  We study the class of reach-avoid dynamic games in which multiple agents
interact noncooperatively, and each wishes to satisfy a distinct target
criterion while avoiding a failure criterion. Reach-avoid games are commonly
used to express safety-critical optimal control problems found in mobile robot
motion planning. Here, we focus on finding time-consistent solutions, in which
future motion plans remain optimal even when a robot diverges from the plan
early on due to, e.g., intrinsic dynamic uncertainty or extrinsic environment
disturbances. Our main contribution is a computationally-efficient algorithm
for multi-agent reach-avoid games which renders time-consistent solutions for
all players. We demonstrate our approach in two- and three-player simulated
driving scenarios, in which our method provides safe control strategies for all
agents.
