• 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.

• Journal of Intelligence and Information Systems
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• v.4 no.2
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• pp.23-34
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• 1998

Travel time forecasting, especially public bus travel time forecasting in urban areas, is a difficult and complex problem which requires a prohibitively large computation time and years of experience. As the network of target area grows with addition of streets and lanes, computational burden of the forecasting systems exponentially increases. Even though the travel time between two neighboring intersections is known a priori, it is still difficult, if not impossible, to compute the travel time between every two intersections. For the reason, previous approaches frequently have oversimplified the transportation network to show feasibilities of the problem solving algorithms. In this paper, forecasting of the travel time between every two intersections is attempted based on travel time data between two neighboring intersections. The time stamps data of public buses which recorded arrival time at predetermined bus stops was extensively collected and forecast. At first, the time stamp data was categorized to eliminate white noise, uncontrollable in forecasting, based on wavelet conversion. Then, the radial basis neural networks was applied to remaining data, which showed relatively accurate results. The success of the attempt was confirmed by the drastically reduced relative error when the nodes between the target intersections increases. In general, as the number of the nodes between target intersections increases, the relative error shows the tendency of sharp increase. The experimental results of the novel approaches, based on wavelet conversion and neural network teaming mechanism, showed the forecasting methodology is very promising.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.112-123
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• 2017

The accurate forecasting of the public transportation's transit and arrival time has become increasingly important as more people use buses and subways instead of personal vehicles under the government's public transportation promotion policy. Using bus management system (BMS) data, which provide information on the real-time bus location, operation interval, and operation history, it is now possible to analyze the bus schedule reliability. However, the punctuality should always be considered together with the operation safety. Therefore, this study suggests a new methodology to secure both reliability and safety using the BMS data. Unlike other studies, we calculated the bus travel time between two bus stops by dividing the total travel length into 6 sections using 5 different measuring points. In addition, the optimal travel time for each bus route was proposed by analyzing the mean, standard deviation and coefficient of variation of the each section's measurement. This will ensure the reliability, safety and mobility of the bus operation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.597-604
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• 2014

In this study, we investigate to show the limitations of current bus arrival time estimation model based on each bus route, and to propose a bus arrival time estimation model based on a bus stop to overcome these limitations. Using the characteristic of bus arrival time calculated on travel time between two bus stops, we develop a model to estimate bus arrival times with the data of all buses traveling the same section regardless of bus route numbers. In the proposed model, an estimated arrival time is calculated by weighted moving average method, and verification between observed value and estimated time is performed on the basis of RMSE. Error was reduced by up to 20% compared to the existing models and the data update period was reduced by more than half that is related to the accuracy of bus arrival time information. We expect to solve the following problems with the suggested method: sudden increase or decrease in arrival time of the bus, the difference of the expected arrival times at the same stop between two or more buses having different route numbers, and impossibility of offering information of a bus if the bus is not operated with the designated schedule.

• 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.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1811-1825
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• 2011

This study analyzed the transit services with respect to transit service measures such as the load factor representing number of passengers between stops, dwelling time, and operational speed based on transit smart card data recorded in 2009. A case study on the local bus line 7024 connecting Seoul railway station to evaluate bus services at passenger perspectives was accomplished. From the results, we found that the dwelling time was not affected by the number of passengers which is because the tagging patterns are different among passengers. The operational speed was analyzed by calculating the average speed of the bus route and the speed of each bus stops based on dwelling time. Interestingly, calculating operation speed based on the transit smart card data is the first time effort ever made and this means that it is not necessary to observe travel speed of bus and railway at a field level any more. we hope that this study will be a basis of evaluation of transit services purely based on the transit smart card data and help to make better transit services for passengers and operators as well.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.1
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• pp.25-32
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• 1988

Vehicle platoons starting a stopline are dispersed while travelling along the street and the delay at the next intersection depends on the arrival pattern of dispersed traffic flow. In this paper, the platoon dispersion charactiristics of our country, especially the time gap between passenger cars and buses caused by the dwell time at bus stops, were investigated through travel time surveys. Based on the survey results, on improved analysis method of intersection delay is proposed.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.335-349
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• 2018

This study analyzes the effect of the changes in traffic environments such as transportation speeds on the time-distance accessibility for the public transportation passengers. To do this, we use passenger transaction databases of the Seoul metropolitan public transportation system: one week for each of the three years (2011, 2013, and 2015). These big data contain the information about time and space on the traffic trajectories of every passenger. In this study, the time-distances of links between subway stations and bus stops of the public transportation system at each time are calculated based on the actual travel time extracted from the traffic-card transaction database. The changes in the time-distance accessibility of the integrated transportation network from the experimental results can be summarized in two aspects. First, the accessibility tends to decline as the year goes by. This is because the transportation network becomes more complicated and then the average moving speed of the vehicles is lowered. Second, the accessibility tends to increase on the weekend in the analysis of accessibility changes by day. This tendency is because the bus speeds on bus routes on the weekend are faster than other days. In order to analyze the accessibility changes, we illustrate graphs of the vehicle speeds and the numbers of passengers by year and day.