Predicting Intra-City Mobility Flows without Using Historical Flow Data

Abstract This work in progress proposes a new deep learning-based method to generate intra-city mobility flows without using historical flow data. The proposed model takes the population/traveler volume of individual regions as inputs, and assumes no further geographical or mobility information about these regions, making it an effective and simple approach to be applied to many cities.