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Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning
2017
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Autonomous vehicle (AV) software is typically composed of a pipeline of individual components, linking sensor inputs to motor outputs. Erroneous component outputs propagate downstream, hence safe AV software must consider the ultimate effect of each component's errors. Further, improving safety alone is not sufficient. Passengers must also feel safe to trust and use AV systems. To address such concerns, we investigate three under-explored themes for AV research: safety, interpretability, and
doi:10.24963/ijcai.2017/661
dblp:conf/ijcai/McAllisterGKWSC17
fatcat:c3rj5ikybbgvrea6zl4niklxcq