In this project, we aim to create high-fidelity models, validated with real-world data, of mixed- mode travel decisions and emerging mobility markets. A growing subset of travelers make decisions informed by apps that optimize (mixed-mode) routes based on user-defined preferences. Locally optimized solutions tend to cause inefficiencies that are exacerbated by risk-sensitivity (arising from endogenous and exogenous uncertainties) in travelers.

Cyber-physical systems (CPS) may be targeted by multiple simultaneous attacks, with the goal of disrupting availability, safety, and performance of the CPS.  This project aims to develop a passivity-based framework for modeling, composing, and mitigating attacks on CPS, as well as verifying the models and mitigation.  Passivity is an energy dissipation property of dynamical systems that provides basic rules for composition and analysis of interconnected systems.