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, and thresholds. Learni...
Yuan-Xin Tian, Zhi-Yuan Liu, Jin-Hao Li et al.· 0 citations
RiskWorld, a risk-aware world modeling framework for shared occupancy forecasting and selective trajectory replacement, is introduced and within-setting ablations show that RiskWorld achieves lower collision rates than the current-state rescoring baseline, while forecast reuse enables additional candidates to be evalua...
Rong-Xiang Zeng, Lin-Sen Cai, Jia-Fu Zhang et al.· 0 citations
Nine metrics that make a verifier claim checkable, and coordinates for the verifiers still to be built, are closed with nine metrics that make a verifier claim checkable.
Yong-Yong Wan, Xi-Hang Yue, Zhi-Rui Liu et al.· 0 citations
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