• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.587-595
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• 2008

Many studies on bus scheduling optimization have been done from the 1960s to recent years for establishing rational bus schedule plan that can improve convenience of bus passengers and minimize unnecessary runs. After 2000, as part of the Intelligent Transport Systems (ITS), the importance of the schedule management and providing schedule information through bus schedule optimization has become a big issue, and much research is being done to develop optimization models that will increase bus passenger convenience and, on the side of bus management, minimize unnecessary bus operation. The purpose of this study is to calculate the optimal bus frequency and create a timetable for each bus stop by applying DTR or DTRC model that use data for each bus stop and route segment. Model verification process was implemented using data collected from bus management system (BMS) and integrated transit-fare card system for bus route of Seoul's No. 472 line. In order to evaluate the reliability and uncertainty of optimal solution, sensitivity analysis was implemented for the various parameters and assumptions used in the bus scheduling model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.110-112
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• 2010

Because the building of new meteorological observation towers requires high cost, a collection of precise meteorological data over city area is not easy. To collect atmosphere environment data or meteorological data precisely, a new approach is required. This paper introduces a new meteorological data collecting system using the public traffic systems such as regular route bus. On real time, the regular route bus can provide a meteorological data in periodic time interval and provide them on static route. Without constructing new facilities, only simple sensing and transmission equipments to attach on the bus are needed.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.2
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• pp.189-196
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• 2011

Recently, research and development of a hybrid system for passenger cars as well as for heavy-duty vehicles has become more intensive. An electric powertrain system using an electric motor can replace conventional gasoline and diesel engines. The electric motor has a higher efficiency, better acceleration performance, and is more comfortable than conventional powertrain systems; however, new methods for assessing power performance and energy convergence efficiency have to be investigated because the characteristics of an electric motor are entirely different from those of an internal combustion engine (ICE). In this study, an experiment was carried out on a motor (PMSM: Permanent Magnet Synchronous Motor) test bench. One simple driving mode and four other driving modes identified from real-world driving data of a city bus were selected to perform the experiment on the motor test bench. Then, methods for assessing the acceleration performance, energy convergence efficiency, regenerative effect, etc., were investigated. It was found that the energy efficiency of PMSM was about 90% and that 40% of demand energy was regenerated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.52-64
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• 2023

This paper concentrated on estimating the travel time value of individual regional bus passengers in various in-vehicle crowding conditions. In the analysis model, the traffic-selection data of individual transportation passengers based on smart-card data were used. Variables which reflect the level of in-vehicle crowding and the variables of in-vehicle travel time that reflect the level of in-vehicle crowding were included in the model using Box-Cox transformation. The result of this paper indicates that the travel time value experienced by individual users would increase as the in-vehicle crowding level increases. The smart card data used in this paper is considered to have significant implications in terms of conducting more sophisticated and realistic qualitative research to reflect the values of variables for in-vehicle traffic hours and in-vehicle crowding levels, which previously had limitations in observation and quantification. It is expected that the effects of improvement measures for reducing congestion on regional buses can be considered quantitatively by applying the estimation results of crowding multiplier.

• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.71-95
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• 2013

This study aims to validate the cost of building the infrastructure to commercialize online electric vehicles. For that purpose, we probe the cost to construct the necessary infrastructure for online electric vehicles regarding Seoul area public bus transit. OLEV and PEV are considered as alternative electric vehicle schemes, and each of them has their own cons and pros in terms of rechargeable battery cost and charger cost. An optimization model which minimizes the cost to install online electric bus feeding devices is proposed in order to compare the total costs of the two alternative schemes. We developed a Mixed Integer Programming model to locate the feeding devices of several different lengths at each bus stops. Furthermore, we implemented a computer simulator to obtain the parameters which will be used in the MIP model and a Web-based system which determines the optimal location of infrastructure for the whole city area from a result of the MIP model. The cost comparison result shows that the total cost of OLEV is cheaper than that of PEV considering the real data of Seoul area public transit, and, as a result, confirms the feasibility of the commercialization of OLEV.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.53-61
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• 2005

The Seoul City Government recently reformed the entire public transport system in an effort to prevent further deterioration in urban bus system's performance and service level. To analyze into impact on the productivity of Seoul's urban bus firms, this paper measures firm-level technical efficiency and productivity change with data envelopment analysis and Malmquist index approach. The paper then conceptualizes that these forms produce three kinds of output (bus-kilometers, passengers, or bus-kilometers and passengers) using five inputs (driver, maintenance, management, vehicle and fuel). The findings show that most (over one half) firms experienced a decline (an improvement) in productivity in the case of specifying only bus-kilometers (passengers) as output. As a result, it is discovered that an average firm had no change in productivity in the case of combining bus-kilometers and passengers as output. This is because the efficiency of an average firm declined due to increase in employees per bus and to an decrease in kilometers per bus. while its effectiveness improved due to an increase in passengers per bus which was caused by an increase in routes and a change in fare structure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.55-61
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• 2019

To improve bus service quality and passengers' safety at bus stops, it is necessary to analyze the relationship between bus stopping behaviors and bus stop conditions. Thus, this study investigated the proper stopping rate at 31 bus stops on Central Boulevard in Busan metropolitan city and analyzed the relationship between the proper stopping rate and bus stop operating conditions such as the length of berth, the distance from the front line of berth to bus shelter and so on. The analysis results show that the proper stopping rate is 45.82 % and the rates are closely related to each bus stop operating condition. Therefore, it is highly recommended that the front line of berth should be located parallel to bus shelter for improving the safety of bus passengers. In addition, it is suggested that the length of berth should be longer than 15m and the pavement marking of berth be redesigned with dash lines to take account of buses' entering and leaving the berth.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.234-246
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• 2017

The Seoul metropolitan government introduced the bus information systems, bus rapid transit to increase travel speed and punctuality but still suffer from insufficiency. This paper delivers a study verifying the external factors at near the bus stops. The dependent variable was set to the standard deviation of (1) travel time and (2) travel time to and from the bus stop in this study. The independent variables were set to (1) the number of routes, (2) traffic volume by bus type, (3) the number of bus bays, (4) the possibility of passing, (5) the distance to crosswalks and intersections, and (5) the presence of residential road. The results showed that the most significant factors included the link section speed, number of bus bay, distance to crosswalk, and the possibility of passing.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.197-205
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• 2006

The study suggested a demand forecasting method which explicitly reflects transfer between various transport modes especially related light rail transit project with multi-modal transit system. The suggested method classifies several groups depending on characteristic of trips and applies different demand model for each group to explain travel pattern more realistically More specifically. the trips was classified by trips within the LRT route, trips between inside and outside of the LRT route. and through trips via the LRT route. The study also suggested a evaluation measurement of time saving due to the LRT construction, which are consistent along with the do-case and the do-nothing-case even though some mode shift could be happen after introducing the LRT.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.