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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteSome Waymo robotaxis stopped or remained stationary at San Francisco intersections during the December 20, 2025 power outage—not because they ran out of battery or lost onboard computing power, but because a citywide failure of traffic signals created an unusual surge in requests for remote confirmation.
Some Waymo robotaxis stopped or remained stationary at San Francisco intersections during the December 20, 2025 power outage—not because they ran out of battery or lost onboard computing power, but because a citywide failure of traffic signals created an unusual surge in requests for remote confirmation.
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Waymo’s vehicles are designed to treat a dark traffic signal as a four-way stop. That behavior allowed the fleet to navigate thousands of signal outages. But as the blackout spread, many intersections became harder to interpret, traffic conditions deteriorated, and requests to Waymo’s Remote Assistance team rose far beyond normal levels. Vehicles waiting for confirmation sometimes stayed put, adding to congestion that was already being caused by the blackout itself.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchThe incident was therefore a failure of an entire operating system—vehicles, traffic infrastructure, remote support, emergency communications and city traffic management—rather than a simple case of autonomous cars being unable to “see” a dark traffic light.
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The blackout turned ordinary intersections into an autonomy stress test
The disruption began on December 20, 2025, after an arc-flash event and subsequent fire at PG&E’s Mission Substation near 8th and Mission Street. PG&E said the sustained outage affected more than 120,000 customers at its peak. Its initial public statement identified the substation fire but said the root cause had not yet been determined at that stage.
The outage affected nearly one-third of San Francisco. With power unavailable, many traffic signals went dark, leaving drivers, transit operators, pedestrians and autonomous vehicles to negotiate intersections without their normal control system. The San Francisco Municipal Transportation Agency described some all-way-stop situations as confusing or hazardous.
This was not a single failed intersection. It was a city-scale infrastructure disruption. San Francisco maintains more than 1,200 traffic signals and associated communications and field hardware, so a widespread power failure removed a major layer of organization from the road network at once.
Waymo knew dark signals should be four-way stops—but still got stuck
Waymo says its Driver is designed to treat a traffic signal that is not operating as a four-way stop. In principle, that gives the vehicle a defined fallback rule: approach cautiously, determine the right of way, and proceed when it is safe.
That rule does not make every dark intersection straightforward. A normal four-way stop assumes that the other road users understand and follow the same basic procedure. During the blackout, however, streets were unusually congested, signals were failing across a large area, law-enforcement officers were directing traffic at some locations, and drivers were encountering conditions they did not expect. Vehicles also had to account for pedestrians, emergency vehicles and other road users whose behavior could be difficult to predict.
When Waymo’s onboard system needed additional verification, it could ask the company’s Remote Assistance team for a confirmation check. That escalation path was useful during smaller or more localized outages. The December event exposed what happened when a normally manageable source of uncertainty appeared at a large number of intersections at the same time.
According to the available regulatory records, Waymo vehicles initially did not experience notable problems navigating dark signals. Around 5 p.m., however, confirmation requests began exceeding typical volume by a marked amount. Some vehicles waiting for an answer remained stationary at darkened intersections.
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Waymo said its fleet traversed more than 7,000 dark signals during the outage. That is the company’s own operational figure, not an independently audited safety result, but it does show why the incident cannot accurately be summarized as every Waymo being unable to drive without working signals.
The response system became part of the traffic problem
A California Public Utilities Commission filing said 829 Waymo vehicles operated for at least some period inside the affected geographic area during the peak outage period, defined as approximately noon to 11 p.m. on December 20.
That number matters because a remote-assistance system can behave very differently under fleet-scale stress than it does during an isolated event. A single vehicle asking for help is one type of operational problem. Hundreds of vehicles encountering dark signals, unusual traffic-control arrangements and blocked or confusing intersections in the same city can produce a synchronized demand spike.
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As requests accumulated, some vehicles remained in place while waiting for confirmation. A stationary car at one intersection may be a cautious response. A group of stationary cars distributed through a disrupted road network can become another obstruction, particularly when streets are already clogged and emergency routes need to remain open.
The CPUC record places Waymo’s service suspension at approximately 5:55 p.m. As conditions worsened, the company said it directed vehicles to pull over and park appropriately. It planned to return vehicles to depots in waves so they would not further obstruct traffic or emergency vehicles.
That response also illustrates the trade-off facing an autonomous fleet during a crisis. Continuing service may preserve mobility for some passengers, but it can increase the number of vehicles exposed to uncertain intersections and overload support staff. Stopping service reduces new demand, yet withdrawing hundreds of vehicles requires safe places to pull over, a coordinated routing plan and a way to avoid creating additional blockages.
