Agent-based Modeling of Traffic Behavior in Growing Metropolitan Areas

The urban settlement development of the past centuries was characterized by the process of suburbanization. Currently, the process of (re-) urbanization in metropolitan areas leads to population growth. This increase results in even more traffic participants in highly condensed areas and thus challenging the urban mobility system. Capacity and frequency of service of public transportation, a city's layout and road capacities constrain urban traffic. Transitions in travel behavior in Germany (e.g. less young adults consider cars as status symbols, and thus car ownership decreases) as well as the introduction of new types of mobility, such as sharing systems and electric mobility exacerbate the challenges for the future urban mobility. Both an expansion and modernization of the transportation system and an intelligent shift of traffic streams will help to overcome those challenges. Traffic simulation software is naturally used to derive results about public transportation in metropolitan areas. With the help of agent-based modeling, however, human behavior in a certain research area can be modeled according to pre-defined rules and variables. Not every single inhabitant of the metropolitan area is represented by traffic simulation software, whereas in agent-based modeling all inhabitants will be featured in the model. Agent-based modeling is used for scenarios of the future traffic behavior and the ability to easily adapt to new constraints in the general framework of the model. The metropolitan area of Stuttgart is used as case study and MATSim is used as agent modeling software. Following the model setup, different scenarios are evaluated. The main research question focuses on the alteration of the urban mobility system when newly-built residential or industrial areas or rehabilitated areas are connected to the transport system. First results regarding the demographic development of Stuttgart are presented as well as the current status of the model itself.