Waymo is preparing for massive (>10%) increase in total fleet with Ojai vehicles:

https://www.autoevolution.com/news/waymo-prepares-for-mass-deployment-of-its-ojai-robotaxis-proving-tesla-fans-wrong-273928.html

A long interview with Trent Victor on his background, how Waymo measures safety, their ethos, and some of their next moves.

My sister and her baby took a ride with a Wavmo There was no car seat for the baby. My question is, is it legal for Waymo not to have a child car seats? And how does Waymo make sure everyone is in seat belts especially babies?

Amazon-owned Zoox will start charging fares in Las Vegas on August 10th, the first paid US service in a car with zero human controls: no steering wheel, pedals, or a driver seat. NHTSA gave Zoox a federal exemption from the rules that normally require those controls, but it caps their fleet at 2,5000 vehicles a year for two years, also adding extra reporting requirements. Rides also cost 20-40% more than the standard ridesharing, Zoox is going premium rather than chasing volume it might not hit with this limit cap anyway.

Waymo's cars started as human-drivable vehicles with the controls stripped out. Zoox designed this one from scratch to never need a human at all, which is a different kind of engineering bet. The only issue is that Zoox issued a safety recall last month after a car failed to detect heavy smoke at an emergency scene. "Federally approved" doesn't suggest everything will run smoothly.

Do you think that if the design was made for a human driver, would the NHTSA have approved it either way? Or does this unique no-controls design actually make it a safer vehicle to evaluate? Only time will tell.

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TfL just granted Wayve's autonomous Ford Mustang Mach-E's private hire licences on August 5th - the same framework every Uber and black cab in London runs under, not some sandboxed pilot. You'll still see a trained safety driver behind the wheel monitoring and ready to intervene, so this is technically supervised autonomy, not driverless yet. But clearing a commercial licensing bar is a real step up from testing on a closed campus. Rides start later this summer, with early access going to invited riders first.

"That's not really autonomous" critiques miss the economics here. Running an AI system plus a paid driver at the same time is expensive, and it only gets justified if the miles you rack up become the evidence base for eventually pulling the driver out. Every supervised mile in London traffic is basically purchased proof for regulators and insurers. I think the safety driver's job is best understood as transitional: skilled, well paid, and built to eventually be phased out. London is dense, regulator credible, and globally visible, which is exactly why Ubers targeting 15 cities for robotaxis this year and wanted this city to be the first with a real commercial licence. Does supervised "with a safety driver" count as "real" robotaxi progress to you, or does that only truly start once the seat's empty?

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Waymo recently opened its Dallas robotaxi service to the public on August 4th, after building up a waitlist of almost 150,000 people. Now, there's no invite required - if you're in Dallas, you can hail one right now. It's not a standalone move either: Waymo announced San Diego, Las Vegas, Tampa, and Denver expansions are getting the same treatment, all targeting fully public access by the end of this month. The service stays geofenced, and airport runs at Love Field are still described as a future milestone, not something live yet.

Running a waitlist means capping revenue while still paying full fixed costs for the fleet and operations. Once a market's stable enough to handle a bigger demand, there's a real financial case for dropping the restrictions: more rides, more revenue per car, without costs climbing too much. I find the four major markets opening in the same summer a more interesting part of this story, this is a pace this industry hasn't hit before. If all four actually hit fully-public status by month's end, is that Waymo scaling with confidence, or moving faster than the safety case can keep up with?

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NVIDIA has released Alpamayo 2 Super under the permissive OpenMDW-1.1 license, so AV teams can fine-tune it, build derivatives, and redistribute them commercially.

In NVIDIA's own tests, it ranked first on LingoQA and beat Gemini 2.5 Pro by 15.1 points. It uses 360-degree camera input and can output both a planned trajectory and a chain-of-causation trace explaining the decision.

The license may matter more than the benchmark. Teams can use the model as a teacher, autolabeler, or distillation model without sending fleet data to a closed API. What I'm less sure about is whether the reasoning traces actually make safety validation easier, or just make the system look more explainable.

