Development of an Algorithm to Analyze Home-based Work Trips Using Mobile Phone Data

Minsu Won; Jeongyoon Choi; Haesun Lee; Juyoung Kim

doi:10.7470/jkst.2021.39.3.383

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2021 Vol.39, Issue 3 Preview Page

Article

Development of an Algorithm to Analyze Home-based Work Trips Using Mobile Phone Data 모바일기지국 데이터를 이용한 출퇴근 통행 분석 알고리즘 개발: 집, 직장 추정을 중심으로

30 June 2021. pp. 383-398

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Abstract

Mobile phone data is one of the most crucial mobility big data to analyze all people‘s movements with a cell phone and collect a whole bunch of information about individual trips and activities. Many previous studies have verified those promising potential and utilization in the transportation research area, but there are still several limitations to extract precise and accurate travel information from the data. Therefore, for commuting trips, this study has proposed a new concept of an algorithm: 1) effectively preprocessing the mobile phone data and its signal handover phenomenon by smoothing the raw data; 2) precisely identifying locations of home and work using a stay time and frequency; 3) providing a point-based spatial estimate like GPS information to overcome the low spatial resolution of the mobile phone data. A GPS survey such as a ground truth was conducted to verify performances of the proposed algorithm, and the verification results have shown that the identification accuracy regarding home and work is about 90%, and more than 85% of all estimated home and work locations have less than 1km spatial differences from the actual locations. In addition, due to the unique features of the proposed algorithm, the constructed travel information can analyze a commuting trip for irregular work schedules such as night or evening duty.

Keywords

cell phone data

commuting trips

mobile phone data

mobility big data

signal handover

모바일기지국 데이터는 사람의 이동정보를 파악하여 개별 통행에 대한 다양한 정보를 수집할 수 있는 중요한 모빌리티 데이터이다. 기존 많은 연구를 통하여 이러한 모바일기지국 데이터의 가능성 및 잠재력이 다양한 방법으로 검증되었으나, 여전히 정확하고 정밀한 통행 정보를 추출하는 데에는 여러 가지 한계점을 보이고 있다. 그러므로 본 연구에서는 출퇴근 통행을 중심으로 1) 데이터 군집(Data Aggregation and Smoothing) 방법을 이용하여 신호 왜곡 현상을 효과적으로 처리하고, 2) 점유시간 및 빈도를 이용하여 더욱 정확하게 집과 직장을 식별하고, 3) GPS와 같은 점 단위의 위치 추정으로 모바일기지국 데이터의 공간적 저해상도 문제를 해결할 수 있는 알고리즘을 제시하였다. GPS 다이어리 조사 자료를 이용한 검증 결과, 집과 직장의 식별 정확도는 약 80% 이상이었으며, 공간적 위치 정확도는 거리오차 1km 이하가 각각 약 90%, 85%였다. 이것은 가구통행실태조사의 기본 공간 단위인 읍면동 평균 반경 약 3km를 고려하더라도 매우 정확한 결과라고 할 수 있다. 또한, 정기 근무시간(9시 출근, 18시 퇴근)에 해당하지 않는 야간 및 저녁 근무에 대한 통행도 분석할 수 있었다.

키워드

모바일 통신 데이터

출퇴근 통행

모바일 기지국 데이터

모빌리티 빅데이터

통신 신호 왜곡 현상

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Information

Publisher :Korean Society of Transportation
Publisher(Ko) :대한교통학회
Journal Title :Journal of Korean Society of Transportation
Journal Title(Ko) :대한교통학회지
Volume : 39
No :3
Pages :383-398
Received Date : 2021-05-10
Revised Date : 2021-05-18
Accepted Date : 2021-06-18
DOI :https://doi.org/10.7470/jkst.2021.39.3.383

Journal of Korean Society of Transportation ISSN:1229-1366(Print) 2234-4217(Online) 대한교통학회지

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