  Bikes are among the healthiest, greenest, and most affordable means of
transportation for a better future city, but mobility patterns of riders with
different income were rarely studied due to limitations on collecting data.
Newly emergent dockless bike-sharing platforms that record detailed information
regarding each trip provide us a unique opportunity. Attribute to its better
usage flexibility and accessibility, dockless bike-sharing platforms are
booming over the past a few years worldwide and reviving the riding fashion in
cities. In this work, by exploiting massive riding records in two megacities
from a dockless bike-sharing platform, we reveal that individual mobility
patterns, including radius of gyration and average travel distance, are similar
among users with different income, which indicates that human beings all follow
similar physical rules. However, collective mobility patterns, including
average range and diversity of visitation, and commuting directions, all
exhibit different behaviors and spatial patterns across income categories.
Hotspot locations that attract more cycling activities are quite different over
groups, and locations where users reside are of a low user ratio for both
higher and lower income groups. Lower income groups are inclined to visit less
flourishing locations, and commute towards the direction to the city center in
both cities, and of a smaller mobility diversity in Beijing but a larger
diversity in Shanghai. In addition, differences on mobility patterns among
socioeconomic categories are more evident in Beijing than in Shanghai. Our
findings would be helpful on designing better promotion strategies for dockless
bike-sharing platforms and towards the transition to a more sustainable green
transportation.
