Vehicles with different capabilities for automated driving will gradually be deployed in road transportation systems over the coming decades. Mixed traffic conditions may change the characteristics of the traffic flow dynamics. 

Microscopic traffic simulation is used for studying traffic flow dynamics in transportation systems. By simulating the interactions between individual vehicles, effects caused by changes in the road infrastructure, by road closures, or by the number and the types of vehicles can be investigated. Impacts on traffic performance can be analyzed in terms of travel times, travel time delays, queue formations, or vehicle throughput. To evaluate the impact of automated driving on traffic performance using microscopic traffic simulation, existing microscopic driving models need to be further developed to describe automated driving. 

The aim of this thesis is to investigate how to further develop microscopic traffic simulation models for automated driving. In this investigation, the aspects to consider in simulation experiments including automated driving are identified. These aspects are the vehicle system, the role of authorities, the role of the users, of the infrastructure, of connectivity features, and of the sensor-based perception of the vehicles. A microscopic traffic simulation experiment showing the possible effects on a motorway in terms of vehicle throughput and travel delays is presented. 

A conceptual model that describes how driving automation systems deal with the perception tasks is proposed. Future research directions will focus on implementing this model for perception in traffic simulation platforms and on the modeling of lateral tactical maneuvers. iii