• Journal of KIISE:Databases
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• v.33 no.7
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• pp.655-667
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• 2006

Due to the rapid development in mobile communication technologies, the usage of mobile devices such as cellular phones and PDAs becomes increasingly popular. One of the best ways to maximize the usability of mobile devices is to make them aware of their current locations and the locations of other fixed and mobile objects. In this paper, we propose a cost-effective Bus Information System, ACE-BIS, which utilizes a mobile device to retrieve the bus routes to reach a destination from the current location. To accomplish this task, ACE-BIS maintains a small amount of information on bus stops and bus routes in a mobile device and runs a heuristic routing algorithm based on such information. When a user asks more accurate route information or calls for a 'leave later query', ACE-BIS entrusts the task to a server into which real-time traffic and bus location information is being collected. By separating the roles into a mobile device and a server, ACE-BIS is able to provide bus routes at the lowest cost for wireless communications, without imposing much burden to a server. The results of extensive experiments revealed that ACE-BIS is effective and scalable in most experimental settings.

• Journal of the Economic Geographical Society of Korea
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• v.18 no.4
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• pp.539-555
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• 2015

This study proposes the methodology for measuring the time-distance accessibility on the Seoul bus system based on the T-card transaction databases and analyzes the results. T-card transaction databases contain the time/space information of each passenger's locations and times of the departure, transfers, and destination. We introduce the bus network graph and develop the algorithms for time-distance accessibility measurement. We account the average speed based on each passenger's get-in and getoff information in the T-card data as well as the average transfer time from the trip chain transactions. Employing the modified Floyd APSP algorithm, the shortest time distance between each pair of bus stops has been accounted. The graph-theoretic nodal accessibility has been given by the sum of the inverse time distance to all other nodes on the network. The results and spatial patterns are analyzed. This study is the first attempt to measure the time-distance accessibility for such a large transport network as the Seoul bus system consists of 34,934 bus stops on the 600 bus routes, and each bus route can have different properties in terms of speed limit, number of lanes, and traffic signal systems, and thus has great significance in the accessibility measurement studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.595-603
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• 2019

To alleviate the demand on private car that is constantly increasing, Busan Metropolitan City (BMC) has established Bus Rapid Transit (BRT) to revitalize public transportation. But there are no unified lane system between BRT and general bus stations, which makes off-lane turning general bus to contribute to congestion. And as the bottleneck phenomenon at entrance/exit accelerates the congestion, there has been huge dissatisfaction among commuting drivers. Therefore, this study identifies efficient methods to operate better through measuring civilian awareness. We evaluate both satisfaction and drawbacks on BRT service with Importance-Performance Analysis (IPA). We first distinguish the groups by the awareness on BRT and their main transit usage, and then clarify the difference between the groups. And as a result, the group who is positive to BRT and uses buses often demands improvement in bus indoor comfort and curbing jaywalking. On the other hand, group who is negative to BRT and uses private cars often demands improvement in lane changing and the moving speed of private cars. We next examines the groups with MDPREF, one method of Multidimensional Scaling (MDS). And we have clarified that the evaluating criteria and the individual attributes of the groups corresponds very well.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.153-166
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• 1998

본 연구에서는 도시 가로망에서의 구간 통행시간을 예측하기 위하여 time-frequency 분석의 일종인 웨이브렛변환과 RBF신경망 모형을 이용한 예측모형을 개발하였다. 웨이브렛 변환을 이용한 시계열 자료 분석을 통해서 통행시간에 내재되어 있는 다양한 패턴의 특징을 추출함으로써 오전/오후의 첨두현상, 신호교차로의 현시주기 등 주기적으로 발생되는 요인들에 의해서 통행시간 시계열 자료의 패턴에 나타나는 규칙성을 분석해 내었다. 분석된 패턴정보에 대한 규명은 카오스 이론을 근간으로한 시간지연좌표를 이용하여 시계열 자료의 규칙성을 시각적으로 판별하여 예측모형 구축에 활용하도록 하였다. 또, RBF신경망을 이용하여 예측범위의 공간적/시간적 확대에 따른 모형 구축에 소요되는 시간을 최소화하도록 하였으며, 시내버스 노선의 정류장간 운행시간 예측을 통해서 기존 연구에서 제기되었던 현실세계의 단순화, 다단계 예측시 정확성 등의 문제를 해결하였다. 예측실험결과 웨이브렛 변환을 데이터의 전처리 과정에 삽입하여 링크 통행시간의 패턴정보 예측에 활용할 경우, 기존의 예측모형에 비해서 훨씬 정확한 예측이 가능한 것으로 나타났으며, RBF 신경망은 짧은 학습시간에도 불구하고 역전파 신경망보다 우수한 예측력을 갖고 있는 것으로 밝혀졌다.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.943-946
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• 2018

