Design Loop: Calibration of a Simulation of Productive Congestion Through Real-World Data for Generative Design Frameworks


This paper extends the applicability of generative design for space planning frameworks for ongoing and guided post-occupancy modifications. It involves the comparison of a graph-based productive-congestion simulation with empirical data and the use of a metaheuristic search algorithm to calibrate and fine-tune simulation parameters for greater accuracy. This methodology is demonstrated through a real-world generative designed case-study and the post-occupancy collection and processing of movement data through custom computer vision workflows.

Download publication

Related Resources

See what’s new.



Beyond heuristics: A novel design space model for generative space planning in architecture

This paper proposes a novel design space model which can be used in…



Princeton Laboratory for Embodied Computation

Commissioned by Princeton University, the Laboratory for Embodied…



Research Conversations with Fope Bademosi

Fope Bademosi, Circular Economy and Construction Researcher, shares…



Can a robot design and build its own infrastructure?

Exploring the design process for 3D printing a 5m bridge. …

Get in touch

Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.

Contact us