Automating synthetic trip data generation for an agent-based simulation of urban mobility
This paper explores the use of an automated pipeline to construct synthetic (artificially derived) trip data from aggregate socio-demographic sources to build a simulation of individual vehicles interacting with one another. The study shows that quality data sources are required in order to do this effectively and accurately. It is shown that aspects of typical patterns and behaviours may still n