본 논문은 공공데이터 API를 활용한 ITS(Intelligent Transport System)를 구현하여, 버스 승하차 관련 문제를 개선하는 버스 승하차 사전 알림 시스템에 관한 것이다. 수도권 및 대도시 전체 버스 관련 민원신고 중 가장 많이 차지하는 부분이 버스의 정류장 무정차 통과 및 승차거부 문제다. 이를 해결하기 위해 사전에 승객의 승하차 여부를 버스 운전사에게 미리 알리는 시스템을 제안한다. 이 시스템은 승객용 애플리케이션, 중앙 서버 그리고 버스에 설치되는 디바이스로 구성되어 있으며 예비 승하차 승객이 애플리케이션을 이용하여 자신이 원하는 버스에 대한 정보를 MQTT Broker를 이용하여 서버에 보내고 서버는 해당 버스의 정보와 현재 노선의 운행 현황을 주기적으로 확인하여 요청 정류장 이전에 도달하였을 때 버스 운전자 측 디바이스에 신호를 보내어 버스 운전자가 예비 승하차 승객이 있음을 사전에 알 수 있게 한다. 이 시스템을 통해 무정차 및 승차거부 문제를 근본적으로 해결하여 사용자 편의 승객 안전 일반 차량 운전자 안전 도로 교통 안정화를 도모한다.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.97-108
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• 2006

At present, Korean many cities depend on subjective judgements of experts to estimate the number of bus-stops and inter-stop space. To get reliable results by using more objective procedure, we search for old studies and models, but they don't concern alighting demands and a random demand distributions. Our study recognize and overcome these limitation. We devide the demand into boarding and alighting demands, and define the model that can estimate flexibly optimal number of bus-stop and inter-stop space on each segment by the demand distribution. Also we apply this new model to a simple example route having various demand distributions As a result, the number of bus-stop on each segment can be estimate flexibly in proportion to boarding or alighting demand by using this model.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.666-674
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• 2007

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.1-10
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• 2009

Bus delay time is occurred as the result of traffic condition and important factor to predict bus arrival time. In this paper, transition probability matrixes between bus stops are made by using Markov Chain and it is predicted bus delay time with them. As the results of study, it is confirmed a possibility of adapting the assumption which it has same bus transition probability between stops through paired-samples T-test and overcame the limitation of exiting studies in case there is no scheduled bus arrival time for each stops with using bus interval time. Therefore it will be possible to predict bus arrival time with Markov Chain.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.603-611
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• 2020

This study collected and analyzed transportation card data in order to better understand the operation and usage of city buses in Ulsan Metropolitan City in Korea. The analysis used quantitative and qualitative indicators according to the characteristics of the data, and also the categories were classified as general status, operational status, and satisfaction. The existing city bus survey method has limitations in terms of survey scale and in the survey process itself, which incurs various types of errors as well as requiring a lot of time and money to conduct. In particular, the bus means indicators calculated using transportation card data were analyzed to compensate for the shortcomings of the existing operational status survey methods that rely entirely on site surveys. The city bus index calculated by using the transportation card data involves quantitative operation status data related to the user, and this results in the advantage of being able to conduct a complete survey without any data loss in the data collection process. We took the transportation card data from the entire city bus network of Ulsan Metropolitan City on Wednesday April 3, 2019. The data included information about passenger numbers/types, bus types, bus stops, branches, bus operators, transfer information, and so on. From the data analysis, it was found that a total of 234,477 people used the city bus on the one day, of whom 88.6% were adults and 11.4% were students. In addition, the stop with the most passengers boarding and alighting was Industrial Tower (10,861 people), A total of 20,909 passengers got on and off during the peak evening period of 5 PM to 7 PM, and 13,903 passengers got on and off the No. 401 bus route. In addition, the top 26 routes in terms of the highest number of passengers occupied 50% of the total passengers, and the top five bus companies carried more than 70% of passengers, while 62.46% of the total routes carried less than 500 passengers per day. Overall, it can be said that this study has great significance in that it confirmed the possibility of replacing the existing survey method by analyzing city bus use by using transportation card data for Ulsan Metropolitan City. However, due to limitations in the collection of available data, analysis was performed only on one matched data, attempts to analyze time series data were not made, and the scope of analysis was limited because of not considering a methodology for efficiently analyzing large amounts of real-time data.