• Proceedings of the KSR Conference
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• 1998.11a
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• pp.288-295
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• 1998

In this paper the system safety program plan(SSPP) for the development of Korea high speed railway system was presented. The plan for the design phase built up base upon MIL-STD 882C, manual for the development of rail transit system safety program plans by American Public Transit Association, and SSPP for Seoul-Pusan High Speed Rail project should be modified and then applied to the phases of manufacturing, test and commissioning. The plan deals with the safety program, the reference standards, the management and responsibility for the safety related activities, the methods to be used for early identifying safety critical items and functions and eliminating or controlling all hazards in a timely and cost-effective manner, and the documentation generated for safety assessment.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.109-120
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• 2006

Since the 1st of July, 2004, the public transport system of the Seoul metropolitan area has been rearranged. In the new system, bus lines are divided into 4 classes-wide area, arterial road, branch, and rotation lines with renewed fare system based on the total distance travelled. Since central control center known as the Bus Management System (BMS) integrates the entire system operation. it now becomes feasible to collect travel information and provide it to the users scientifically and systematically. The Purpose of this study is to forecast transit travel time using real-time traffic data coming from both buses and subway. This is significant contribution since provision of real-time transit information and easy access to it would most likely boost the use of mass transit system, alleviating roadway congestion in the metropolitan area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.744-751
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• 2006

Even many kinds of Internet-based services have been generated due to the great development of the Internet. PSTN still exists in the center of the national infrastructure network and the transit exchanges will be maintained the core roles in PSTN for many years in the future. These transit exchanges often suffer from unexpected overload situation because they have to process Intelligent Network calls and mobile calls additionally as well as POTS (Plain Old Telephone Service). In this paper, we suggest an efficient overload control algorithm for the distributed transit switching system under the various types of call services. We also show that this algorithm can be implemented easily cooperating with the network management control functions. The simulation technique is used to show that the proposed algorithm effectively controls calls and maintains safely the call processor's load under the various kinds of overload situations.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.437-448
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• 2016

Some previous researches suggested a transit trip destination inference method by constructing trip chains with incomplete(missing destination) smart card dataset obtained on the entry fare control systems. To explore the feasibility of the transit trip destination inference method, the transit trip chains are constructed from the pre-paid smart card tagging data collected in Busan on October 2014 weekdays by tracing the card IDs, tagging times(boarding, alighting, transfer), and the trip linking distances between two consecutive transit trips in a daily sequences. Assuming that most trips in the transit trip chains are linked successively, the individual transit trip destination zones are inferred as the consecutive linking trip's origin zones. Applying the model to the complete trips with observed OD reveals that about 82% of the inferred trip destinations are the same as those of the observed trip destinations and the inference error defined as the difference in distance between the inferred and observed alighting stops is minimized when the trip linking distance is less than or equal to 0.5km. When applying the model to the incomplete trips with missing destinations, the overall destination missing rate decreases from 71.40% to 21.74% and approximately 77% of the destination missing trips are the single transit trips for which the destinations can not be inferable. In addition, the model remarkably reduces the destination missing rate of the multiple incomplete transit trips from 69.56% to 6.27%. Spearman's rank correlation and Chi-squared goodness-of-fit tests showed that the ranks for transit trips of each zone are not significantly affected by the inferred trips, but the transit trip distributions only using small complete trips are significantly different from those using complete and inferred trips. Therefore, it is concluded that the model should be applicable to derive a realistic transit trip patterns in cities with the incomplete smart card data.

• Journal of Environmental Health Sciences
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• v.42 no.6
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• pp.353-364
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• 2016

Objectives: Determining the time activity patterns of urban populations is critical when performing an exposure assessment. The purposes of this study were to classify urban populations in Korea by their time activity patterns and to identify factors that influence these patterns. Methods: The time activity patterns of 31,634 and 20,263 individuals were obtained from two national databases collected in 2004 and 2009, respectively. The two largest metropolitan cities in Korea, Seoul and Busan, were selected for this analysis. For each city, multivariate linear regressions were performed to determine factors affecting the time spent in a residence and in transit. We also used cluster analysis to classify each urban population by activity pattern. Results: Nine distinctive activity patterns were identified in the Seoul and Busan populations, respectively, and the resulting classified population groups had specific characteristics. The identified patterns were similar for Seoul and Busan. The most significant factors affecting time spent in a residence were employment status, age, marriage status, education, and gender. Gender, education, employment status, and monthly income were significant factors affecting time spent in transit. Conclusion: These results indicate that, in addition to region, exposure scientists in Korea should consider classifying populations based on age, gender, and occupation.

