Travel pattern analytics driven by cellular signaling data

Yu Chiun Chiou, Chih Wei Hsieh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Cellular signaling data (CSD) could be one of the primary data sources for transportation planning and demand forecasting as a result of the rapid growth in triangulation and location techniques. Utilizing CSD to analyze travel patterns requires a meticulous process to overcome data oscillation and trajectory discontinuities. This study analyzes CSD and develops analytical models to enhance the applicability of CSD in transportation planning. For this study, we invite 30 volunteers to participate in a 30-day travel diary survey to collect data. In addition, based on CSD, we develop analytical algorithms to generate travel trajectories and analyze travel patterns, including the home and work location, trip chaining, and trip purpose of the user. Comparing the model results against the diary travel survey data indicates 84% accuracy for trip estimation and 89% accuracy for trip purpose identification, suggesting that the applicability of the proposed algorithm is satisfactory.

Original languageEnglish
Article number100042
JournalAsian Transport Studies
StatePublished - Jan 2021


  • Cellular signaling data
  • Trip chaining pattern
  • Trip identification


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