DMDU: Decision Making under Deep Uncertainty

Mission Statement

To advance the methods, tools, and practice of decision-making under deep uncertainty in transportation planning, enabling more robust and responsible decisions in a rapidly changing world.

Goals

We are modelers, so this initiative takes a model-centric view of DMDU, but a big part of DMDU is moving the focus away from model forecasts and towards getting to better decisions! We seek to:

Complement predictive applications of models with insights generated from exploratory applications
Promote use of models in concert with decision makers and stakeholders
Facilitate an adaptive planning process where multiple futures are considered and immediate steps are taken to maintain flexibility and resiliency