Web: http://arxiv.org/abs/2205.01887

May 5, 2022, 1:12 a.m. | Anshul Nayak, Azim Eskandarian, Zachary Doerzaph

cs.LG updates on arXiv.org arxiv.org

Past research on pedestrian trajectory forecasting mainly focused on
deterministic predictions which provide only point estimates of future states.
These future estimates can help an autonomous vehicle plan its trajectory and
avoid collision. However, under dynamic traffic scenarios, planning based on
deterministic predictions is not trustworthy. Rather, estimating the
uncertainty associated with the predicted states with a certain level of
confidence can lead to robust path planning. Hence, the authors propose to
quantify this uncertainty during forecasting using stochastic approximation …

arxiv bayesian future uncertainty

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