  Despite the long history of modelling human mobility, we continue to lack a
highly accurate approach with low data requirements for predicting mobility
patterns in cities. Here, we present a population-weighted opportunities model
without any adjustable parameters to capture the underlying driving force
accounting for human mobility patterns at the city scale. We use various
mobility data collected from a number of cities with different characteristics
to demonstrate the predictive power of our model. We find that insofar as the
spatial distribution of population is available, our model offers universal
prediction of mobility patterns in good agreement with real observations,
including distance distribution, destination travel constraints and flux. In
contrast, the models that succeed in modelling mobility patterns in countries
are not applicable in cities, which suggests that there is a diversity of human
mobility at different spatial scales. Our model has potential applications in
many fields relevant to mobility behaviour in cities, without relying on
previous mobility measurements.
