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Data-Driven Risk Fields for Safer End-to-End Autonomous Driving

Tian, Yuanxin et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognitionrobotics
Safety is a fundamental requirement for autonomous driving, yet existing end-to-end driving models still lack explicit risk-aware learning capacities. Existing rule-based risk models provide interpretable safety priors, yet their absolute risk scores depend on handcrafted functions, coefficients, an
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