Land Use and Mobility Simulation Model

We developed a simulation model which could show the behaviors of the population at baseline and in response to each intervention. A synthetic population to be simulated was generated using a combination of individual (American Community Survey) and aggregated (Public Use Microdata Sample) census data products. For each synthetic individual in each scenario: home location choice, daily activity schedule, transportation modes and routes would be simulated. To ensure that the behaviors were realistic, a range of behavioral models were developed and calibrated using open source data. For example, a generalized nested logit model was developed and calibrated using the National Household Travel Survey data, to predict modes of transportation including potential uptake of new mobility modes.

Performance Indicators

We developed and evaluated a range of key performance indicators for each simulated scenario. Prior to the collaboration, Ford had engaged with the local community to develop a set of project goals and community commitments—the 'Tomorrow Together' goals—and these provided a starting point for the research team to develop a set of quantifiable indicators. The set of indicators we developed are summarized in the table below. These were grouped into five categories: Economic Performance, Innovation Potential, Sustainable Mobility, Sustainable Buildings and Community Benefits.

User Interaction

Two modes were developed for stakeholders to interact with the models and explore scenarios—a range of static scenarios and an interactive Cityscope model.

Scenarios

A set of five scenarios of interest were developed through consultation with the Ford team. These scenarios represented varying combinations of interventions, starting with the Business-as-Usual scenario and culminating in an 'Innovation Community' scenario in which built area changes, mobility innovations and housing and amenity provision were combined. The results of the scenarios are summarized below.

Interactive CityScope

Finally, an open-ended web-based tool was developed to allow users to interactively experiment with land-use interventions and get feedback on the predicted urban performance. CityScopeJS was developed in Javascript using the React framework. Users can select from the list of predefined land-uses by clicking the icons in the pane to the right of the screen, select a number of floors and then apply their selection to the interactive grid cells using a ”painting” motion. The urban performance metrics are given in near-real-time in the form of spatial visualizations and charts. Different model outputs can be shown on screen by selecting from the list of different layers in the pane to the left of the screen.

Through the fixed scenarios explored and early experimentation with the interactive model, it became clear that individual interventions such as the development of office space or the provision of a new mobility option can improve some aspects of urban performance but these improvements are often traded off against other aspects. However, combining multiple interventions together in a compact mixed use community was shown to lead to improvements across all of the diverse dimensions analyzed.