Online monitoring for safe pedestrian-vehicle interactions
This addresses safety concerns for autonomous vehicles operating in pedestrian zones, though it is incremental as it builds on existing reachability and intent estimation methods.
The paper tackled the problem of ensuring safe interactions between autonomous vehicles and pedestrians by developing a pedestrian intent estimation framework and an online monitoring scheme, achieving real-time safety assessments in approximately 0.3 seconds.
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.