• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.179-186
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• 2014

This study attempted to identify the characteristics of transfer trips between subways and buses in Daegu city and to analyze various impact factors that influence the number of transfer trips using a multiple regression analysis. Based on the results, this study aims to propose some policy implications to improve the operation efficiency of a transit center. As a result, it is found that the number of transfer trips is inversely proportional to transfer time, while directly proportional to the number of connected bus routes, subway's spatial location, and bus route connection index. Specifically, it is found that the number of transfer trips are mostly affected by bus route connection index.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.53-62
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• 2006

The aim of this paper is to analyze the changes in the travel pattern of public transit users, service satisfaction before and after public transportation system reform in Daegu. For this purpose, we conducted a survey of people on public transit users and the results of study are as follows : First, it was found that transfer trip had increased, especially concerning the changes of travel pattern from bus trip to the transfer trip between the bus and subway. Because it makes a financial sense to transfer based on free charge transfer system. Secondly, the transfer satisfaction was improved for public transit users, but they are still reluctant to use transfer system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.57-66
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• 2012

This study intended to evaluate the operational performance change from the introduction of the bus signal priority system using the field data. To complete the objective, travel time and volume data were collected from the before and after study, then the distribution of individual vehicle's travel time and the difference of travel time and traffic volume were compared respectively. Analysis results showed that no significant volume change was observed from both passenger vehicle and bus for the major and cross streets. It was identified that the quality of travel time distributions of passenger vehicle and bus was improved after introducing the bus signal priority system. In terms of average speed, passenger car in a major direction increased by 6.5% and bus increased by 10.5% in general. Statistical tests showed that those speed differences were statistically significant at the 95% of confidence level. The results of this paper will be a good source for further research in the area of bus signal priority control.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.672-675
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• 2009

BMS(Bus Management System)의 핵심인 버스도착예정시간을 산출하는 데 있어서 기존 대부분의 도시에서는 시계열 모형의 이동평균법, 칼만필터링 등으로 버스도착예정시간을 예측하고 있으나 이는 급격한 통행량의 변화 또는 급작스러운 사고, 신호체계 등에 적응 할 수 없다. 따라서 본 논문에서는 주변 도로의 통행량에 따른 버스의 정류장 도착시간을 예측하는 방법을 제안 한다. 주변 도로의 통행량과 실제 버스의 통행시간을 실측하여 기록, 학습하고 모델링하여 미래의 버스의 운행시간을 예측하는 방법이다. 또, 이동평균법에 의한 버스도착시간 예측결과와 본 논문에서 제안하는 결과와 비교, 분석하였다.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.43-54
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• 2000

이 연구는 버스정보 시스템 설계에 필요한 운행시격 결정과 통행시간 예측을 위한 알고리즘 개발을 다룬다. 운행시격 결정 문제는 버스와 같은 대중교통 수단을 운영하는데 중요한 요소 중에 하나이다. 기존 연구는 버스 운행비용과 승객비용의 합을 최소로 하는 운행시 격을 찾는데 초점을 두고 이다. 이때 승객비용이란 승객 대기비용과 승객 교통비용의 합으로 이루어진다. 그런데 우리나라와 같이 버스회사 수입이 전액 운행수입에만 의존하는 경우엔 이러한 접근 방식이 타당하지 않다. 기존의 방식과 다르게 승객비용으로 승객 이탈비용을 사용하여 버스의 최적 운행시 격을 구하는 것이 이 연구의 목적이다. 먼저 정류장이 하나인 경우에 대해 해석적 방법으로 풀고, 정류장이 여러 개인 경우에 대해서는 시뮬레이션 기법을 적용한다. 또한 이 연구는 신뢰성이 높고 정확한 통행시간 예측정보를 산출하기 위해 2 단계 예측 기법과 전문가시스템을 이용하는 자료융합 알고리즘을 개발한다. 정확한 정보를 제공하려면 교통정보 수집원을 통해 얻는 자료가 정확해야 하고, 또한 교통상황 변화에 따라 실시간으로 통행시간을 예측하는 것이 필요하다. 이 연구는 AVL(Automatic Vehicle Location)시스템을 이용한 버스정보시스템에서 실시간 데이터와 과거 데이터를 융합하여 통행시간을 예측하는 알고리즘을 개발한다. AVL 데이터를 수집하는 과정에서는 경제성을 고려하여 데이터를 수집한다. 그리고, 버스의 운행관리와 정확한 도착예정시간을 예측하기 위해 AVL시스템을 통해 얻은 데이터의 패턴을 분석하고 유고상황을 감지한다.

• 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.33 no.3
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• pp.1115-1122
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• 2013

Recently the demands for traffic information tend to increase, and travel time might one of the most important traffic information. To effectively estimate exact travel time, highly reliable traffic data collection is required. BIS(Bus Information System) data would be useful for the estimation of the route travel time because BIS is collecting data for the bus travel time on the main road of the city on real-time basis. Traditionally use of BIS data has been limited to the realm of bus operating but it has not been used for a variety of traffic categories. Therefore, this study estimates a route travel time on road networks in urban areas on the basis of real-time data of BIS and then eventually constructs regression models. These models use an explanatory variable that corresponds to bus travel time excluding service time at the bus stop. The results show that the coefficient of determination for the constructed regression model is more than 0.950. As a result of T-test performance with assistance from collected data and estimated model values, it is likely that the model is statistically significant with a confidence level of 95%. It is generally found that the estimation for the exact travel time on real-time basis is plausible if the BIS data is used.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.147-157
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• 2013

This study developed the transit transfer mode choice model aimed Daegu transit users using multinomial logit model. Dependent variables of estimating multinomial logit model were transit transfer modes such as bus to bus, bus to subway, subway to subway, bus to others, and subway to others, and explanatory variables which affect transit transfer mode choice were sex, age, occupation, handicap, transfer area, purpose of travel and travel time. Also probability regarding explanatory variables was estimated using multinomial logit model and limit marginal analysis was carried out according to explanatory variables(cost, time). In the results, indicating goodness of fit is very reasonable as ${\rho}^2$=0.354. According to the result of marginal analysis for the selection of probability, when travel time is increased, users of bus to bus and bus to subway prefer to use subway to subway. Furthermore users of bus to bus and bus to subway prefer to use bus to others and subway to others when travel cost is increased in the result of marginal analysis for the selection of probability.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.170-181
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• 2015

This study explores passengers' travel characteristics at six bus stops on the Seoul Ring Expressway using smart traffic card data. Based on the characteristics, political strategies to improve bus facilities on expressway are suggested. Firstly, among them two bus stops of Guri and Uiwang-Cheonggye have higher transfer rate of passengers, 37.56% and 36.9% of the total intercity (red) bus passengers on the expressway, respectively. Secondly, Uiwang-Cheonggye bus stop has the highest transfer rate, and Guri bus stop has also higher transfer rate and the highest on-and-off passengers. It implies that both bus stops need to be prioritized for improving bus stop facility, access roads, and connection facility between the bi-directional stops. Thirdly, Guri (down) bus stop has relatively longer waiting time for transfer, thus shorter bus headways running the bus stop should be considered. Lastly, most passengers using both stops come to and from Bundang-gu in Geongnam City. Overall, the results of this study would be helpful for transport planners to develop effective bus route policies and bus operation.