The data coming out from an independent study of Waymo autonomous vehicles is, frankly, amazing. Swiss Re, one of the largest global insurance firms based out of Zürich, reports that 25.3 million fully autonomous miles drive by Waymo vehicles resulted in a 92% reduction in car crash injuries. In plain English, Waymo self-driving tech is […]

The data coming out from an independent study of Waymo autonomous vehicles is, frankly, amazing. Swiss Re, one of the largest global insurance firms based out of Zürich, reports that 25.3 million fully autonomous miles drive by Waymo vehicles resulted in a 92% reduction in car crash injuries.

In plain English, Waymo self-driving tech is 12.5x safer than human drivers.

Let’s dig into what that means!

  • filister@lemmy.worldEnglish
    162·
    17 hours ago

    While I don’t disagree that autonomous cars are safer, I think they are comparing the Waymo city miles against mixed mileage and when you are driving at reduced speed the chance to have an accident lowers significantly.

    But yes, people get distracted all the time, can be angry, tired, etc. that will negatively affect their driving.

    • Kecessa@sh.itjust.worksEnglish
      5·
      13 hours ago

      Less accidents per km on highways because it’s all people going in the same direction at a more constant speed.

    • KayLeadfoot@fedia.ioOP
      10·
      16 hours ago

      The article covers an academic-style research paper. You might find that section of the full research paper interesting! You spotted something important, but I think you think that city driving is safer, when the opposite is true:

      https://waymo.com/research/do-autonomous-vehicles-outperform-latest-generation-human-driven-vehicles-25-million-miles/

      Here’s the part you might find interesting, the “12x safer than human” claim likely greatly understates the safety advantage, just due to the methodology of the study:

      “The garaging zip code of the insured vehicle was used as a proxy for the city (Phoenix, San Francisco, Los Angeles, Austin) in which the vehicle drives. Waymo also almost exclusively operated on surface streets (non access-controlled freeways) with a unique distribution of driving that is representative of a ride-hailing fleet. In contrast, the benchmark represents the privately insured driver population that resides in these geographic regions. The associated benchmark mileage has more freeway driving than the Waymo ADS. There are several considerations when examining these results with respect to this limitation. First, freeway driving has a lower crash rate (Scanlon et al., 2024a). Including freeway driving makes this benchmark crash rate artificially lower, so, by including freeways in this study’s benchmark, the benchmark crash rate underestimates the true driving risk of where the Waymo ADS operates. Second, driving outside of these denser urban areas that the Waymo ADS operates would likely represent a reduction in overall relative crash risk. For example, commuters from the city would likely experience a reduced crash risk as they travel to less densely populated areas (Chen et al., 2024). Previous studies have shown that most injury collisions occur within a small radius from residency, and that American drivers rarely travel far from their place of residence, with approximately 80% of one-way household trips being less than 10 miles (DOE, 2022). Third, the benchmark drivers garaged in the Waymo deployment area are not operating with the same distribution of mileage within the geographical limits as the Waymo ADS. Chen et al. (2024) explored the effect of Waymo’s driving distribution on benchmark crash risk and found that - should the benchmark driving distribution match Waymo’s in San Francisco, Phoenix, and Los Angeles - the benchmark police-reported crash rates would have been between 14% and 38% higher. Due to all three of these limitations being expected to artificially suppress the benchmark crash rate (underestimation), the benchmarking results in this study are considered to be conservative. Surely, there is an opportunity in future work to leverage new data, such as insurance telematics, to more precisely define and leverage the benchmark driving exposure data to better account for this potential confounder.”