about the vehicles progress speed in government organization small to bus driver. Therefore, Inform a bus that own wants to ordinary people who carry transfer communication terminal is situated to where present, ad Do by purpose that offer system that inform running information of a bus to ARS and FAX, internet and ordinary people through PC communication. Also, Intelligence style bus control system that see also includes function that do as can guide arrival expectation depot automatically without driver's manufacturing when run a bus.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1203-1210
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• 2018

As the use of public transportation is increasing, a service considering the convenience of passengers is being launched utilizing the Internet (IoT) data collected through the bus information system. However, the bus information system only provides limited information such as the current location of the bus (GPS) and the expected arrival time at the stop. Additional IoT sensor information is needed to provide various services for the safety and convenience of passengers. In this paper, to improve the safety and convenience of passengers, we have added the boarding doors imaging sensor, temperature and humidity sensors, and sensor for measuring the number of passengers. The proposed IoT bus system can attach various sensors to buses to provide high-quality safety services to passengers.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.1-11
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• 2008

As bus is realized by economical, environmental transportation that is available mass transport than car, various policy for improvement of services is achieved. As innovative public transportation systems like BMS (Bus Management System) have established, it is possible to manage bus service efficiently. However, the present bus service management system mainly focuses on enhancing service reliability represented by schedule adherence index. This study discusses the necessity of a special management for bus bunching phenomena at stops, and develops two kinds of bus bunching indices based on the Number of Berth and the Average Bus Arrival Rate. The bus bunching indices were measured by utilizing the bus operational information from BMS at the Seoul TOPIS(Transportation & Information Service). In order to evaluate the sensitivity of the Indices, the indices were applied to two different bus groups: buses on exclusive bus median lane, and regular (shared) lanes. As analysis result, is bunching as is near in downtown and is bunching to peak time morning than the afternoon. Compared with the schedule adherence index, the suggested indices were proved as an efficient complementary indices in the evaluation of the bus operational performance. The results of index comparison between exclusive bus median lane and shared lanes can promote the expansion of exclusive bus median lane. Moreover, it can also be used as a reference in deciding bus station scale including the Number of Berth and the route adjustment plan.