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Validate the accuracy of crash/mileage subselection and dynamic benchmarking adjustments

Validate the absolute accuracy of the crash and mileage subselection routines and the spatial dynamic benchmarking adjustment method by comparing against ground-truth datasets and performing uncertainty quantification to assess the robustness of alignment and reweighting procedures.

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Background

The paper uses subselection (vehicle type, road type, in-transport) and a spatial dynamic benchmark adjustment to align human and ADS data. The authors acknowledge that the absolute accuracy of these methods remains unknown.

Independent validation and formal uncertainty assessment would increase confidence in the methodological choices and the resulting safety impact conclusions.

References

The absolute accuracy of the crash and mileage subselection and dynamic benchmark adjustment are relatively unknown.

— Comparison of Waymo Rider-Only Crash Rates by Crash Type to Human Benchmarks at 56.7 Million Miles (2505.01515 - Kusano et al., 2 May 2025) in Appendix – Study Conformance to the RAVE Checklist (Table A11, Recommendation 2a Justification)