SafeTREC Seminar Mar 13, 2015: Applying UrbanSim to Transportation Issues in Cities

February 17, 2015

SafeTREC Seminar

Applying UrbanSim to Transportation Issues in Cities

Fletcher Foti
Synthicity

ABSTRACT
UrbanSim is a software-based simulation system for supporting planning and analysis of urban development, incorporating the interactions between land use, transportation, the economy, and the environment. It is the result of over 15 years of active research, and has been applied to planning processes of over a dozen regional governments and large cities. Recent improvements to UrbanSim include an accessibility engine to compute walking-scale accessibility metrics over a metropolitan area in less than a second, and the ability to run real estate pro formas on the complete set of parcels in a region to understand real estate development feasibility the way a developer might. The new methodology has also received interest from the travel modeling community, and a consortium of regions has funded a pilot to create an activity-based travel model using the same core framework.

Synthicity will be releasing UrbanCanvas publicly in spring 2015. UrbanCanvas is a 3D urban design platform that allows the editing of proposed developments which can be used to create scenario inputs to UrbanSim, as well as to view UrbanSim outputs as prototypical buildings. Synthicity hopes that UrbanCanvas can become a transformative technology that allows planners and citizens to weigh in on proposed developments early enough in the process to positively affect social, economic, environmental, and aesthetic outcomes of future population and economic growth.

 SPEAKER BIO
Dr. Fletcher Foti had eight years of experience implementing high-performance database algorithms as a programmer for a small startup in Princeton, New Jersey, before returning to school to work on the UrbanSim platform at UC Berkeley with Paul Waddell as his doctoral advisor. Fletcher is now Chief Data Scientist and co-founder with Waddell of the firm Synthicity and is leading the team that is reimplementing the UrbanSim methodology using the modern data science stack, which includes Python, Pandas, GitHub, and other tools.