• Smart Media Journal
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• v.8 no.1
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• pp.59-66
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• 2019

The importance of data is increasing at a high rate as data is massively generated and taken into account in various policy supports and contents. However, because of their speed of growth, it is difficult to find the data that is needed. Both the methodological elements that summarize the data and the technical elements of the visualization that help to see at a glance are important. This paper summarizes data visualization methods to improve the currently used design - oriented infographics and propose data - centric infographics. In addition, we will present examples of data analysis and infographics production using Tableau Public. The Gwangju metropolitan city bus user data was used for infographics production, and the results show that the total number of passengers using the stopping point is similar to that of the general passengers, while it is different from the numbers of transit passengers and teen riding-and-transit passengers. Data-centric infographics visualization, unlike existing infographics that is pronounced only as a visual role, is expected to be used as a tool for scientific research as well as efficiently delivering data.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1777-1782
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• 2007

Since July in 2004, starting with urban bus reorganization of Seoul metropolitan government, the change of the public transportation which integrates the urban bus and the subway of the metropolis are being continued. But the integration of such bus and the subway is staying to only a fare system mainly, and the guidance system of the subway and the bus has not changed. So we propose the concept of the new guidance system following public transportation change tendency. At first we introduce the new information system which can guide city railroad and bus altogether, and we propose new system which can guide divided by the trunk line and the branch line instead of bus and subway. Last high-functional guidance system which can give passengers tip and hint for various and effective usage of public transportation in more complicated city transit network is introduced. This new guidance system can increase competitiveness of public transportation system and stretch transportation share of it. And that guidance system is high-class contents that all public transportation business can utilize, so it can originate new industry. In conclusion, this new innovative guidance system is important field that government, local administration and public transportation business must be concerned and develop.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.103-114
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• 2005

The transit fare resulted from the renovation of public transit system in Seoul is basically determined based on the distance-based fare policy (DFP). In DFP, the total fare a passenger has to pay for is calculated by the basic-transfer-premium fare decision rule. The fixed amount of the basic fare is first imposed when a passenger get on a mode and it lasts within the basic travel distance. The transfer fare is additionally imposed when a passenger switches from one mode to another and the fare of the latter mode is higher than the former. The premium fare is also another and the fare of the latter begins to exceed the basic travel distance and increases at the proportion of the premium fare distance. The purpose of this study is to propose an algorithm for finding K number of paths, paths that are sequentially sorted based on total amount of transit fare, under DFP of the idstance-based fare policy. For this purpose, the link mode expansion technique is proposed in order to save notations associated with the travel modes. Thus the existing K shortest path algorithms adaptable for uni-modal network analysis are applicable to the analysis for inter-modal transportation networks. An optimality condition for finding the K shortest fare routes is derived and a corresponding algorithms is developed. The case studies demonstrate that the proposed algorithm may play an important role to provide diverse public transit information considering fare, travel distance, travel time, and number of transfer.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.1-14
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• 2008

Mass transit information should contribute many benefits to users. Especially transportation information technology is developing highly with information technology in Korea recently. Hereafter it is expected to provide customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithms in public transportation networks including travel and transfer attributes. In this research, multi objectives such as travel time, transfer time, and number of transfer and so on are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding alternatives arbitrarily is proposed by selecting the best alternative which provides maximum utility to users among non dominated paths. Therefore, the ultimate goal of this study proposes a multi objective shortest paths finding algorithm which can take into account multiple user classes in a transit network with multiple travel modes. The proposed algorithm is demonstrated based on the two case studies - a small toy network and the large-scaled Seoul Metropolitan subway network.