A cost opportunity model for human mobility

Characterizing mobility patterns between locations of people and goods is not only a long-standing research topic, but it has also critical practical applications in transportation science, spatial economics, sociology and many other fields. Despite the long history of modeling human mobility, we continue to lack a model can reflect the degree of people's perception of travel cost. Here, we present a cost opportunity model that assumes an individual choosing a destination is proportional to the number of opportunities at the destination, and inversely to the power of the number of intervening opportunities between the origin and destination. Further, we use real mobility data collected from a number of cities and countries to demonstrate the predictive ability of this simple model. The results show that the new model can reveal people's perception of travel cost and offers universal predictions for different types of mobility that are consistent with real observations, thus suggesting that the proposed model better captures the mechanism underlying human mobility. Besides, our model preserves the analytical property of being equivalent to a gravity model in the limit of a uniform population distribution.