A multi-scale unified model of human mobility in urban agglomerations.

ABSTRACT: Understanding human mobility patterns is vital for the coordinated development of cities in urban agglomerations. Existing mobility models can capture single-scale travel behavior within or between cities, but the unified modeling of multi-scale human mobility in urban agglomerations is still analytically and computationally intractable. In this study, by simulating people's mental representations of physical space, we decompose and model the human travel choice process as a cascaded multi-class classification problem. Our multi-scale unified model, built upon cascaded deep neural networks, can predict human mobility in world-class urban agglomerations with thousands of regions. By incorporating individual memory features and population attractiveness features extracted by a graph generati

SUBMITTER: Chen Y 

PROVIDER: S-EPMC10682749 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature