Spatiotemporal Travel Demand from Aggregated Mobile Positioning Data in Tokyo, Japan

• Published in: Journal of the Eastern Asia Society for Transportation Studies Vol. 15; pp. 1068 - 1076
• Main Author: ARIGA, Toshinori
• Format: Journal Article
• Language: English
• Published: Eastern Asia Society for Transportation Studies 2024
• Subjects: 250-m grid cell aggregation; big data; mobile phone positioning data; spatiotemporal travel demand analysis
• ISSN: 1881-1124
• DOI: 10.11175/easts.15.1068

Even within a fixed area, traffic volumes and choices of mode of transportation can be expected to vary throughout the day. Person-trip surveys and other conventional survey methods have limited sample sizes, and so do not always address these issues. However, providing detailed transportation service and transportation planning requires an understanding of transportation demand by time of day in small areas and regional grid cells. In this study, therefore, the author used KDDI Location Data, a big data set of origin–destination data that has recently become available, to analyze hourly travel demand with 250-m grid cells in Tokyo on a weekday in October 2018. The results show that generated traffic volumes reach a maximum at different times of the day in different cells, and that traffic volume distributions and modes of transportation tend to differ between the early morning and late hours.