PURPOSES : Transportation researchers have contributed to try to both understand and accumulate scientifically how individuals move across time and space. Currently, data generated from household travel diary surveys have been used as the basis of travel behavior (or human mobility patterns) analysis in transportation planning and have been buoyed in a sustainability for decades. Against this backdrop, this study introduces mobile phone signaling big data that can convey more detailed human mobility information across time and space and supplement travel behavior analysis.
METHODS: We propose a usable and useful dataset driven from the mobile phone signaling data for better travel behavior analysis. Several data-driven approaches have been tried to estimated and calculate variables inserted into the dataset. RESULTS: In the result, this paper discussed the promise of mobile phone based dataset to applications for inferring human mobility patterns applied to directly transport policy.
CONCLUSIONS: It is our hope that this study will stimulate future studies on transportation planning and mobility analysis using mobile phone signaling data in Korea.

ABSTRACT
 1. 서론
 2. 모바일 빅데이터
  2.1. 데이터 유형
  2.2. 데이터 전처리
  2.3. MPSD 데이터 기초 특성 분석
  2.4. 조사 기반 데이터와 MPSD 데이터의 비교
 3. 모빌리티 분석을 위한 데이터 셋
  3.1. 통행 특성 구분
  3.2. 통행 순서 부여
  3.3. 통행 목적 구분
  3.4. 통행 수단 구분
  3.5. 데이터 기반 통행사슬 형성
 4. 활용성 검토
  4.1. 상시적·광역적 고해상도 통행 분석
  4.2. 출퇴근 통행 특성 분석
  4.3. 사회경제적 측면 분석
 5. 결론
 REFERENCES

• 송태진(한국교통연구원 부연구위원) | Song Tai-Jin 교신저자
• 이해선(한국교통연구원 연구원) | Lee Haesun