• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.11-30
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• 2019

Smartcards are used as the basic data for utilizing the various transportation policies and evaluations, etc. and provided the transportation basic statistics index. However, the main problem of the smartcard data is that the most of users do not take the alighting tag at the stop, so there is a limit to the scope of use for the total O-D trip data because incomplete O-D traffic data of transportation card users. In this study, a decision tree of learning model is estimated for the alighting stop of smartcard users. The model estimation accuracy in range less than 2 stops interval was 89.7% on average. By eliminating the incompleteness alighting stop of smartcard data through this model, it is expected to be used as the basic data for various transportation analyses and evaluations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.90-101
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• 2010

The existing HiPassPlusCard system is composed of the HiPassPlusCard, a Purchase SAM, a Purchase terminal, a settlement system and OBU. However, this system is confronted by the problem with its incompatibility. This problem occurred because the technology companies made cards in their own ways in respect of the parts which were not yet set by KS standard. Thus if existing HiPassPlusCard user wants to use any other public transportations, user would have to buy other cards and have to bring all them. Also if the HiPlusCard wants to extend their business to apply its technology into infrastructure of the other companies, the HiPlusCard has to construct infra independently so that it causes the such problems of duplicated investment. To solve these problems, we have analyzed and upgraded the existing HiPassPlusCard system, and we designed and developed the Nation-wide Interoperable HiPassPlusCard system. Then the conformity test demonstrated that it is efficiency-oriented and technically performs well. Also we, the HiPlusCard, the Korea Financial Telecommunications & Clearings and the KORAIL NETWORKS, run the Test-bed in Gwangju for 6 months. The test-bed indicated that Nation-wide Interoperable HiPassCard system practically works well.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1270-1272
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• 2003

Smart card system is being used in many countries to improve access to their transportation systems. Especially for subway system that typically see high volumes of passengers at specific times of the days, it's critical to find a ray to collect fares without unnecessarily delaying passengers. The card consists of antenna, modulation and demodulation block, power supply module and memory. The antenna receives the power and data signal from reader. The FRAM is used as the inner memory. And it is a non-volatile memory and complements the problems, that is high consumption and low data processing speed, of using conventional EEPROM in the passive smart cart. In this paper, we analyze and design the RF passive smart card to apply to the fare collection for the subway gate system.

• The Journal of Economics, Marketing and Management
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• v.9 no.5
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• pp.39-50
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• 2021

Purpose: This study is to analyze the changes of consumption patterns to diagnose the economic impacts on consumers' market during COVID-19, and to suggest implications to overcome the new social and economic crisis of Jeju Island. Research design, data, and methodology: We collected a set of credit card transaction records issued by BC Card Company from merchants in Jeju Special Self-Governing Province for past 4 years from 2017 to 2020 from the Jeju Data Hub run by Jeju Special Self-Governing Province. The big data contains details of approved credit card transactions including the approval numbers, amount, locations and types of merchants, time and age of users, etc. The researchers summed up amount in monthly basis, transforming big data to small data to analyze the changes of consumption before and after COVID-19. Results: Sales fell sharply in transportation industries including airlines, and overall consumption by age group decreased while the decrease in consumption among the seniors was relatively small. The sales of Yeon-dong and Yongdam-dong in Jeju City also fell significantly compared to other regions. As a result of the paired t-test of all 73 samples in Jeju City, the p-value of the mean consumption of the credit card in 2019 and 2020 is significant, statistically proven that the total consumption amount in the two years is different. Conclusions: We found there are sensitive spots that can be strategically approached based on the changes in consumption patterns by industry, region, and age although most of companies and small businesses have been hit by COVID-19. It is necessary for local companies and for the government to be focusing their support on upgrading services, in order to prevent declining sales and job instability for their employees, creating strategies to retain jobs and prevent customer churn in the face of the crisis. As Jeju Province is highly dependent on the tertiary industry, including tourism, it is suggested to create various strategies to overcome the crisis of the pandemic by constantly monitoring the sales trends of local companies.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.111-121
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• 2007

A transit assignment model can forecast the behaviors of transit users. thereby playing an important role In the evaluation of transit policies. Most existing transit assignment models are based on the models for passenger cars; therefore they cannot reflect the specific characteristics of transit modes. In addition most of the existing models are based on a single transit mode (bus or rail), and they cannot forecast the behaviors of transit users in a changing mass transportation system. The goal of this study is to overcome these problems with the exiting models and to develop a more realistic model. The newly developed model is based on mixed transit modes and is a stochastic model that can reflect the different preferences of each transit user for travel time and transfering. Data gathered from the Seoul metropolitan area's smart card are used to calibrate this model. This study is expected to be used for the evaluation of transportation policies and to attribute the development of transit revitalization strategies.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.684-692
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• 2007

• 한국ITS학회:학술대회논문집
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• v.2007 no.10
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• pp.42-50
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• 2007

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.1-11
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• 2023

COVID-19 has caused the dramatic reduction of public transportation demand in Busan Metropolitan City, that is, daily public transportation trips in 2020 dropped by approximately 920,000 trips from 2019 based on the public transportation card data. This study investigated the underlying factors affecting the public transportation demand discrepancy between before and after COVID-19 at the primary administration unit(i.e., Eup, Myeon, Dong) level with Ordered Logistic Regression model. Finding of this study is as follows. The primary administration units characterized with high ratio of welfare recipients, industrial area, and day boarders were heavily dependent on public transit, indicating little change in public transportation demand. On the other hands, the primary administration units which have high ratio of urban rail transit uses experienced significant reduction of public transportation demand. In conclusion, transportation policies taken under emergent situation such as COVID-19 need to take into account the region-based characteristics rather than unilateral ones.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.28-38
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• 2019

The smart card data stores the transit usage records of individual passengers. By using this, it is possible to analyze the traffic demand by station and time. However, since the purpose of the trip is not recorded in the smart card data, the demand for each purpose such as commuting, school, and leisure is estimated based on the survey data. Since survey data includes only some samples, it is difficult to predict public transport demand for each purpose close to the complete enumeration survey. In this study, we estimates the purposes of trip for individual passengers using the smart card data corresponding to the complete enumeration survey of public transportation. We estimated trip purposes such as commute, school(university) considering frequency of O-D, duration, and departure time of a passenger. Based on this, the passengers are classified as workers and university students. In order to verify our methodology, we compared the estimation results of our study with the patterns of the survey data.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.153-169
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• 2022

With the extension of the average life span and the rapid aging of the population, defining elderly population as a single group is difficult as the physical, economic and social conditions of individual have become different. Therefore, policies that take into account the characteristics of each group are required. The purpose of this study is to classify individual travel types and to analyze the characteristics of each travel type, based on individual public transportation trajectory data as known as smart card data. Among the four classified types, the long-distance low-frequency stay type and the short-range medium-frequency mobile type show external activity traffic characteristics for retirement leisure, while the long-distance high-frequency stay type and the long-distance high-frequency mobile group include regular commuting. Traffic variability and residence areas of stay were identified in terms of each classified travel type. The results of this study provide the important suggestions for establishing a transportation policy that takes into account the characteristics of each type of elderly population in Seoul.