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Comparative Safety Performance of Autonomous- and Human Drivers: A Real-World Case Study of the Waymo One Service

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arxiv 2309.01206 v1 pith:X2STJYYS submitted 2023-09-03 cs.RO

classification cs.RO
keywords humandriverwaymoclaimscpmmautonomousdamagedrivers
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This study compares the safety of autonomous- and human drivers. It finds that the Waymo One autonomous service is significantly safer towards other road users than human drivers are, as measured via collision causation. The result is determined by comparing Waymo's third party liability insurance claims data with mileage- and zip-code-calibrated Swiss Re (human driver) private passenger vehicle baselines. A liability claim is a request for compensation when someone is responsible for damage to property or injury to another person, typically following a collision. Liability claims reporting and their development is designed using insurance industry best practices to assess crash causation contribution and predict future crash contributions. In over 3.8 million miles driven without a human being behind the steering wheel in rider-only (RO) mode, the Waymo Driver incurred zero bodily injury claims in comparison with the human driver baseline of 1.11 claims per million miles (cpmm). The Waymo Driver also significantly reduced property damage claims to 0.78 cpmm in comparison with the human driver baseline of 3.26 cpmm. Similarly, in a more statistically robust dataset of over 35 million miles during autonomous testing operations (TO), the Waymo Driver, together with a human autonomous specialist behind the steering wheel monitoring the automation, also significantly reduced both bodily injury and property damage cpmm compared to the human driver baselines.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Determining Absence of Unreasonable Risk: Approval Guidelines for an Automated Driving System Deployment

    cs.SE 2025-05 unverdicted novelty 5.0 of 10

    Twelve acceptance criteria spanning system safety, testing, risk management, and field monitoring form a proposed framework for approving automated driving system deployments.

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