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title: Waymo vs Tesla: Two Ways to Build Self-Driving Cars
description: A comparison of Waymo's and Tesla's autonomous driving architectures across sensing, representation, prediction, planning, validation, and training. Waymo...
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og:description: A comparison of Waymo's and Tesla's autonomous driving architectures across sensing, representation, prediction, planning, validation, and training. Waymo...
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# Waymo vs Tesla: Two Ways to Build Self-Driving Cars

**[ByteByteGo](https://daily.dev/sources/bytebytego)** · 13 min read · 1 upvotes · 0 comments

## Summary

A comparison of Waymo's and Tesla's autonomous driving architectures across sensing, representation, prediction, planning, validation, and training. Waymo relies on lidar, radar, and cameras feeding a Foundation Model that produces structured, inspectable representations, verified through separate Teacher/Student models and a Safety Framework, reporting 220.6 million rider-only miles and published crash-reduction statistics. Tesla relies on a pure-vision camera approach with neural networks trained on fleet telemetry from millions of consumer vehicles, verified currently by human drivers under Full Self-Driving (Supervised), with its own Vehicle Safety Report methodology. The piece frames the core tradeoff as how much knowledge is fixed in advance (Waymo) versus computed at drive time (Tesla).

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.bytebytego.com/p/waymo-vs-tesla-two-ways-to-build>

## Questions this post answers

### How many rider-only miles has Waymo driven and what safety improvement does it report compared to human drivers?

Waymo reports 220.6 million rider-only miles through March 2026 across five metro areas, with no human in the driver's seat. Measured against human crash rates in the same operating areas, Waymo reports a 94% reduction in serious injury or worse crashes and an 82% reduction in injury-causing crashes. The methodology is peer-reviewed and the raw data is downloadable for third-party reproduction.

_Anyone comparing autonomous driving safety claims can follow ongoing coverage of these metrics on daily.dev._

### Does Tesla's Full Self-Driving use lidar or radar sensors?

No, Tesla's Model 3 and Model Y run camera-based Tesla Vision without radar, relying entirely on a 'pure vision' approach using exterior cameras and neural network processing rather than lidar or radar hardware. This contrasts with Waymo's sixth-generation system, which carries 13 cameras, four lidar units, six radar units, and audio receivers for redundancy.

_Engineers evaluating sensor tradeoffs in autonomous systems can track this debate through daily.dev._

### How does Tesla measure collision reduction with Full Self-Driving Supervised engaged?

Tesla's Vehicle Safety Report compares Teslas with Full Self-Driving (Supervised) engaged against manually driven Teslas using the same telemetry pipeline, reporting 7 times fewer major and minor collisions and 5 times fewer off-highway collisions. A collision counts as system-engaged if the feature was active within five seconds beforehand, and Tesla assigns no fault determination in the data.

_Developers weighing how vendors report safety metrics for driver-assist systems can follow this analysis on daily.dev._

## Similar posts on daily.dev

- [Waymo CEO explains why Tesla’s camera-only self-driving falls short](https://daily.dev/posts/waymo-ceo-explains-why-tesla-s-camera-only-self-driving-falls-short-ithapwkvi) · Hacker News · 0 upvotes · 0 comments
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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#career](https://daily.dev/tags/career), [#tesla](https://daily.dev/tags/tesla), [#autonomous-cars](https://daily.dev/tags/autonomous-cars)

[View this post on daily.dev](https://daily.dev/posts/waymo-vs-tesla-two-ways-to-build-self-driving-cars-smlysvlpu)

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