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Short answer: Yes—Waymo’s current driverless service has accumulated substantial evidence of lower crash involvement and lower injury-crash rates than human drivers in the specific cities and operating conditions studied. But the claim that Waymos are so safe that crashes are “almost comical” is rhetoric, not a scientific finding.
Through March 2026, Waymo says its vehicles had driven 220.6 million rider-only miles and experienced 94% fewer serious-injury-or-worse crash involvements than its human-driver benchmark. An independent July 2026 Insurance Institute for Highway Safety study found 68% fewer police-reportable crash involvements per mile in four cities. Those are meaningful results—but they coexist with recalls, edge-case failures, a child-strike investigation, and fatal crashes involving Waymo vehicles.
The original headline came from a real safety signal, but it overstated what the evidence could prove. Waymo’s robotaxis do not appear to be crash-proof, and the available data does not show that every autonomous vehicle is safer than every human driver in every environment. It does show something narrower and more defensible: in the mapped, supported operating domains where Waymo currently runs driverless service, its vehicles have been involved in substantially fewer serious and injury-producing crashes per mile than comparable human-driven vehicles.
The evidence is now stronger than it was when Futurism published its October 3, 2025 story. Waymo has added more than 120 million rider-only miles to its dataset, and IIHS has supplied an independent comparison using a different crash-screening method. The right conclusion is not that Waymo’s safety claims are “just marketing.” Nor is it that Waymo can be trusted to handle every unusual road situation without failure.
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What the 2025 Futurism story actually reported
Futurism’s story followed a September 2025 Waymo update covering 96 million fully autonomous, or rider-only, miles through June 2025. At that point, Waymo reported 91% fewer crashes resulting in serious injury or worse than its human-driver comparison benchmark.
The story also referenced 45 Waymo crashes reported to the government between mid-February and mid-August 2025. A case-level review suggested that many involved another driver, a stationary Waymo vehicle, or an unusual circumstance rather than an obvious mistake by Waymo’s driving system.
The underlying data was not fabricated. The problem was that the headline compressed several different claims into one impression. It did not fully explain that:
- Waymo’s principal metric measures crash involvement, not legal fault.
- The comparison uses specific cities, road types, time periods, and operating conditions.
- Waymo vehicles have broader reporting obligations than ordinary human drivers.
- A low injury-crash rate does not measure every operational hazard, such as blocking traffic or becoming stranded.
- The data available in 2025 did not include the later independent IIHS analysis, subsequent recalls, or the January 2026 child-strike investigation.
The latest Waymo numbers through March 2026
Waymo’s Safety Impact dashboard, reflected in a June 2026 update, now covers 220.6 million rider-only miles through March 2026. The company compares its crash-involvement rates with human-driver rates in the areas where it operates, adjusting for the geographic distribution of Waymo’s driving.
| Outcome | Waymo result compared with human benchmark |
|---|---|
| Crashes resulting in serious injury or worse | 94% fewer |
| Crashes involving airbag deployment in any vehicle | 82% fewer |
| Crashes involving any reported injury | 82% fewer |
| Injury-causing pedestrian crashes | 93% fewer |
| Injury-causing cyclist crashes | 84% fewer |
| Injury-causing motorcycle crashes | 84% fewer |
These are large differences, especially the 94% reduction in serious-injury-or-worse crash involvement. But “94% safer” would be an inaccurate shorthand. The figure applies to one outcome category and one comparison—not to every kind of collision, every road, or every Waymo software release.
Waymo reports the underlying rates as incidents per million miles, or IPMM:
| Outcome | Waymo IPMM | Human benchmark IPMM |
|---|---|---|
| Serious injury or worse | 0.01 | 0.23 |
| Any injury reported | 0.71 | 3.91 |
| Airbag deployment in any vehicle | 0.30 | 1.68 |
| Airbag deployment in the Waymo vehicle | 0.06 | 1.11 |
The figures are rounded and should not be read as the exact probability that a particular passenger will be injured on a particular trip. They are fleet-level rates calculated across large populations of vehicle miles. Rare events can produce unstable estimates in smaller subgroups, which is why a rounded percentage should not be treated as a permanent property of the system.