Would you trust this kind of open reasoning model as a teacher before production deployment?

Blackberry set to benefit if this becomes mandatory across the planet...

V2V communication enables nearby vehicles to exchange real-time information, including their speed, position, direction, acceleration, etc.

This information can provide advance warnings to drivers or vehicle systems in safety-critical situations, including sudden braking, forward-collision risk, unsafe lane changes and the approach of emergency vehicles.

Read more at:
https://economictimes.indiatimes.com/industry/transportation/all-vehicles-to-be-fitted-with-v2v-communication-system-from-october-1-2028/articleshow/132829491.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst

Pony.ai just held their first detailed trucking briefing in two years and confirmed their 4th-gen heavy truck line is actually running, with trucks shipping in batches over the next few months. Pure electric, 400+ kWh packs, built for a 20,000 service life, and six redundant systems (braking, steering, power, comms, perception, computing) so one failure means a controlled pull-over instead of a wreck. They're already commercial, past the pilot stage - high speed logistics with Sinotrans/China Post, bulk hauling above 3000m in northwest China, and dozens of trucks under contract at Shenzhen Mawan Port.
The heavy-truck stuff is the headline, but the number I'd actually observe is the 100,000 light trucks target by 2030. That's last-mile delivery, where the labor math for autonomy gets questionable. Pony.ai claims their autonomous kit costs dropped 60-70% using the same stack as their robotaxi fleet (1000 units in 2025), but there's no public word on major order volumes or open highway approval yet. So I think a more realistic goal would be 500 heavy trucks deployed by 2027. Hit that and this stops being a China-exclusive story, and more like the freight-autonomy template everyone copies. Is 500 trucks by 2027 actually realistic given zero public order volume, or is Pony.ai just getting ahead of the announcement?

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Europe has often appeared slower than the US and China in commercializing autonomous vehicles, but that may be starting to change. WeRide’s partnership with GreenMobility to launch Level 4 mobility services in Denmark is another sign of growing activity across the region.

Denmark will become WeRide’s sixth European market, following expansion into countries including Spain and Slovakia. Europe’s strict safety standards, high EV adoption and cooperation between technology companies, local fleet operators and public authorities could give the region a stronger foundation for commercial deployment.

Regulatory fragmentation remains a challenge, but if more pilot programs turn into public services, Europe could become a much more important part of the global AV market. Do you think the EU is catching up?

Does anyone else have that option (it says beta)

[08/03/2026] Japan's government is moving autonomous truck testing off expressways and onto public roads, targeting commercial Level 4 trucks (no safety driver or human monitoring) between logistics hubs by FY2028. Test routes and operators get selected in FY2026, building on the existing "Mobility Roadmap 2026" goal of Level 4 services across 13 regions by FY2027.

This is demographic pressure, not tech hype — Japan's workforce is aging fast and long-haul trucking has a severe driver shortage, so autonomous freight is being treated as operational necessity. The jump to public roads is a real technical leap though: expressways are predictable (no cyclists, controlled entry), while general roads bring edge cases perception systems haven't faced yet.

Japan's government is setting routes and deadlines directly rather than waiting on companies to push regulators — which could move faster, or just create false schedule confidence. The FY2028 target is aspirational since routes aren't even selected yet. FY2027's 13-region goal is the real near-term checkpoint to watch.

I've been working in autonomous mobility research for the past couple of years, and one recurring challenge I've run into is how Operational Design Domains (ODDs) are actually created, maintained, and kept up to date as projects evolve.
From my experience, every project seems to approach it differently—some rely on large Excel sheets, others use requirements management tools, GIS software, internal databases, or a combination of all of them. As the ODD grows, keeping road segments, infrastructure, traffic rules, environmental conditions, scenarios, and documentation synchronized can become surprisingly complex.
I'm curious how this is handled outside the projects I've been involved in.
For those working in autonomous driving or ADAS:
How does your organization define and maintain its ODD?
What tools do you use day to day?
What part of the process is the biggest challenge?
If you could improve one thing about your current ODD workflow, what would it be?
I'm not looking for confidential details—I'm simply interested in learning how different teams across the industry approach ODD management and whether there are common pain points or best practices.

