Agent-based modelling has proven as an effective approach to analyze, reconstruct, and predict systems with many individual entities. Typical use cases include segregation processes, predator/prey models, or supply chain optimization (TISUE 2004). Most of these models work within the framework of a “patch-dominated” world, where agents move within a world consisting of square-cells named patches (AL-DMOUR 2011). The development of network specific extensions for simulation software like the “network” and “gis” extensions of NetLogo have allowed to apply agent-based theories to spatial data (CROOKS 2012). This allows the shift from a patch to a network concept. However, there are still some shortcomings that are not satisfyingly solved within the NetLogo software that may hinder an efficient and realistic simulation of agent movements along spatial networks. This work evaluates the role of scale and time in agent-based traffic models and offers suggested implementations to allow for easier and more realistic parameterization and runtime analysis of traffic models. It will also discuss performance issues with the shortest path calculation in NetLogo, and provide a possible solution to increase the simulation speed. The model and analysis derived in this project are based on a polyline shapefile that contains the street network of Salzburg city.