Predicting Human Mobility from Region Functions

Abstract

People in nowadays cities have been suffering from increasingly severe traffic jams due to the less awareness of how such collective human mobility are caused by urban planning. This study aims to discover the association between region functions and the resulting human mobility. We establish a linear regression model to predict the traffic flows of Beijing based on the input referred to as bags of POIs. By solving the predictor in the sense of sparse representation, we find that the average prediction precision is over 74% and each type of POI contributes differently in the predictor, which accounts for what factors and how such region functions attract people's visiting. Based on those findings, predictive human mobility could be taken into account when planning new regions and region functions.

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