The strongest independent check: IIHS
The most important development since the 2025 story is the July 2026 IIHS study. Rather than simply repeating Waymo’s preferred severity comparisons, IIHS examined roughly 50 million miles of Waymo driverless operation in Phoenix, San Francisco, Los Angeles, and Austin.
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IIHS manually reviewed federally reported automated-vehicle crash narratives and asked whether a reasonable person would normally have reported each event to police. This matters because automated-vehicle reporting requirements can capture minor contacts that would never appear in ordinary police-based human-driver data.
After that screening, IIHS found that Waymo’s driverless vehicles had:
- 68% fewer police-reportable crash involvements per mile than human drivers overall in the studied cities and periods.
- 85% fewer single-vehicle crashes per mile.
- 81% fewer injury crashes per mile.
- 91% fewer instances of rear-ending another vehicle.
- 40% fewer instances of being rear-ended.
IIHS also found that only about 22% of reported Level 4 crash involvements appeared police-reportable or possibly police-reportable under normal circumstances. About two-thirds of the Level 4 incidents in the study occurred during driverless operation. The researchers concluded that Waymo vehicles were unlikely to be the striking vehicle or the primary contributor in the crashes they examined.
The city-by-city results show why the aggregate finding should not be turned into a universal guarantee:
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|---|---|
| Phoenix | 76% lower |
| San Francisco | 35% lower |
| Los Angeles | 71% lower |
| Austin | 4% higher |
Austin is particularly important. Waymo’s rate was 4% higher than the human comparison there, although IIHS said the Austin sample was relatively small. That does not overturn the overall result, but it demonstrates that performance can vary by city and that the aggregate number hides local differences.
IIHS described its manual narrative-coding approach as valuable but difficult to scale as automated-vehicle deployments grow. In other words, the study is meaningful independent corroboration—not a final, universally applicable safety certification.
What exactly does “safe” mean here?
Several different propositions are often mixed together when people discuss robotaxi safety:
- Crash involvement: How often is a Waymo vehicle involved in a collision per mile?
- Causation or fault: Did Waymo’s behavior contribute to the collision, and who is legally responsible?
- Crash severity: Did the event cause property damage, an airbag deployment, an injury, a serious injury, or a death?
- Operational safety: Does the vehicle handle unusual conditions without blocking emergency responders, stopping in a dangerous location, becoming stranded, violating traffic controls, or creating delays and unsafe maneuvers?
Waymo’s main dashboard is primarily a crash-involvement and outcome analysis. Waymo says it counts collisions regardless of which party was at fault. That is a defensible design choice: it avoids subjective fault judgments and produces a metric that can be compared consistently over time.
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But it also creates a communication trap. A Waymo that is rear-ended while stopped may be blameless in the collision, yet it still appears in the crash-involvement numerator. Conversely, an incident in which Waymo’s behavior contributed to a crash cannot be dismissed simply because another road user also made a mistake.
“Involved” is not the same as “caused,” and “not apparently at fault” is not the same as “irrelevant to the safety analysis.”
What is a rider-only mile?
A rider-only, or RO, mile is a mile driven without a human driver in the vehicle. It is the relevant exposure measure for Waymo’s commercial driverless service—not a mile accumulated with a safety driver monitoring the vehicle from the front seat.
Waymo describes the service as SAE Level 4 operation within a defined operating domain. Remote assistance can provide contextual information when the vehicle encounters an unusual situation, but Waymo says remote personnel are not continuously driving the car. That distinction is important: a remote-assistance system does not automatically mean a human is performing the driving task from a control room.
