An agent-based approach to procedural city generation incorporating Land Use and Transport Interaction models
This work addresses procedural city generation for urban planning or simulation applications, but it appears incremental as it builds on existing LUTI models and agent-based methods.
The paper tackled the problem of generating realistic artificial cities by developing an agent-based system that uses Land Use and Transport Interaction (LUTI) models to create reward functions, resulting in a system that incrementally builds cities with distinct land uses from an empty road network.
We apply the knowledge of urban settings established with the study of Land Use and Transport Interaction (LUTI) models to develop reward functions for an agent-based system capable of planning realistic artificial cities. The system aims to replicate in the micro scale the main components of real settlements, such as zoning and accessibility in a road network. Moreover, we propose a novel representation for the agent's environment that efficiently combines the road graph with a discrete model for the land. Our system starts from an empty map consisting only of the road network graph, and the agent incrementally expands it by building new sites while distinguishing land uses between residential, commercial, industrial, and recreational.