Travel preference of bicycle-sharing users: A multi-granularity sequential pattern mining approach

Abstract

Public bicycles are an indispensable part of green public transportation and are also a convenient and economical manner for the general public. In operation management, it is very important and imperative to understand the user demand and pattern of the public bicycle system. This paper took the public bicycle system in Hohhot as the research object, collected nearly 4 years of operating data, and studied the travel preferences of users in the public bicycle system in view of multiple granularities. Specifically, the data of car rental users at three time-granularities were obtained through data extraction technology. Finally, frequent pattern mining was performed on car rental data based on different time granularities and mapped to the user’s riding preference, and then the riding modes of different car rental users founded on different time granularities were determined. Finally, this article gave different management opinions based on the different riding preferences of public bicycle users in Hohhot.