• Title/Summary/Keyword: 교통카드 빅 데이터

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Time-distance Accessibility Computation of Seoul Bus System based on the T-card Transaction Big Databases (교통카드 빅데이터 기반의 서울 버스 교통망 시간거리 접근성 산출)

  • Park, Jong Soo;Lee, Keumsook
    • Journal of the Economic Geographical Society of Korea
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    • v.18 no.4
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    • pp.539-555
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    • 2015
  • This study proposes the methodology for measuring the time-distance accessibility on the Seoul bus system based on the T-card transaction databases and analyzes the results. T-card transaction databases contain the time/space information of each passenger's locations and times of the departure, transfers, and destination. We introduce the bus network graph and develop the algorithms for time-distance accessibility measurement. We account the average speed based on each passenger's get-in and getoff information in the T-card data as well as the average transfer time from the trip chain transactions. Employing the modified Floyd APSP algorithm, the shortest time distance between each pair of bus stops has been accounted. The graph-theoretic nodal accessibility has been given by the sum of the inverse time distance to all other nodes on the network. The results and spatial patterns are analyzed. This study is the first attempt to measure the time-distance accessibility for such a large transport network as the Seoul bus system consists of 34,934 bus stops on the 600 bus routes, and each bus route can have different properties in terms of speed limit, number of lanes, and traffic signal systems, and thus has great significance in the accessibility measurement studies.

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The Effects of COVID-19 on Public Transportation Demand: The Case of Busan Metropolitan City (코로나19의 확산이 대중교통 수요변화에 미치는 영향요인 분석 - 부산광역시를 중심으로 -)

  • Minjeong KIM;Hoe Kyoung KIM
    • 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.

Will the Addition of Competing Transit Systems Increase Overall Transit Passengers? Lessons Learned from Urban Rail Transit Line 3 in Daegu (도시철도 개통에 따른 대중교통 통행량 변화 분석: 대구도시철도 3호선 개통을 대상으로)

  • Hwang, Jung Hoon;Chung, Younshik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.3
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    • pp.371-377
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    • 2022
  • Urban rails and buses are representative public transit systems that not only cooperate with each other, but also compete with each other. In other words, there is a possibility that the overall demand for public transportation may increase due to the introduction of a competitive public transportation system, or there is a possibility that demand will be maintained at the level that is simply converted to a competitive system. The objective of this study is to analyze the change in public transit flow when an additional transit system is introduced in a city with alternative public transit systems. To carry out this objective, we analyzed changes in public transit passenger flow before and after the introduction of an urban rail transit line 3 in Daegu Metropolitan City, where two public transit systems, urban rail and bus, exist. For accurate analysis, big data collected by passenger transportation cards were utilized for one week in the second week of April 2015, 2016, and 2019. From the analysis, it was found that although the urban rail passenger flow increased due to the additional urban rail transit system, the change in the overall public transit passenger flow in the city was insignificant. In other words, it is interpreted that the bus transit passengers have been shifted to the urban transit systems. Based on the results, this study suggested various policies to increase the demand for public transit rather than simply adding public transit systems.

Understanding elderly's travel pattern based on individual trip trajectory using smart card data (스마트카드 데이터를 활용한 통행궤적 기반 고령인구 통행유형 분류)

  • Lee, Ju-Yoon;Kang, Young-Ok
    • 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.

A Model for Analyzing Time-Varying Passengers' Crowdedness Degree of Subway Platforms Using Smart Card Data (스마트카드자료를 활용한 지하철 승강장 동적 혼잡도 분석모형)

  • Shin, Seongil;Lee, Sangjun;Lee, Changhun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.5
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    • pp.49-63
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    • 2019
  • Crowdedness management at subway platforms is essential to improve services, including the prevention of train delays and ensuring passenger safety. Establishing effective crowdedness mitigation measures for platforms requires accurate estimation of the congestion level. There are temporal and spatial constraints since crowdedness on subway platforms is assessed at certain locations every 1-2 years by hand counting. However, smart cards generate real-time big data 24 hours a day and could be used in estimating congestion. This study proposes a model based on data from transit cards to estimate crowdedness dynamically. Crowdedness was defined as demand, which can be translated into passengers dynamically moving along a subway network. The trajectory of an individual passenger can be identified through this model. Passenger flow that concentrates or disperses at a platform is also calculated every minute. Lastly, the platform congestion level is estimated based on effective waiting areas for each platform structure.

