TY - JOUR
T1 - Analyzing long-term travel behaviour
T2 - 2017 ISCTC 11th International Conference on Transport Survey Methods
AU - Li, Yeun Touh
AU - Iwamoto, Takenori
AU - Schmöcker, Jan Dirk
AU - Nakamura, Toshiyuki
AU - Uno, Nobuhiro
N1 - Funding Information:
We would like to acknowledge the support of Shizutetus (Shizuoka Railway) for this study. Further we thank Mr. Maadi Saeed, PhD student at Kyoto University, for his assist ance and efforts to process some of the required data.
Publisher Copyright:
© 2018 The Authors. Published by Elsevier Ltd.
PY - 2018
Y1 - 2018
N2 - This study attempted to validate the trend of long-term usage of public transport based on the information of the smart card holder and "long-term graphical usage patterns" that are obtained via a questionnaire survey. The study was conducted in Shizuoka prefecture, Japan, where the smart card "LuLuCa" was introduced in 2006. In this paper, the monthly usage (revealed usage) of smart card data was traced back from October 2011 to February 2017; on the other side, the usage survey was distributed in early 2017 to the targeting users (monitors) to obtain their "stated usage" over time. We found that the, from the smart card data, observed long-term usage dynamics are fairly in line with their chosen pattern, though biased to more recent observations. Further, regression analysis of individual patterns suggests the trend of "actual usage" can be explained with the chosen pattern (stated usage). This suggests that obtaining pattern information can be simple way for analysts to classify users and potentially predict their future demand.
AB - This study attempted to validate the trend of long-term usage of public transport based on the information of the smart card holder and "long-term graphical usage patterns" that are obtained via a questionnaire survey. The study was conducted in Shizuoka prefecture, Japan, where the smart card "LuLuCa" was introduced in 2006. In this paper, the monthly usage (revealed usage) of smart card data was traced back from October 2011 to February 2017; on the other side, the usage survey was distributed in early 2017 to the targeting users (monitors) to obtain their "stated usage" over time. We found that the, from the smart card data, observed long-term usage dynamics are fairly in line with their chosen pattern, though biased to more recent observations. Further, regression analysis of individual patterns suggests the trend of "actual usage" can be explained with the chosen pattern (stated usage). This suggests that obtaining pattern information can be simple way for analysts to classify users and potentially predict their future demand.
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U2 - 10.1016/j.trpro.2018.10.005
DO - 10.1016/j.trpro.2018.10.005
M3 - Conference article
AN - SCOPUS:85058841876
SN - 2352-1457
VL - 32
SP - 34
EP - 43
JO - Transportation Research Procedia
JF - Transportation Research Procedia
Y2 - 24 September 2017 through 29 September 2017
ER -