This report describes an approach for planning under deep uncertainty, Robust Decision Making (RDM), and demonstrates its use by the El Dorado Irrigation District (EID). Using RDM, the authors and EID tested the robustness of current long-term water management plans and more robust alternatives across more than 50 futures reflecting different assumptions about future climate, urban growth, and the availability of important new supplies.

How safe should highly automated vehicles (HAVs) be before they are allowed on the roads for consumer use? In this report, RAND researchers use the RAND Model of Automated Vehicle Safety to compare road fatalities over time under a policy that allows HAVs to be deployed when their safety performance is just moderately better than human drivers and a policy that waits to deploy HAVs only once their performance is nearly perfect.

This report highlights RAND’s contributions to the Louisiana Coastal Protection and Restoration Authority’s Master Plan. Its purpose is to help policymakers in other coastal regions understand the value of a solid technical foundation to support decisionmaking on strategies to reduce flood risk, rebuild or restore coastal environments, and increase the resilience of developed coastal regions.