• Title/Summary/Keyword: 택시 데이터

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A study on the placement of empty taxis based on the location history data (위치이력 데이터를 이용한 공택시 배치에 관한 연구)

  • Lee, Jung-Hoon;Park, Gyung-Leen
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2008.10a
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    • pp.195-199
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    • 2008
  • 본 논문은 택시들의 승차율을 높이고 승객들의 대기시간을 최소화하기 위하여 제주 택시들의 이동이력 데이터를 기반으로 하여 공차들을 승객을 만날 가능성이 많은 지역으로 배치하는 기법을 제시한다. 이동이력 데이터에 포함된 공차 보고와 승차 보고 수 사이의 스케일 차이를 극복하기 위하여 전체수와 영역내 합에 대한 비율로 정규화하는 방법을 설명하고 장단점을 분석한다. 또 시간대별, 요일별, 주간별 택시들의 승객 대기시간에 대한 통계 데이터에 기반하여 가장 수요와 공급이 적정하게 유지되는 시간구간을 발견하고 이 구간에 대한 택시 분포와 현재의 택시 분포의 차이에 의해 수요보다 공급이 많은 곳의 택시를 재배치한다.

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Finding Frequent Route of Taxi Trip Events Based on MapReduce and MongoDB (택시 데이터에 대한 효율적인 Top-K 빈도 검색)

  • Putri, Fadhilah Kurnia;An, Seonga;Purnaningtyas, Magdalena Trie;Jeong, Han-You;Kwon, Joonho
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.9
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    • pp.347-356
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    • 2015
  • Due to the rapid development of IoT(Internet of Things) technology, traditional taxis are connected through dispatchers and location systems. Typically, modern taxis have embedded with GPS(Global Positioning System), which aims for obtaining the route information. By analyzing the frequency of taxi trip events, we can find the frequent route for a given query time. However, a scalability problem would occur when we convert the raw location data of taxi trip events into the analyzed frequency information due to the volume of location data. For this problem, we propose a NoSQL based top-K query system for taxi trip events. First, we analyze raw taxi trip events and extract frequencies of all routes. Then, we store the frequency information into hash-based index structure of MongoDB which is a document-oriented NoSQL database. Efficient top-K query processing for frequent route is done with the top of the MongoDB. We validate the efficiency of our algorithms by using real taxi trip events of New York City.

Analysis scheme for customer pick-up points based on the Jeju Taxi Telematics system (제주 택시 텔레매틱스에 기반한 택시 승차지점 분석 기법)

  • Lee, Jung-Hoon;Park, Gyung-Leen
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2008.06a
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    • pp.275-279
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    • 2008
  • 본 논문은 제주 택시 텔레매틱스 사업의 운영 결과 축적된 히스토리 정보를 기반으로 택시들의 운행기록을 분석하여 승객들이 택시를 찾는 지점을 분석하는 기법을 제시하고 이를 바탕으로 시간별 지역별 링크별 승차 패턴을 분석한다. 이를 위하여 택시의 상태도 천이에서 승차지점을 추출하였으며 해당 데이터를 데이터베이스 테이블에 저장하였다. 이후 승차지점들을 그루핑하여 승차 패턴의 추이를 발견하고 이에 대한 분석을 수행하였다. 이 분석 데이터는 택시들을 지역별 시간대별로 승객이 많이 찾는 위치로 이동시키고 택시의 공차 운행율을 감소시키는 배차 방식을 개발하여 택시의 영업 수익 증대와 승객의 택시 대기시간 감소를 기할 수 있다.

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The Impact of the Mobile Application on Off-Line Market: Case in Call Taxi and Kakao Taxi (모바일 어플리케이션이 오프라인 시장에 미치는 영향: 콜택시와 카카오택시를 중심으로)

  • Kyeongjin Lee;Jaehong Park
    • Information Systems Review
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    • v.18 no.4
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    • pp.141-154
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    • 2016
  • Mobile application is growing explosively with the advent of a new technology: smartphones. Mobile application is a new marketing channel and performs as a start-up platform. This study examines the effect of mobile application on the off-line market. Despite the continuous declining demand for taxi service, paradoxically, the supply of taxi service has increased. The taxi industry can be categorized into general taxi and call taxi. General taxi is accidental and inefficient because it has to search for its own passenger. As call taxi takes the request of a passenger, it is more efficient than general taxi. However, the current defective passenger-taxi driver matching system and insufficient taxi driver management hinder the development of the call taxi market. Differences in differences (DID) is an econometrical methodology that examines whether or not an event has meaningful influence. This research uses DID to investigate the effect of the Kakao taxi application on the call taxi industry. Furthermore, it examines the effect of major companies' reckless diversification, which is considered unethical behavior. The passengers of call taxi data from August 2014 to July 2015 and those of designated driving service data of the same period were collected as the control group.

