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Towards Explainable and Advisable Model for Self-driving Cars

Humans learn to drive through both practice and theory, e.g. by studying the rules, while most self-driving systems are limited to the former. Being able to incorporate human knowledge of typical causal driving behaviour should benefit autonomous …

Towards an Interpretable Deep Driving Network by Attentional Bottleneck

Deep neural networks are a key component of behavior prediction and motion generation for self-driving cars. One of their main drawbacks is a lack of transparency -- they should provide easy to interpret rationales for what triggers certain …