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README.md

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-# RADIUS_DataSet550
 
-RADIUS_DataSet550 is the first release of the safety-critical long-tail driving scenario dataset. It contains **550 instances** in total, including **500 safety-critical long-tail scenes** and **50 normal scenes**.
+## RADIUS-Drive（及 RADIUS-Data）
 
+本仓库在 Hugging Face 上发布 RADIUS-Drive（风险感知一致性诊断评测基准）。
+This Hugging Face repo hosts RADIUS-Drive, a risk-aware diagnostic benchmark for safety-critical autonomous driving.
+
+GitHub: https://github.com/pupprtseven/RADIUS_Drive_Bench
+Paper: 
+
+## Benchmark Overview
+
+RADIUS-Drive 关注 Pseudo-Correctness（伪正确性）：
+模型可能给出表面正确的驾驶决策，但未能识别、定位或验证潜在风险机制。
+
+RADIUS-Drive targets Pseudo-Correctness, where models produce correct-looking driving decisions while failing to trigger, localize, or validate underlying risk factors.
+
+为此，RADIUS-Drive 提出 SAR（Safety → Awareness → Reasoning）诊断协议，
+通过跨阶段一致性指标，系统性评估模型在安全关键决策中的 风险感知与推理一致性。
+
+To this end, RADIUS-Drive introduces the SAR (Safety → Awareness → Reasoning) diagnostic protocol, enabling consistency-centric evaluation of risk perception and decision reasoning.
+
+## 任务 / Tasks
+### SAF（Safety）
+
+检测模型是否能够识别并响应安全关键风险信号。
+Detect whether the model correctly triggers safety awareness under risk-critical conditions.
+
+### AWR（Awareness）
+
+评估模型是否能够定位并解释风险来源，而非仅给出结果。
+Assess whether the model localizes and explains the source of risk, beyond outcome correctness.
+
+### REA（Reasoning）
+
+验证模型的决策是否基于与风险一致的因果推理过程。
+Verify whether decisions are supported by risk-consistent causal reasoning.
+
+### X-CONS（Cross-Phase Consistency）
+
+检查 Safety、Awareness 与 Reasoning 之间是否存在一致性违背（Pseudo-Correctness）。
+Evaluate cross-phase consistency to diagnose pseudo-correct behavior.
+
+## 关键约定 / Key Conventions
+
+所有样本均配备 可审计的 ground truth，支持
+reference-based injection 与 reference-free generation 两种场景构造方式。
+
+All samples provide auditable ground truth, supporting both reference-based injection and reference-free generation.
+
+## 评测结果应同时报告：
+
+阶段内性能（per-phase）
+
+跨阶段一致性指标（e.g., CF-CDA, Guess）
+
+Results should report both per-phase scores and cross-phase consistency metrics.
 ## Dataset Contents
 Each instance **X** is released as an image plus JSON sidecars: