Limits of Probabilistic Safety Guarantees when Considering Human Uncertainty
Richard Cheng,Richard M. Murray,Joel W. Burdick,Richard Cheng,Richard M. Murray,Joel W. Burdick
When autonomous robots interact with humans, such as during autonomous driving, explicit safety guarantees are crucial in order to avoid potentially life-threatening accidents. Many data-driven methods have explored learning probabilistic bounds over human agents’ trajectories (i.e. confidence tubes that contain trajectories with probability δ), which can then be used to guarantee safety with prob...