The 220.6 million-mile figure also does not mean that Waymo has tested every possible road or weather condition. It refers to the rider-only miles included in the company’s current analysis. It should not be generalized to:
- Every test mile Waymo has ever driven.
- Every future software or sensor configuration.
- Highway driving in general.
- Every Waymo city, climate, or road design.
- Other autonomous-driving systems.
- Tesla’s supervised driver-assistance systems, which are a different technology and operating model.
How Waymo compares its vehicles with human drivers
The basic idea is straightforward: compare vehicle crash involvements per million miles rather than comparing raw crash totals. A fleet that drives more miles will naturally accumulate more incidents, so mileage is the necessary denominator.
The details are more complicated. Waymo’s analysis uses:
- Waymo vehicle involvement data reported under the NHTSA Standing General Order.
- Human-driver crash data from police reports and state-maintained records.
- Vehicle-miles-traveled data for the relevant areas.
- Adjustments for where Waymo drives within its service geography.
- Separate categories for injury, serious injury, airbag deployment, and other crash outcomes.
The use of vehicle involvement rather than crash counts avoids a unit mismatch. A single collision can involve several vehicles, so comparing the number of Waymo vehicles involved with the number of human-driver crashes would not be an apples-to-apples calculation. Waymo’s methodology FAQ explains why the comparison is built around crashed vehicles per million miles.
The reporting problem cuts in both directions
Waymo vehicles must report certain incidents under NHTSA’s Standing General Order, including some minor-contact events. Human-driver comparisons generally rely on police reports, and many ordinary crashes never reach the police.
Waymo cites estimates that approximately 69.7% of property-damage crashes and 31.9% of injury crashes are not reported to police. That creates two possible distortions:
- If every minor Waymo contact is counted while comparable minor human crashes are missing, Waymo can look worse than it should.
- If human underreporting is not adequately corrected, human driving can look safer than it really is.
Waymo applies an underreporting correction for its any-injury comparison. It says there is no reliable correction available for airbag-deployment data or serious-injury benchmarks. This limitation does not make the comparison useless, but it means the exact size of the advantage depends partly on assumptions about reporting.
IIHS addressed the same problem differently by manually coding whether federally reported automated-vehicle incidents would ordinarily have been police-reportable. That approach improves comparability for the study, but it depends on narrative interpretation and is difficult to perform at unlimited scale.
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The current Waymo dashboard covers driving in Los Angeles, the San Francisco Bay Area, Phoenix, Austin, and Atlanta. The IIHS study examined Phoenix, San Francisco, Los Angeles, and Austin. These are not interchangeable datasets, and neither establishes a nationwide safety rate.
Waymo’s data is primarily based on surface streets. The company has said freeway mileage historically has not been sufficient for the same statistical analysis. A robotaxi that performs impressively on mapped urban streets should not automatically be assumed to perform equally well on every freeway, rural road, snow-covered route, or temporary construction layout.
Conditions that could affect generalization include:
- Snow, ice, heavy rain, flooding, dust, and other weather not represented equally across the service areas.
- Road markings, signs, traffic patterns, and construction practices in different regions.
- Unusual police direction or emergency-response procedures.
- Roads outside Waymo’s mapped and supported operating domain.
- Different mixes of pedestrians, cyclists, motorcycles, commercial vehicles, and aggressive human drivers.
- New vehicle platforms or software versions with limited real-world exposure.
Waymo also generally combines relevant rider-only miles accumulated to date, which increases statistical power. The trade-off is that the aggregate can conceal performance differences between software releases. More recent releases make up a larger share of the newest mileage, but the published overall number is not a clean head-to-head test of one version against another.
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Waymo’s earlier research includes a 7.1-million-mile comparison and a 56.7-million-mile crash-type analysis. Those studies form part of an evolving evidence base, but the same principle applies: each result is tied to its own dates, cities, data sources, and definitions.
Why might Waymo be safer than an average human driver?
The observed results are consistent with several plausible advantages, although the available data does not prove how much each factor contributes.
