TY - JOUR
T1 - Travel pattern analytics driven by cellular signaling data
AU - Chiou, Yu Chiun
AU - Hsieh, Chih Wei
N1 - Publisher Copyright:
© 2021 The Authors
PY - 2021/1
Y1 - 2021/1
N2 - 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.
AB - 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.
KW - Cellular signaling data
KW - Trip chaining pattern
KW - Trip identification
UR - http://www.scopus.com/inward/record.url?scp=85126594195&partnerID=8YFLogxK
U2 - 10.1016/j.eastsj.2021.100042
DO - 10.1016/j.eastsj.2021.100042
M3 - Article
AN - SCOPUS:85126594195
SN - 2185-5560
VL - 7
JO - Asian Transport Studies
JF - Asian Transport Studies
M1 - 100042
ER -