  As autonomous systems begin to operate amongst humans, methods for safe
interaction must be investigated. We consider an example of a small autonomous
vehicle in a pedestrian zone that must safely maneuver around people in a
free-form fashion. We investigate two key questions: How can we effectively
integrate pedestrian intent estimation into our autonomous stack. Can we
develop an online monitoring framework to give formal guarantees on the safety
of such human-robot interactions. We present a pedestrian intent estimation
framework that can accurately predict future pedestrian trajectories given
multiple possible goal locations. We integrate this into a reachability-based
online monitoring scheme that formally assesses the safety of these
interactions with nearly real-time performance (approximately 0.3 seconds).
These techniques are integrated on a test vehicle with a complete in-house
autonomous stack, demonstrating effective and safe interaction in real-world
experiments.