- No fatigue, distraction, alcohol impairment, or emotional driving: An automated system does not glance at a phone, fall asleep, drive after drinking, or intentionally speed out of frustration.
- Consistent monitoring: Waymo uses a sensor suite designed to continuously observe the vehicle’s surroundings rather than relying on a human’s attention and visual scanning.
- Controlled speed and behavior: Waymo says its vehicles are designed to follow speed limits and use conservative driving behavior.
- Seat-belt protection: The service requires or promotes seat-belt use, removing one common source of human-driver risk.
- Defined deployment: The vehicle operates in a mapped, supported area rather than being expected to solve every road condition immediately.
- Formal readiness reviews: Waymo says it evaluates major changes before deployment rather than treating public roads as an uncontrolled experiment.
Waymo’s deployment-readiness explanation and its readiness paper describe 12 review criteria:
- System safety
- Cybersecurity
- Verification and validation
- Collision-avoidance testing
- Predicted collision risk
- Impeded progress
- Rules-of-the-road compliance
- Vulnerable-road-user interactions
- High-severity assessment
- Conservative severity estimates
- Risk management
- Field safety
These practices are relevant to understanding why a driverless fleet might outperform humans. They are not, by themselves, independent proof that a particular design feature caused the observed reduction. The strongest evidence remains the outcome data and its independent comparison with human driving.
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What happened in the 45 serious reported crashes?
A September 2025 review by Understanding AI examined 45 Waymo crashes involving an injury or airbag deployment between mid-February and mid-August 2025. This was a selected set of reported serious incidents, not a list of every physical contact in Waymo’s mileage.
The review found:
- 24 incidents occurred while the Waymo was stationary.
- Seven involved another vehicle rear-ending a Waymo that was moving.
- Three involved passengers opening doors into passing bicycles or scooters.
- One involved a Waymo wheel detaching.
The reviewer judged that most apparent driving-error cases appeared mostly or completely attributable to another driver, while acknowledging a handful in which Waymo’s software might have handled the situation better.
This is useful case-level context, but it is not an official legal fault adjudication. A stationary vehicle can still raise safety questions about where it stopped, how it reacted, or whether it created a hazard. A passenger opening a door is not necessarily a perception or planning failure, but it remains part of the real-world safety experience of a robotaxi.
Recalls show why “safer” does not mean “defect-free”
Waymo has issued safety recalls, including software recalls. These do not automatically disprove the fleet-level crash comparison. They do demonstrate that a system can have a very low aggregate crash rate while still containing specific and potentially serious edge-case defects.
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In 2024, Waymo announced a software recall after two vehicles struck the same configuration involving a towed pickup truck. The event led to a correction of the previous software. See Waymo’s recall announcement.
Chains, gates, and gate-like barriers
In May 2025, NHTSA recall 25E-034 covered approximately 1,212 vehicles using prior fifth-generation software. Under some circumstances, the system could mishandle chains, gates, and other gate-like barriers. The recall report said there were no injuries associated with the relevant collisions. The NHTSA report is the authoritative source for the recall details.
School-bus stop arms and flashing lights
In December 2025, NHTSA recall 25E-084 covered 3,067 vehicles whose software could resume moving before a school bus had deactivated its flashing lights or retracted its stop arm. The recall report documents the defect and affected population.
Freeway construction zones
In June 2026, NHTSA recall 26E-035 covered 3,871 vehicles capable of driverless freeway operation. In some circumstances, those vehicles could enter and drive at speed into freeway construction zones. See the NHTSA recall report.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThese examples are a reminder that safety is not a single number. A low rate across hundreds of millions of miles and a dangerous defect affecting a particular scenario can both be true.
A child was struck near a school
NHTSA opened Preliminary Evaluation PE26001 after Waymo reported that one of its vehicles struck a child near a Santa Monica elementary school on January 23, 2026. According to NHTSA’s investigation resume, the child ran from behind a double-parked SUV toward the school and suffered minor injuries.