Emergency communications were under unusual pressure
The outage also tested the channels that connect an autonomous fleet with public-safety agencies. A CPUC filing says San Francisco emergency-management dispatchers placed 31 calls to Waymo’s first-responder hotline between approximately 3 p.m. and 8 p.m. Those calls totaled two hours and 36 minutes, with a large majority of that time reportedly spent on hold.
At the same time, the San Francisco Fire Department received 801 calls during the 24-hour period from 8 a.m. on December 20 to 8 a.m. the next day. Its daily average was reported as 507 calls, making the outage-period total a 58% increase.
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Those figures do not prove that Waymo caused the city’s emergency-response burden. The blackout itself affected a huge area, disrupted traffic signals and created a broader public-safety incident. They do show why a first-responder channel must be designed for peak conditions rather than ordinary operations. A hotline that works adequately on a typical day may become a serious operational weakness when city agencies and a large autonomous fleet need to communicate at the same time.
Waymo added to congestion, but did not create the entire crisis
It would be inaccurate to say that Waymo alone caused San Francisco’s traffic collapse. The city was dealing with a major utility outage, dark signals, confused road users, emergency activity and traffic-control interventions. Municipal records and Waymo’s own account describe a broad disruption that affected the transportation system as a whole.
The narrower and better-supported conclusion is that some stationary Waymos contributed to congestion during an already severe citywide event. The vehicles’ cautious behavior was part of the chain of events, but it interacted with the scale of the blackout and the capacity of the remote-assistance system.
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This distinction also avoids two opposite mistakes. It is wrong to claim that the cars were unaffected simply because they could detect the road and had a dark-signal policy. It is equally wrong to claim that the entire fleet failed or that the robotaxis were the primary cause of every traffic problem in San Francisco.
San Francisco improvised around disabled signals
The city’s response involved more than monitoring autonomous vehicles. San Francisco used generators to “back feed” selected traffic signals, deployed traffic-control personnel at disrupted intersections and adjusted transit operations. SFMTA staff worked through the weekend to maintain mobility and safety while signals remained out.
These measures highlight an important difference between an individual vehicle’s fallback behavior and a city’s ability to restore orderly movement. A robotaxi can treat one dark signal as a four-way stop, but that does not replace the network-level coordination provided by functioning signals, traffic officers, transit priority systems and emergency-routing procedures.
It also explains why infrastructure resilience is directly relevant to autonomous driving. The car may be capable of operating without one piece of infrastructure; the transportation service may still struggle when that infrastructure fails across a large geographic area.
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Waymo said it was rolling out fleet-wide updates to give vehicles more specific information about regional power outages and help them navigate dark intersections more decisively. The company also announced improvements to emergency-preparedness and response protocols and said it would expand engagement with first responders.
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The proposed change addresses the central weakness exposed in December: a vehicle should not treat every dark signal as an isolated mystery when the fleet knows that a regional outage is in progress. Shared outage context could help the Driver distinguish between a single malfunction and a widespread infrastructure event, reducing unnecessary hesitation and allowing the company to manage service withdrawal earlier.
Waymo characterized its previous confirmation strategy as useful for smaller outages but insufficiently scalable for an event affecting a large portion of a major city. That is a system-design lesson rather than an admission that remote assistance is inherently unsafe. Remote support can help resolve unusual situations, but its capacity, escalation rules and fallback behavior must be planned for correlated failures affecting many vehicles simultaneously.
Waymo also said it had trained more than 25,000 first responders in the United States and elsewhere on interacting with its vehicles. That number is a Waymo-reported figure. Training is only one part of the solution: agencies also need dependable contact routes, clear procedures for directing or securing vehicles, and response arrangements that remain usable when normal communications are busy.
A smaller July 2026 outage tested the response
The issue reappeared as an operational consideration on July 18, 2026, when another PG&E outage affected traffic signals in parts of San Francisco’s Richmond District and Presidio.
Waymo temporarily paused or adjusted service for approximately one hour while it assessed the outage and coordinated with local officials, then resumed service. The available public reporting describes a short precautionary service adjustment, not a repeat of the December event’s citywide gridlock and prolonged vehicle stoppages.
That comparison should be treated cautiously. The July public record contains fewer technical details than the CPUC documentation for December. The incident does not prove that Waymo’s announced December changes failed, nor does it prove that every underlying risk was eliminated. It does show that power-related signal failures remained a live operating concern for Waymo in San Francisco in 2026—and that a temporary service pause could be used while the company assessed conditions.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the incident says about robotaxi safety
The central lesson is not simply that autonomous vehicles need to recognize dark traffic lights. Waymo says its vehicles already had a fallback behavior and navigated more than 7,000 dark signals during the December outage. The deeper issue was how the complete service behaved when several dependencies failed together.
