Tesla Robotaxi Collision Avoidance Saves Passengers from Waymo Vehicle | Taha Abbasi

Tesla Robotaxi’s Collision Avoidance Saves Passengers from Waymo Vehicle

In a moment that perfectly encapsulates the autonomous vehicle rivalry, a Tesla Robotaxi in Austin used its Collision Avoidance Assist system to protect passengers from an approaching Waymo vehicle. The incident, captured on video and shared widely on X, shows the Tesla detecting and reacting to a potential collision scenario that the Waymo vehicle apparently failed to anticipate. For Taha Abbasi, this is not just a viral clip — it is a data point in the most important technology competition of our time.

The footage shows a Tesla operating in autonomous mode when a Waymo vehicle approaches from an intersecting trajectory. The Tesla’s system identifies the threat, calculates an evasion path, and executes a smooth avoidance maneuver — all without human intervention. The passengers, initially unaware of the danger, only realize what happened after the car has already saved them. This is the promise of autonomous driving made tangible: machines reacting faster than human reflexes allow.

Vision-Only vs. LIDAR: A Real-World Test

This incident is particularly significant because it pits Tesla’s vision-only system directly against Waymo’s LIDAR-equipped vehicle in a real-world scenario. Waymo has long argued that LIDAR provides a safety advantage over camera-only systems — the ability to precisely measure distances in three dimensions, regardless of lighting conditions. Yet here, it was the camera-based Tesla that detected and avoided the hazard while the LIDAR-equipped Waymo created it.

Taha Abbasi cautions against drawing sweeping conclusions from a single incident. Both systems have impressive safety records, and isolated events do not define overall capability. However, this incident challenges the narrative that LIDAR is inherently superior for safety-critical autonomous driving decisions. Tesla’s neural network, trained on billions of miles of real-world driving data, demonstrated a reaction that the sensor-rich Waymo system did not match.

The Austin Testing Ground

Austin has become the epicenter of the autonomous vehicle revolution. Both Tesla and Waymo operate robotaxi services in the city, giving residents a front-row seat to the technology competition. The close proximity means incidents like this — where the two systems interact — are inevitable and increasingly informative.

For Tesla, every interaction is a training opportunity. The data from this avoidance maneuver will be analyzed, validated, and used to improve the neural network for the entire fleet. This is the fundamental advantage of Tesla’s approach: every event makes every car smarter. Waymo’s system, by contrast, operates primarily on pre-mapped routes with less cross-fleet learning capability.

Collision Avoidance Assist: The Unsung Hero

Tesla’s Collision Avoidance Assist is not a new feature, but its performance in autonomous mode demonstrates a level of sophistication that casual observers often underestimate. The system processes camera feeds from eight cameras simultaneously, builds a real-time 3D model of the environment, predicts the trajectories of all nearby objects, and calculates intervention strategies — all within milliseconds.

What Taha Abbasi finds most impressive is not just the detection but the quality of the evasion maneuver. The Tesla did not slam the brakes or swerve dangerously. It executed a smooth, controlled adjustment that protected passengers without creating secondary hazards. This is the difference between a safety system that merely avoids impact and one that manages the entire dynamic situation intelligently.

The Bigger Picture

Both Tesla and Waymo are making autonomous driving safer than human driving. The real competition is not about which company is “better” in absolute terms — both are impressive. The competition is about which approach scales more effectively. Tesla’s vision-only system works on any road, in any city, with any weather condition, because it learns from the diversity of its global fleet. Waymo’s LIDAR approach works extraordinarily well in mapped geofences but requires significant investment to expand to new cities.

As Taha Abbasi sees it, the incident in Austin is a preview of a future where multiple autonomous systems share roads, interact with each other, and collectively make transportation safer. The path there will include moments of friction, and the companies that learn fastest from those moments will win.

Read more analysis at Waymo’s safety record analysis and Tesla FSD safety data comparison.

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About the Author: Taha Abbasi is a technology executive, CTO, and applied frontier tech builder. Read more on Grokpedia | YouTube: The Brown Cowboy | tahaabbasi.com