Dynamic Urban Planning: an Agent-Based Model Coupling Mobility Mode and Housing Choice. Use case Kendall Square

TL;DR

This paper introduces an agent-based model that simulates citizens' housing and mobility choices to support dynamic urban planning and policy evaluation, validated in Kendall Square, MA.

Contribution

It presents a novel agent-based model coupling housing and mobility choices for urban planning, validated in a real-world case study.

Findings

Model accurately reflects citizen decision patterns

Supports evaluation of housing incentives impacts

Enhances understanding of urban characteristic promotion

Abstract

As cities become increasingly populated, urban planning plays a key role in ensuring the equitable and inclusive development of metropolitan areas. MIT City Science group created a data-driven tangible platform, CityScope, to help different stakeholders, such as government representatives, urban planners, developers, and citizens, collaboratively shape the urban scenario through the real-time impact analysis of different urban interventions. This paper presents an agent-based model that characterizes citizens' behavioural patterns with respect to housing and mobility choice that will constitute the first step in the development of a dynamic incentive system for an open interactive governance process. The realistic identification and representation of the criteria that affect this decision-making process will help understand and evaluate the impacts of potential housing incentives that aim to promote urban characteristics such as equality, diversity, walkability, and efficiency. The calibration and validation of the model have been performed in a well-known geographic area for the Group: Kendall Square in Cambridge, MA.