- Onboard perception and planning: The vehicle must identify the intersection, road users, lane layout and available right of way.
- Traffic infrastructure: Signals, communications equipment and related hardware provide the coordination that makes urban movement predictable.
- Remote assistance: Human support must have enough capacity to handle an abnormal, correlated spike in requests.
- Service-suspension logic: The fleet needs a fast way to reduce exposure and avoid leaving vehicles in obstructive locations.
- Parking and retrieval: Vehicles must be withdrawn without blocking lanes, transit routes or emergency access.
- Emergency coordination: Fire, police and city dispatchers need reliable channels and clear procedures for interacting with the fleet.
- Utility and municipal response: Power restoration, signal back-up, traffic control and transit adjustments determine how quickly the surrounding road network can recover.
In other words, robotaxi resilience is a system property. A vehicle can be technically capable of handling a dark signal while the service as a whole is not yet resilient to hundreds of dark signals appearing at once.
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Three separate accountability questions
The blackout should be examined across three accountability layers rather than reduced to a single question of whether Waymo’s artificial intelligence “failed.”
- Utility reliability: What caused the Mission Substation arc-flash event and fire, and how effectively was power restored? PG&E’s direct-cause investigation addresses this layer.
- Municipal traffic management: How did San Francisco handle dark signals, emergency routing, traffic officers and transit continuity? SFMTA’s response addresses this layer.
- Waymo’s operational design: How did the Driver, Remote Assistance, service-suspension logic and first-responder channels perform under fleet-scale stress? The CPUC filings and Waymo’s own statements address this layer.
All three deserve scrutiny. But they should not be collapsed into the claim that one company, one algorithm or one failed piece of equipment caused the entire disruption.
The larger lesson is infrastructure, not just AI
Autonomous driving is often evaluated as though the vehicle is an independent computer navigating an otherwise stable world. Urban deployment is less self-contained. Robotaxis depend on the electrical grid, traffic-signal networks, road markings, curb access, communications, emergency agencies, remote operators and municipal rules.
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The December outage exposed a particularly difficult type of failure: not an isolated sensor problem, but a correlated infrastructure event that made many vehicles cautious at the same time. The response must therefore include more than better perception models. Fleets need regional outage awareness, capacity planning for remote assistance, resilient emergency hotlines, rapid service-withdrawal procedures and regular coordination exercises with cities and first responders.
That is why the Waymo episode matters beyond one company or one San Francisco blackout. It is a practical test of whether autonomous transportation can remain predictable when the infrastructure that organizes human traffic suddenly disappears. The answer will depend as much on utilities, cities and operational procedures as on the software inside the car.Bottom line: The December 2025 outage did not show that Waymo robotaxis simply lost power or could not recognize a dark traffic light. It showed that a cautious fallback policy, a surge in remote-assistance requests and widespread traffic-signal failure can combine into a city-scale bottleneck. Some Waymos added to congestion, but the broader crisis was a failure of interconnected urban infrastructure and emergency coordination. Waymo’s later software and response changes—and its shorter July 2026 service pause—suggest that outage resilience remains an active engineering and regulatory issue.
Frequently Asked Questions
Did the Waymo cars lose power?},{
No. The available records do not say that the robotaxis ran out of battery or lost onboard computing power. They describe vehicles waiting for remote confirmation after encountering unusually difficult dark-signal situations during the outage.
Why did some Waymo vehicles stop at intersections?
Waymo says its Driver treats a dark traffic signal as a four-way stop. That fallback worked at many intersections, but a large number of simultaneous signal failures increased uncertainty and remote-assistance demand. Some vehicles remained stationary while waiting for confirmation.
Did Waymo cause San Francisco’s entire traffic jam?
No. The blackout affected nearly one-third of San Francisco, disrupted many traffic signals and created widespread congestion and emergency-management challenges. Some stationary Waymos contributed to that congestion, but the evidence does not support blaming the robotaxis for the entire citywide crisis.
Did Waymo have the same problem again in July 2026?
On July 18, 2026, an outage affected signals in parts of the Richmond District and Presidio. Waymo paused or adjusted service for about an hour while it assessed conditions and coordinated with local officials, then resumed service. The available reporting does not establish that this was the same failure mode as December or that the December fixes failed.
The Bottom Line
Bottom line: The December 2025 outage did not show that Waymo robotaxis simply lost power or could not recognize a dark traffic light. It showed that a cautious fallback policy, a surge in remote-assistance requests and widespread traffic-signal failure can combine into a city-scale bottleneck. Some Waymos added to congestion, but the broader crisis was a failure of interconnected urban infrastructure and emergency coordination.
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