• Journal of Korean Society of Transportation
• /
• v.31 no.6
• /
• pp.12-21
• /
• 2013

Fare is critical variable when deciding project feasibility for a monorail system in tour regions. This study aims to estimate optimal fare balancing operators and users. An object of this study is Wolmi-eunha circulation monorail at Jung-Gu, Wolmido in Incheon metropolitan city. This study introduces a stepwise optimization technique to decide relevant fare ranges between operator's cost and user's cost. We found that the optimized station interval is 0.532km, the optimized headway is 0.206hour, optimal number of stations is 12, optimal number of vehicles is 3. Using these optimized variables, minimum user cost and minimum operator cost can be calculated. Optimal fare range is calculated from 1,261 Won to 5,063 Won. It is also found that sightseeing transport system has less sensitivity on access cost because distance differences among sightseeing transport stations located in the tour regions are negligible.

• Journal of Korean Society of Transportation
• /
• v.23 no.3 s.81
• /
• pp.149-159
• /
• 2005

The paper presented not only the difference of the marginal walking time by passenger. but also the derivation of the bus service determination model by passenger attributes. The marginal walking distance to bus stop is a basic parameter to estimate bus service coverage area in certain area. And the marginal walking distance could be transformed from the marginal walking time, which is the focus of this paper. The result of analysis revealed that the age and income of passenger are strongly related to the marginal walking time. In planning or regulating the spacing of bus routes or bus stops in certain area, the model suggested in this paper help for the planner to choose optimal alternative.

• Journal of Korean Society of Transportation
• /
• v.25 no.3
• /
• pp.137-144
• /
• 2007

This study involves an analytical approach to determine transit dispatching schedules (headways) Determining a time schedule is an important process in transit system planning. In general, the transit headway should be shorter during the peak hour than at non-peak hours for demand-responsive service. It allows passengers to minimize their waiting time under inelastic, fixed demand conditions. The transit headway should be longer as operating costs increase, and shorter as demand and waiting time increase. Optimal headway depends on the amount of ridership. and each individual vehicle dispatching time depends on the distribution of the ridership. This study provides a theoretical foundation for the dispatching scheme consistent with common sense. Previous research suggested a dispatching scheme with even headway. However, according to this research, that is valid for a specific case when the demand pattern is uniform. This study is a general analysis expanding that previous research. This study suggests an easy method to set a time table without a complex and difficult calculation. Further. if the time axis is changed to the space axis instead, this study could be expanded to address the spacing problems of some facilities such as roads. stations, routes and others.

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

• Journal of Korean Society of Transportation
• /
• v.25 no.6
• /
• pp.129-140
• /
• 2007

The planning procedure of a transit operation consists of design, operation, and evaluation according to the research characteristics. There are some review studies on the operation and evaluation procedure, but the research on the design procedure has not yet been organized systematically. In this study, the research on transit system design was reviewed and the model structure and its solution method were arranged. The decision variables of the design procedure are network structure, line spacing or position, stop spacing, dispatching headway, and fleet size. In the analytical research on design procedure, system total cost is generally used as the objective function. System total cost is comprised of user cost, which is the sum of user access, waiting, and travel cost, and operating cost. Total cost of the transit system, used as the objective function, has the unique minimum because it is differentiable. There is a certain decision variable that makes the derivative of the objective function equal to zero and the second derivative of the objective function is positive. Therefore the decision variable that makes the first derivative of the objective function zero is the optimum that minimizes the objective function, and each of the cost components of the objective function become the same. This study is expected to help understanding about the research on the design procedure of transit operation planning and to help be a catalyst for relevant research.

• Spatial Information Research
• /
• v.22 no.5
• /
• pp.65-75
• /
• 2014

Bus headway plays an important role not only in determining the passenger waiting time and bus service quality, but also in influencing the bus operation cost and passenger demand. Previous research on headway control has considered only an hourly difference in the distribution of ridership between peak and non-peak hours. However, this approach is too simple to help manage ridership demand fluctuations in a short time scale; thus passengers' waiting cost will be generated when ridership demand exceeds the supply of bus services. Moreover, bus ridership demand varies by station location and traffic situation. To address this concern, we propose a headway control algorithm for minimizing the waiting time cost by using Smart Card data. We also provide proof of the convergence of the algorithm to the desired headway allocation using a set of preconditions of political waiting time guarantees and available fleet constraints. For model verification, the data from the No. 143 bus line in Seoul were used. The results show that the total savings in cost totaled approximately 600,000 won per day when we apply the time-value cost of waiting time. Thus, we can expect that cost savings will be more pronounced when the algorithm is applied to larger systems.

• Journal of Korean Society of Transportation
• /
• v.23 no.8 s.86
• /
• pp.129-138
• /
• 2005

Since Successive introduction of BMS(Bus Management System) into the local governments has been able to collect each bus data on the road and valuate the bus operation by the quantitative index not qualitative index. we need a study on punctuality index for evaluation of service level for bus operation using bus location information. We propose punctuality index for bus operation using time-space diagram and valuate the index by application to real bus data.

• Journal of Korean Society of Transportation
• /
• v.27 no.6
• /
• pp.45-53
• /
• 2009

This study presumes the efficiency of each route by utilizing data of Seoul's exclusive bus routes for the 2008 and the DEA model. In the estimation, it is assumed that the number of passengers and profits of each route is calculated by considering the number of buses and stops, travel distance, intervals and management cost. This study computed the efficiency scores of each bus line in Seoul based on the data for the first half of 2008 and one of the DEA models, namely the BCC model. After analysis using the input-oriented BCC model, out of a total of 18 lines of interest, there were 2 CRS lines and 16 IRS lines. Also, the Tobit Regression Analysis that helps identify the impact of the elements used in the analysis on efficiency scores proved that the most influential element to exclusive buses is the length of intervals.

• Journal of Digital Convergence
• /
• v.14 no.7
• /
• pp.425-430
• /
• 2016

This study is to improve the design of bus transfer information that can be substantially used. This study has been processed using the following steps. First, I tried to define the information design and way-finding information design. Secondly, I have researched several case studies, and considered solutions. Finally, I evaluated way-finding maps through pair-wise comparisons, and drew needs through an interview. As the result of this research, there were some problems in font size, improper space between letters and non-consistent information. To solve these problems, the information has to be clear using easy symbols to be well-recognized by citizens. Also, the font size needs to be decided by a calculation of minimum legible size of letters. Lastly, a value contrast between a background color and a letter color needs to be applied more than 70 percent for better visibility. The study is expected to be used as a reference which helps informational design to be developed.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.1
• /
• pp.32-43
• /
• 2020

The transfer time is an important factor in establishing public transportation planning and policy. Therefore, in this study, the influencing factors of the transfer time for transit users were identified using smart card data, and the estimation results for the transfer time using the deep learning method such as deep neural network models were compared with traditional regression models. First, the intervals and the distance to the bus stop had positive effects on the subway-to-bus transfer time, and the number of bus routes had a negative effect. This also showed that the transfer time is affected by the area in which the subway station exists. Based on the influencing factors of the transfer time, the deep learning models were developed and their estimation results were compared with the regression model. For model performance, the deep learning models were better than those of the regression models. These results can be used as basic data for transfer policies such as the differential application of transit allowance times according to region.