ROCVMay 11

HiDrive: A Closed-Loop Benchmark for High-Level Autonomous Driving

arXiv:2605.0997281.8Has Code
Predicted impact top 15% in RO · last 90 daysOriginality Incremental advance
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For researchers in autonomous driving, HiDrive provides a more challenging and realistic testbed to evaluate systems on rare and safety-critical situations, filling gaps in current benchmarks.

The paper introduces HiDrive, a closed-loop benchmark for end-to-end autonomous driving that focuses on long-tail scenarios and advanced driving capabilities such as legal compliance, moral reasoning, and emergency response, addressing limitations of existing saturated benchmarks.

End-to-end autonomous driving has witnessed rapid progress, yet existing benchmarks are increasingly saturated, with state-of-the-art models achieving near-perfect scores on widely used open-loop and closed-loop benchmarks. This saturation does not mean that the problem has been solved; instead, it reveals that current benchmarks remain limited in scenario diversity, object variety, and the breadth of driving capabilities they evaluate. In particular, they lack sufficient long-tail scenarios involving rare but safety-critical objects and fail to assess advanced decision-making such as legal compliance, ethical reasoning, and emergency response. To address these gaps, we propose HiDrive, a new closed-loop benchmark for end-to-end autonomous driving that emphasizes long-tail scenarios and a richer evaluation of driving capabilities. HiDrive introduces a diverse set of rare objects and uncommon traffic situations, and expands evaluation from basic driving skills to more advanced capabilities, including rule compliance, moral reasoning, and context-dependent emergency maneuvers. Correspondingly, we extend previous collision-avoidance-centered metrics into a comprehensive evaluation system that encompasses collision and braking, traffic-rule compliance, and moral-reasoning indicators. Built on a more advanced physics engine, HiDrive provides physically realistic lighting and high-fidelity visual rendering, offering a more challenging and realistic testbed for assessing whether autonomous driving systems can handle the complexity of real-world deployment. The HiDrive software, source code, digital assets, and documentation are available at https://github.com/VDIGPKU/HiDrive.

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