TY - JOUR
T1 - Nationwide synthetic human mobility dataset construction from limited travel surveys and open data
AU - Kashiyama, Takehiro
AU - Pang, Yanbo
AU - Shibuya, Yuya
AU - Yabe, Takahiro
AU - Sekimoto, Yoshihide
N1 - Publisher Copyright:
© 2024 The Author(s). Computer-Aided Civil and Infrastructure Engineering published by Wiley Periodicals LLC on behalf of Editor.
PY - 2024/11/1
Y1 - 2024/11/1
N2 - In recent years, the explosion of extensive geolocated datasets related to human mobility has presented an opportunity to unravel the mechanism behind daily mobility patterns on an individual and population level; this analysis is essential for solving social matters, such as traffic forecasting, disease spreading, urban planning, and pollution. However, the release of such data is limited owing to the privacy concerns of users from whom data were collected. To overcome this challenge, an innovative approach has been introduced for generating synthetic human mobility, termed as the “Pseudo-PFLOW” dataset. Our approach leverages open statistical data and a limited travel survey to create a comprehensive synthetic representation of human mobility. The Pseudo-PFLOW generator comprises three agent models that follow seven fundamental daily activities and captures the spatiotemporal pattern in daily travel behaviors of individuals. The Pseudo-PFLOW dataset covers the entire population in Japan, approximately 130 million people across 47 prefectures, and has been compared with the existing ground truth dataset. Our generated dataset successfully reconstructs key statistical properties, including hourly population distribution, trip volume, and trip coverage, with coefficient of determination values ranging from 0.5 to 0.98. This innovative approach enables researchers and policymakers to access valuable mobility data while addressing privacy concerns, offering new opportunities for informed decision-making and analysis.
AB - In recent years, the explosion of extensive geolocated datasets related to human mobility has presented an opportunity to unravel the mechanism behind daily mobility patterns on an individual and population level; this analysis is essential for solving social matters, such as traffic forecasting, disease spreading, urban planning, and pollution. However, the release of such data is limited owing to the privacy concerns of users from whom data were collected. To overcome this challenge, an innovative approach has been introduced for generating synthetic human mobility, termed as the “Pseudo-PFLOW” dataset. Our approach leverages open statistical data and a limited travel survey to create a comprehensive synthetic representation of human mobility. The Pseudo-PFLOW generator comprises three agent models that follow seven fundamental daily activities and captures the spatiotemporal pattern in daily travel behaviors of individuals. The Pseudo-PFLOW dataset covers the entire population in Japan, approximately 130 million people across 47 prefectures, and has been compared with the existing ground truth dataset. Our generated dataset successfully reconstructs key statistical properties, including hourly population distribution, trip volume, and trip coverage, with coefficient of determination values ranging from 0.5 to 0.98. This innovative approach enables researchers and policymakers to access valuable mobility data while addressing privacy concerns, offering new opportunities for informed decision-making and analysis.
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U2 - 10.1111/mice.13285
DO - 10.1111/mice.13285
M3 - Article
AN - SCOPUS:85195568931
SN - 1093-9687
VL - 39
SP - 3337
EP - 3353
JO - Computer-Aided Civil and Infrastructure Engineering
JF - Computer-Aided Civil and Infrastructure Engineering
IS - 21
ER -