Analysis of User Demand Characteristics of Currently-established Night Bus in Seoul by Using Smart Card Data : Case Study on Gangnam Station (스마트카드 데이터를 이용한 심야버스 이용수요 특성분석 : 강남역을 중심으로)

  • Kim, Min ju;Lee, Young ihn
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.1
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    • pp.101-116
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    • 2017
  • This Study estimates the actual night traffic using the smart card data used by most of the public transportation users, and compares it with the current night bus routes by KT Telecom based on the night time call volume. In order to compare the current night bus and night trips evaluated by smart card data, we presented indicators related to the degree of matching, and estimated the volume of service currently provided. The unique approach of the study is that we chose subway station instead of bus stop for the unit of the study. Bus stops has their complexity in a way that stops with same name could belong to different administrative area depending on its direction. For this reason, we decided to use subway station and defined its adjacent administrative district as the scope of influence. Since night bus is the primary means of transportation during the late night, it is anticipated that they will be able to provide better service by calculating the actual traffic and selecting the routes.

Load Factor Decrease In The Seoul Metro Circle Line through Analyzing Passenger OD Demand (2호선 혼잡구간 OD수요 분리유도를 통한 혼잡도 개선 방안 (교통카드 빅데이터 분석을 중심으로))

  • Eom, Jin Ki;Song, Ji-Young;Lee, Kwang-Sub
    • Journal of the Korean Society for Railway
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    • v.17 no.6
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    • pp.457-465
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    • 2014
  • This study proposes a policy for urban railway travel demand management system in order to decrease the load factor of the Seoul metro Circle line, particularly for the segment between Sadang and Samsung stations, through analyzing the transit smart card data. We propose mixed train operations of the existing Circle line and a line that goes toward Samsung station in order to transport passengers that have two distinct groups: those with the destination of Samsung station and those with destinations after Samsung station. The introduction of a mixed train operation that encourages passengers passing through Samsung station to take a Circle line train will decrease the congested load factor by 11.3% during the morning peak hours using the mixed train operation of the Circle and Samsung lines. This policy could be an effective method to decrease the load factor and improve the comfort of rail passengers without extra investment in the railway facilities.

Urban Vitality Assessment Using Spatial Big Data and Nighttime Light Satellite Image: A Case Study of Daegu (공간 빅데이터와 야간 위성영상을 활용한 도시 활력 평가: 대구시를 사례로)

  • JEONG, Si-Yun;JUN, Byong-Woon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.217-233
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    • 2020
  • This study evaluated the urban vitality of Daegu metropolitan city in 2018 using emerging geographic data such as spatial big data, Wi-Fi AP(access points) and nighttime light satellite image. The emerging geographic data were used in this research to quantify human activities in the city more directly at various spatial and temporal scales. Three spatial big data such as mobile phone data, credit card data and public transport smart card data were employed to reflect social, economic and mobility aspects of urban vitality while public Wi-Fi AP and nighttime light satellite image were included to consider virtual and physical aspects of the urban vitality. With PCA (Principal Component Analysis), five indicators were integrated and transformed to the urban vitality index at census output area by temporal slots. Results show that five clusters with high urban vitality were identified around downtown Daegu, Daegu bank intersection and Beomeo intersection, Seongseo, Dongdaegu station and Chilgok 3 district. Further, the results unveil that the urban vitality index was varied over the same urban space by temporal slots. This study provides the possibility for the integrated use of spatial big data, Wi-Fi AP and nighttime light satellite image as proxy for measuring urban vitality.

A Study on Introducing Autonomous Public Transportation On-demand Service in Real Time Using Delphi Method (델파이 기법을 활용한 실시간 수요대응 자율주행 대중교통서비스 도입 방안 연구)

  • Joung, Junyoung;Shim, Sangwoo;Kim, Minseok
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.183-196
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    • 2022
  • Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

A Case Study on the Smart Tourism City Using Big Data: Focusing on Tourists Visiting Jeju Province (빅 데이터를 활용한 스마트 관광 도시 사례 분석 연구: 제주특별자치도 관광객 데이터를 중심으로)

  • Junhwan Moon;Sunghyun Kim;Hesub Rho;Chulmo Koo
    • Information Systems Review
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    • v.21 no.2
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    • pp.1-27
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    • 2019
  • It is possible to provide Smart Tourism Service through the development of information technology. It is necessary for the tourism industry to understand and utilize Big Data that has tourists' consumption patterns and service usage patterns in order to continuously create a new business model by converging with other industries. This study suggests to activate Jeju Smart Tourism by analyzing Big Data based on credit card usage records and location of tourists in Jeju. The results of the study show that First, the percentage of Chinese tourists visiting Jeju has decreased because of the effect of THAAD. Second, Consumption pattern of Chinese tourists is mostly occurring in the northern areas where airports and duty-free shops are located, while one in other regions is very low. The regional economy of Jeju City and Seogwipo City shows a overall stagnation, without changes in policy, existing consumption trends and growth rates will continue in line with regional characteristics. Third, we need a policy that young people flow into by building Jeju Multi-complex Mall where they can eat, drink, and go shopping at once because the number of young tourists and the price they spend are increasing. Furthermore, it is necessary to provide services for life-support related to weather, shopping, traffic, and facilities etc. through analyzing Wi-Fi usage location. Based on the results, we suggests the marketing strategies and public policies for understanding Jeju tourists' patterns and stimulating Jeju tourism industry.