Trajectory simulation in communities of commuters

Urban planning, development and management authorities and stakeholders need to understand and analyse the mobility patterns of urban dwellers in order to manage sociological, economic and environmental issues. Simulation is indispensable a tool for authorities and stakeholders to better design, operate and control the mobility infrastructures of smart cities. We propose an approach for the simulation of trajectories in communities of commuters. We identify communities of public transport commuters from historical automated fare collection card data using spatial latent Dirichlet allocation. We further aggregate the historical automated fare collection card data to create statistical models of visits and movements of commuters in each community. We use statistical models to simulate trajectories of synthetic individual commuters. We empirically evaluate how the synthetically generated trajectories are typical of their community of commuters and realistic.