This case deserves attention because vulnerable-road-user protection is one of the most important claims in Waymo’s dashboard. Waymo reports 93% fewer injury-causing pedestrian crashes than its human benchmark, but an individual child-strike investigation shows why an aggregate rate cannot be treated as proof that the system will always detect and avoid a pedestrian emerging from behind an obstruction.
The investigation itself is not a final finding that Waymo caused the event through a defect or violation. It is evidence that the system’s most difficult edge cases remain relevant even when the overall pedestrian rate is substantially lower than the human comparison.
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Fatal crashes involving a Waymo require careful wording
A fatal collision involving a Waymo vehicle is not automatically a fatal collision caused by Waymo. At least one 2025 fatal collision in Tempe involved a motorcycle rear-ending a Waymo that was reportedly yielding to a pedestrian, after which another vehicle struck the motorcyclist. Local accounts from Arizona’s Family and The State Press described the Waymo as apparently not the initiating party.
That account should not be converted into a definitive legal finding without an authoritative investigation. The careful statement is that fatal crashes have involved Waymo vehicles, while available reporting may indicate that Waymo was not the initiating party in particular incidents. “No Waymo passenger died” and “Waymo has never been involved in a fatal collision” are entirely different claims.
Crash rates do not capture every operational safety problem
A robotaxi can create a dangerous or disruptive situation without colliding with another road user. Examples include:
- Stopping in a travel lane or an unsafe location.
- Blocking a fire truck, ambulance, police vehicle, or other emergency responder.
- Becoming stranded in construction, flooding, or an unusual road closure.
- Failing to respond appropriately to police hand signals or temporary traffic control.
- Making a cautious maneuver that causes unsafe delays or prompts other drivers to take risks.
- Failing a trip or requiring assistance without producing a recorded crash.
Waymo says its readiness process tracks measures such as impeded progress, improper stops, strandings, delays to other vehicles, and mission failures. Those metrics matter, but they are not the same as the headline serious-crash and injury-crash rates. A complete public safety evaluation should report both collision outcomes and these non-crash operational events.
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How strong is the evidence?
A useful way to judge the claim is to apply a consistent checklist:
| Question | What the evidence says |
|---|---|
| Is exposure normalized? | Yes. The central comparisons use vehicle miles and incidents per million miles rather than raw crash totals. |
| Are outcomes separated by severity? | Yes. The data distinguishes injury, serious injury or worse, airbag deployment, and vulnerable-road-user outcomes. |
| Are the locations matched? | Partly. Waymo adjusts for its operating geography; IIHS compares studied cities directly. Neither result applies everywhere. |
| Is involvement distinguished from fault? | Yes, but this distinction is often lost in headlines. Waymo’s main metric counts involvement regardless of fault. |
| Are reporting differences addressed? | Partly. Waymo applies an injury underreporting correction, while IIHS manually assessed police reportability. No correction is presented as fully reliable for every category. |
| Is uncertainty disclosed? | Waymo’s methodology and underlying materials use rate estimates and 95% confidence intervals. Rounded headline percentages should still be treated as estimates, especially for small city-level or rare-event categories. |
| Are software versions separated? | Not completely. The aggregate generally combines relevant rider-only miles from multiple releases and operating periods. |
| Is there independent corroboration? | Yes. IIHS found lower police-reportable crash involvement overall, though Austin’s small sample was 4% higher than its human comparison. |
| Are edge cases included? | They must be examined separately. Recalls, the child-strike investigation, operational failures, and individual fatal incidents are not erased by a low aggregate rate. |
| Does the evidence justify universal claims? | No. It supports a strong claim about the studied Waymo service domains, not every city, climate, road, system, or future software release. |
So, are Waymos actually much safer than human drivers?
