This NetLogo model is an implementation of the mostly verbal (and graphic) model in Jarret Walker’s Human Transit: How Clearer Thinking about Public Transit Can Enrich Our Communities and Our Lives (2011). Walker’s discussion is in the chapter “Connections or Complexity?”. See especially figure 12-2, which is on page 151.

In “Connections or Complexity?”, Walker frames the matter as involving a choice between two conflicting goals. The first goal is to minimize connections, the need to make transfers, in a transit system. People naturally prefer direct routes. The second goal is to minimize complexity. Why? Well, read the chapter, but as a general proposition we want to avoid unnecessary complexity with its attendant operating characteristics (confusing route plans in the case of transit) and management and maintenance challenges. With complexity general comes degraded robustness and resilience.

How do we, how can we, choose between these conflicting goals? The grand suggestion here is that we only choose indirectly, implicitly. In the present example of connections versus complexity we model various alternatives and compare them on measures of performance (MoP) other than complexity or connections per se. The suggestion is that connections and complexity are indicators of, heuristics for, other MoPs that are more fundamental, such as cost, robustness, energy use, etc., and it is these that we at bottom care most about. (Alternatively, and not inconsistently, we can view connections and complexity as two of many MoPs, with the larger issue to be resolve in light of many MoPs, including but not limited to complexity and connections.) We employ modeling to get a handle on these MoPs. Typically, there will be several, taking us thus to a multiple criteria decision making (MCDM) situation. That’s the big picture.

The purpose of the model is to better understand, how different factors for human residential choices affect the city’s segregation pattern. Therefore, a Schelling (1971) model was extended to include ethnicity, income, and affordability and applied to the city of Salzburg. So far, only a few studies have tried to explore the effect of multiple factors on the residential pattern (Sahasranaman & Jensen, 2016, 2018; Yin, 2009). Thereby, models using multiple factors can produce more realistic results (Benenson et al., 2002). This model and the corresponding thesis aim to fill that gap.

LUXE is a land-use change model featuring different levels of land market implementation. It integrates utility measures, budget constraints, competitive bidding, and market interactions to model land-use change in exurban environment.

The Urban Traffic Simulator is an agent-based model developed in the Unity platform. The model allows the user to simulate several autonomous vehicles (AVs) and tune granular parameters such as vehicle downforce, adherence to speed limits, top speed in mph and mass. The model allows researchers to tune these parameters, run the simulator for a given period and export data from the model for analysis (an example is provided in Jupyter Notebook).

The data the model is currently able to output are the following:

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MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.

MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.

Abstract model investigating the determinants of inter- and intra-urban inequality in contact with nature. We explore the plausibility of a social integration hypothesis - whereby the primary factor in decisions to visit Urban Green Spaces (UGS) is an assessment of who else is likely to be using the space at the same time, and the assessment runs predominantly along class lines. The model simulates four cities in Scotland and shows the conditions under which the mechanisms theorised are sufficient to reproduce observed inequalities in UGS usage.

SiFlo is an ABM dedicated to simulate flood events in urban areas. It considers the water flowing and the reaction of the inhabitants. The inhabitants would be able to perform different actions regarding the flood: protection (protect their house, their equipment and furniture…), evacuation (considering traffic model), get and give information (considering imperfect knowledge), etc. A special care was taken to model the inhabitant behavior: the inhabitants should be able to build complex reasoning, to have emotions, to follow or not instructions, to have incomplete knowledge about the flood, to interfere with other inhabitants, to find their way on the road network. The model integrates the closure of roads and the danger a flooded road can represent. Furthermore, it considers the state of the infrastructures and notably protection infrastructures as dyke. Then, it allows to simulate a dyke breaking.
The model intends to be generic and flexible whereas provide a fine geographic description of the case study. In this perspective, the model is able to directly import GIS data to reproduce any territory. The following sections expose the main elements of the model.

This model is a replication model which is constructed based on the existing model used by the following article:
Brown, D.G. and Robinson, D.T., 2006. Effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecology and society, 11(1).
The original model is called SLUCE’s Original Model for Experimentation (SOME). In Brown and Robinson (2006)’s article, the SOME model was used to explore the impacts of heterogeneity in residential location selections on the research of urban sprawl. The original model was constructed using Objective-C language based on SWARM platform. This replication model is built by NetLogo language on NetLogo platform. We successfully replicate that model and demonstrated the reliability and replicability of it.

The Episim framework builds upon the established transportation simulation MATSim and is capable of tracking agents’ movements within a network and thus computing infection chains. Several characteristics of the virus and the environment can be parametred, whilst the infection dynamics is computed based upon a compartment model. The spread of the virus can be mitigated by restricting the agents’ activity in certain places.

While the world’s total urban population continues to grow, not all cities are witnessing such growth, some are actually shrinking. This shrinkage causes several problems to emerge including population loss, economic depression, vacant properties and the contraction of housing markets. Such problems challenge efforts to make cities sustainable. While there is a growing body of work on study shrinking cities, few explore such a phenomenon from the bottom up using dynamic computational models. To overcome this issue this paper presents an spatially explicit agent-based model stylized on the Detroit Tri-county area, an area witnessing shrinkage. Specifically, the model demonstrates how through the buying and selling of houses can lead to urban shrinkage from the bottom up. The model results indicate that along with the lower level housing transactions being captured, the aggregated level market conditions relating to urban shrinkage are also captured (i.e., the contraction of housing markets). As such, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to achieve urban sustainability.