John Alsterda, Ph.D. candidate in the Dynamic Desing Lab will present Contingency Model Predictive Control (CMPC), a motion planning and control framework that optimizes performance objectives while simultaneously maintaining a contingency plan – an alternate trajectory that avoids a potential hazard. By preserving the existence of a feasible avoidance trajectory, CMPC anticipates emergency and keeps the controlled system in a safe state that is selectively robust to the identified hazard. CMPC is experimentally demonstrated in several driving scenarios involving uncertain danger -- obstacle avoidance, vehicle following, and icy roads. Contingency MPC approaches these potential emergencies with safe, intuitive, and interpretable behavior that balances conservatism with incentive for high performance operation.