In the current studied operating domains, the answer is probably yes. The result is supported by a large Waymo dataset and strengthened by an independent IIHS analysis using a different method. The consistent direction of the findings—fewer serious crashes, fewer injury crashes, fewer single-vehicle crashes, and fewer rear-end collisions—makes it difficult to dismiss the safety advantage as nothing more than publicity.
But the size and scope of that conclusion matter. The evidence does not establish that Waymo vehicles are 94% safer in every sense. It does not show that they never cause crashes. It does not show that they are ready for every climate, road type, or city. It does not show that other autonomous-driving companies have the same performance. And it does not make recalls or operational failures irrelevant.
The most accurate interpretation is:
Waymo’s driverless vehicles have accumulated enough real-world mileage to show a substantial, increasingly independently corroborated reduction in crash involvement and injury-crash rates compared with human drivers in the cities, roads, periods, and metrics studied. That is a significant safety achievement, but it is not the same as being crash-proof or universally validated.
That makes the original Futurism headline directionally right but rhetorically overstated. The data is impressive. “Almost comical” is still a headline flourish.
What the evidence does—and does not—prove
| Claim | Verdict |
|---|---|
| Waymo reports 94% fewer serious-injury-or-worse crash involvements. | Supported, for the specified benchmark, locations, periods, and rider-only miles. |
| Waymo crashes 94% less in every sense. | Not supported. The figure concerns a specific severity category, not all physical contacts. |
| Waymo has never caused a fatal crash. | Not established. Fatal collisions have involved Waymo vehicles, and legal fault requires authoritative determinations. |
| Most reported serious Waymo crashes were caused by humans. | Partly supported as case-review commentary. The independent review reached that judgment for many cases, but it was not an official fault adjudication. |
| Recalls disprove Waymo’s safety advantage. | Not supported. Recalls demonstrate specific defects and the need for safety management; they do not by themselves negate lower aggregate crash rates. |
| Waymo’s result applies to all autonomous vehicles. | False. The evidence is specific to the Waymo systems, vehicles, locations, periods, and operating domains studied. |
Frequently Asked Questions
Does a Waymo crash mean Waymo caused it?
No. Waymo’s main safety-impact metric counts crash involvement regardless of fault. A Waymo can be rear-ended or struck by another road user and still appear in the crash-involvement data. That does not settle legal responsibility, and it does not make every incident irrelevant to the vehicle’s operational safety.
Does remote assistance mean a human is secretly driving the robotaxi?
Waymo says remote assistance provides contextual information when the vehicle encounters an unusual situation; it is not described as a remote human continuously performing the driving task. The vehicle remains responsible for driving within its defined operating domain.
Are Waymos safe outside the cities in the studies?
The available evidence does not establish that. Waymo’s results are concentrated in specific service areas, primarily on surface streets, and under defined operating conditions. They should not automatically be generalized to snow, rural roads, all freeways, new cities, or future software releases.
Do Waymo’s recalls mean the vehicles are unsafe overall?
Recalls show that Waymo can have serious, scenario-specific defects and that ongoing safety management is necessary. They do not, by themselves, prove that the fleet’s overall crash rate is worse than human driving. Both facts can be true at once: the aggregate rate can be lower while particular edge cases require corrective software.
What is the strongest independent evidence about Waymo safety?
A July 2026 IIHS study of roughly 50 million Waymo driverless miles in Phoenix, San Francisco, Los Angeles, and Austin found 68% fewer police-reportable crash involvements per mile than human drivers overall. The result varied by city, however, and Austin’s small sample was 4% higher than its human comparison.
The Bottom Line
Bottom line: Waymo’s safety record is genuinely impressive, not merely a publicity stunt. The best current evidence supports substantially fewer crash involvements and injury crashes than human driving in Waymo’s studied operating domains. But the system remains fallible: recalls, unusual operational failures, a child-strike investigation, and fatal collisions involving Waymo vehicles all show why “safer than humans” should never be mistaken for “incapable of causing harm.”
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