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.
@article{arxiv.1910.05599,
title = {Online monitoring for safe pedestrian-vehicle interactions},
author = {Peter Du and Zhe Huang and Tianqi Liu and Ke Xu and Qichao Gao and Hussein Sibai and Katherine Driggs-Campbell and Sayan Mitra},
journal= {arXiv preprint arXiv:1910.05599},
year = {2020}
}