Perspectives on Modeling and Simulation of Urban Systems with Multiple Actors and Subsystems
Time: Wed 2019-12-18 09.30
Location: T2, Hälsovägen 11C, Huddinge (English)
Subject area: Technology and Health
Doctoral student: Elhabib Moustaid , Hälsoinformatik och logistik, Hälsoinformatik och logistik, Health Informatics and Logistics
Opponent: Professor S Rajagopalan, The International Institute of Information Technology Bangalore
Supervisor: Sebastiaan Meijer, Hälsoinformatik och logistik; Gunnar Flötteröd, Systemanalys och ekonomi
Cities are the spaces of the interaction between social, physical, political, and economic entities, which makes planning and intervening in such systems difficult. Urban systems are complex adaptive systems in that their behaviours are often the result of the interaction of their components. The growth of urban systems is driven by mass urbanization. Their complexity is the result of interactions between its constituent systems and components.
Simulations and models as tools of exploration of urban systems face many challenges to be useful tools for intervening. Throughout the past decades, the use of simulation models focused on providing tools for managing functions and systems within metropolitan and urban environments. The cognizance of the complexity of these environments and the maturity of complexity science as a field of studying complex systems allow for the application of complexity science methods to study urban systems not only as physical systems but as social systems too.
As learning from simulations and models can occur both at their construction and their use, this thesis focused on model and simulation building, running, and final use. The thesis takes into account two main aspects of urban systems. First, urban systems are often multi-stakeholder, that is systems where multiple stakeholders are intervening at the same time, and sometimes without clear boundaries and agency over sub-parts of the system. Second, urban systems can have a multi-subsystem structure, where each subsystem often have their objectives and affecting the rest of the system in unfamiliar ways.
The thesis investigates through a multicase study, with three case studies, five main themes in simulation modeling that relate to increasing validity and usefulness of models for urban complex systems. Those themes are as follows; (1) the ability of simulation to be tools that capture complexity in ways that are similar to the real target systems, (2) the effects of the inclusion of experts in simulation models construction on the models, (3) the ways quantitative and qualitative ways of modeling can together make simulations and models more useful, (4) the value of simulation modeling to study connections in systems that are multi-system and multi-stakeholder, and (5) the ability to learn from models under the model building journey.
The study cases included are modeling of a city pedestrian network, a metropolitan emergency care provision, and urban mental health dynamics. The case studies provided a diversity of system granularity. The methods used for each of the case studies have also been different in able to study different levels of inclusion of expert knowledge, data, and theoretical models.
Besides its contribution to each of the case studies, with new models and simulation approaches, the thesis contributes to the five themes it investigated. It showed simulation modeling to be able to exhibit multiple elements of complexity. It also showed the ability of expert knowledge to help models become more useful and valid either by increasing their realism or level of representation. This result is achieved by the contextualization of the expert knowledge in the case of pedestrian modeling, and its full exploration in the mental health modeling. Furthermore, the thesis shows ways in which simulation and modeling can find and investigate bridges between urban subsystems. The outcomes suggest that simulation modeling can be a useful tool for exploring different kinds of complexity in urban systems as multi-actor and multi-system systems. Models can mirror the complexity of urban systems in their structure. They can also be ways of exploring non-intuitive behaviors and dynamics. Expert knowledge, in particular, is shown throughout the thesis to be able to help simulations achieve more validity and usefulness.