Yuki Arai

Study on the spatial trip pattern of public transport users using an IC card data

Kazushi Sano , Hiroaki Nishiuchi

In the local city, the decrease of the public transport user becomes the problem now. I lower it and do service cost by decreasing the number of flights in Tosa Electric Railway of Kochi, but, actually, which route was used or is not grasped what kind of person used it.
In addition, the collection of large-scale data which chip cards spread and were not able to obtain by the person trip survey by a use history was enabled. However, it cannot inflect effectively without being able to confirm an example to make use of in future administration using this use history. I can grasp the use actual situation of the time space-like public transport of the user if I can make use of the use history of chip card data. The chip card is introduced in Kochi, and it can become useful information in doing time schedule revision by grasping the use actual situation of the public transport user. And devising a measure having you use the user who little, uses public transport more is easy for administration of the public transport now than I have the class of users who do not use public transport before use public transport.
I considered the factor that I influenced every use frequency and card classification of the user because the use increased the user that there was few it in the use days when I appeared with a chip card from an acquired use history from a chip card in this study and was intended that the administration side arranged better knowledge to market it in future. Specifically, I made the similar degree calculation of the time space-like trip pattern using the DTW distance and the activity pattern of the estimate of the trip purpose using the Bayesian estimate, the user of the day. I expanded grasp and the chip card data of trip properties of the user than these, and an abridgement did data item by chief ingredient analysis by provided result and chip card data. Grasp considered the factor that influenced use frequency by doing a discriminant analysis using the data which performed an abridgement every card classification

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