Finding Stop Position of Taxis using IoV data and road segment algorithm (IoV 데이터와 도로 분할 알고리즘을 이용한 택시 정차위치 파악)

  • Lim, Dong-jin;Onueam, Athita;Jung, Han-min
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.590-592
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    • 2018
  • Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

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제주 택시 텔레매틱스 시스템의 구축과 활용

  • Lee, Jeong-Hun;Park, Gyeong-Rin
    • Information and Communications Magazine
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    • v.25 no.7
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    • pp.34-39
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    • 2008
  • 본고에서는 제주 택시 텔레매틱스 시스템에서 제공하는 서비스에 대해 소개하며 이 시스템의 구축과 운영상황을 소개한다. 또 서비스를 고도화하기 위한 플랫폼과 이동이력 데이터의 활용방안에 대해 고찰한다. 제주 택시 텔레매틱스 시스템은 각 차량의 위치를 파악하고 고객의 콜에 대해 가장 가까운 차량을 배차하는 기능을 가지며 대용량 데이터에 대한 고속의 처리 기능을 지원해야 한다. 또 각 차량에서 보고된 위치 정보는 기본적으로 경도, 위도 외에도 속도와 방향에 대한 정보가 포함되므로 링크의 통행속도 산출이나 배차 지점의 분석, 탑승 패턴의 추이, 배차 시간의 분석 등 다양한 부가정보를 산출할 수 있다.

Analysis of the taxi telematics history data based on a state diagram (상태도에 기반한 택시 텔레매틱스 히스토리 데이터 분석)

  • Lee, Jung-Hoon;Kwon, Sang-Cheol
    • Journal of Korea Spatial Information System Society
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    • v.10 no.1
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    • pp.41-49
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    • 2008
  • This paper presents a data analysis method for the taxi telematics system which generates a greate deal of location history data. By the record consist of the basic GPS receiver-generated fields, device-added fields such as taxi operation status, and framework-attached fields such as matched link Identifier and position ratio in a link, each taxi can be represented by a state diagram. The transition and the state definition enable us to efficiently extract such information as pick-up time, pick-up distance, dispatch time, and dispatch distance. The analysis result can help to verify the efficiency of a specific taxi dispatch algorithm, while the analysis framework can invite a new challenging service including future traffic estimation, trajectory clustering, and so on.

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Design and Implementation of the Taxi Telematics Driving History Data Visualization System using Google Earth (Google Earth를 이용한 택시 텔레매틱스 운행 이력 데이터 가시화 시스템의 설계 및 구현)

  • Choi, Jin-Woo;Yang, Young-Kyu
    • Korean Journal of Remote Sensing
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    • v.25 no.1
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    • pp.61-69
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    • 2009
  • This paper presents design and implementation of a system for effective visualizing driving history data of the Jeju taxi telematics system using Google Earth. It is possible to review the situation of all taxies or extract the trace of any taxi or search taxies driven through a region of interest.

A Mathematical Model for Estimating Proper Taxi Fleet Size : Focusing on Pyeong-Taek City Case Study (택시총량산정을 위한 수리모형의 개발 : 평택시를 중심으로)

  • Kim, Suk Hee;Choi, Keechoo;Choi, Doo Sun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.5D
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    • pp.633-639
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    • 2011
  • To estimate a proper fleet size of taxi, a daily archived tachograph was analyzed for both corporate taxi and owner-driver taxi. Mathematical model to estimate a desirable number of taxi was developed using city's characteristics of Pyeong-taek city case. This model could be used as coefficient of determination of city's characteristics model(revised R square) was 0.970. a total amount of taxi number in the future for the city of Pyeong-taek. As a result, the model produced a proper fleet size of Pyeong-taek city in the future as 1,794 taxis by 2014, which was higher in number by 214 taxis, compared to 2009. Also, the model of the service rate, considering operation condition, was used to analyze a total number of taxies. As a result, the model showed a total number of taxis as 1,224 taxis by 2014, which is lower in number by 356 taxies, compared to 2009. It is desirable to use both city's characteristics model and the service rate model to estimate a total number of taxis in conclusion. As a result of adopting average value from two model, the model produced a total supply plan of Pyeong-taek city as 1,509 taxis by 2014, which is smaller than in number by 71 taxis, compared to 2009.

Data Processing Architecture on the Jeju Taxi Telematics System (제주 택시 텔레매틱스 시스템에서 이동 이력 데이터의 처리 구조)

  • Lee, Jung-Hoon;Hong, Young-Shin;Park, Gyung-Leen
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.05a
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    • pp.879-880
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    • 2008
  • 본 논문은 제주 택시 텔레매틱스 시스템에 축적되고 있는 차량들의 이동이력 데이터에 대한 처리구조를 설계하고 구현한다. 각 차량은 1분마다 자신의 위치와 GPS 정보 및 택시의 상태에 관련된 보고를 발생시키며 중앙의 관제시스템은 이를 수합하여 이력데이터를 구성한다. 본 논문에서 구현하는 시스템은 위치 보고를 처리하여 인코딩 변환, 좌표 변환, 맵 매칭, 도로상에서의 위치 계산 등을 수행한 후 오라클 데이터베이스의 이력 테이블에 저장하도록 한다. 이를 위하여 도로 네트워크가 데이터베이스로 변환되었으며 도로망에의 가시화를 위하여 지도 인터페이스 프로그램이 구현되었다. 이러한 정보들은 이력 테이블과 아울러 공간 데이터베이스 엔진과 결합하여 C 언어나 SQL 문장에 의하여 다양한 위치기반 질의를 가능하게 할 뿐 아니라 배차 정보 분석, 현재 통행 속도 분석 등 부가가치가 높은 정보를 산출하는데 필수적인 역할을 수행한다.