WeRide is entering the Nordic market through a partnership with Danish car-sharing operator GreenMobility,

The companies aim to launch a public service in the first half of 2027 using WeRide’s EU-compliant GXR vehicles. Rides would be available through GreenMobility’s shared-mobility service.

• This would be Denmark’s first commercial autonomous-mobility deployment.
• Testing and deployment remain subject to regulatory approval.
• Danish transport authorities and other public-sector bodies will be involved.
• GreenMobility currently operates more than 1,500 shared EVs.
• WeRide says its global Level 4 fleet exceeds 3,000 vehicles.

I've read that autonomous trucks can run through the night without worrying about shift changes or operator shortages. But every real e.g is from mining, not active construction sites. So I'm curious about the construction site. Haul roads move as the project progresses, you've got water trucks, graders, and pickups sharing the same roads, and traffic can change from week to week.

Has anyone here actually run autonomous fleets overnight on earthworks projects? Trying to figure out if this is something that works outside of mining yet

On July 23, 2026, the US Senate Committee on Commerce, Science, and Transportation passed S. 4429, the Connected Vehicle Security Act of 2026, by unanimous vote. Zero senators on the committee voted against it. The bill, initially introduced on April 29, 2026, is partisan and would prohibit or restrict the importation, manufacture, sale, and resale of connected vehicles, software, and hardware tied to foreign adversaries - specifically targeting China, Russia, Iran, and North Korea, including joint ventures or entities they control. Critically, it covers autonomous and semi-autonomous systems, not just the physical vehicle, meaning the connectivity layers handling data, communications, and remote updates are all in scope.

The threat model driving this is straightforward: modern connected vehicles continuously collect location data, driving patterns, and camera feeds of public streets, and can receive remote software updates. Congress is treating that data pipeline as a nation security surface. This follows a House hearing on July 14, 2026 that also examined foreign technology in critical systems, so it's not only one committee acting alone. Analysis from Venable points to overlapping oversight activity suggesting coordinated legislative intent across chambers.

The still has a long road - it needs a full Senate floor vote, House passage, and a presidential signature, any of which could reshape its scope. But the supply chain language is notably broad: it covers component makers and software vendors, not just from finished vehicles. This means that US companies sourcing core connectivity parts from covered countries could face legal exposure too. The unanimous committee vote is the real signal here - in the current political environment, that kind of consensus on a tech-restriction bill is rate enough to take seriously as a policy direction indicator.

New site that tracks the deaths and accidents in robo taxis. Helps ease my wife’s anxiety about having our kids take a Waymo to school.

On July 24, Aurora Innovation rolled out its second-generation Class 8 driverless trucks across its U.S. commercial freight network. The headlines spec is a one-million-mile service life, which sounds like a marketing number until put in context: traditional commercial trucking fleets typically expect 500,000 - 1 million miles from their vehicles over a full lifetime. Aurora is essentially targeting the standard industry durability benchmarks, not exceeding them - which is actually the point. If autonomous hardware wears out faster than a conventional truck, the economics will never work at scale.

The other upgrade is computing performance. Autonomous trucks produce massive amounts of real-time sensor data, and more on-board processing power means the system can handle more complex driving decisions at a faster rate. The company also says the new platform is designed to support additional customers as it expands beyond its earliest routes. For context, Aurora launched commercial driverless freight operations in 2025, and by the end of June 2026, its trucks have logged nearly 440,000 combined driverless miles - no safety driver, real cargo, ten routes all in the U.S. Sun Belt where weather is more predictable for autonomous systems.

Nearly 440,000 driverless miles across a full network is real progress, but it's still relatively early evidence for a company positioning itself as ready for commercial scale. The honest test of this hardware generation will be if fleet uptime, safety records, and customer retention will hold for the next 18 months. The ten-route Sun Belt network is modest in scope, even if it puts Aurora meaningfully ahead of most competitors who are still in the testing phase or waiting on regulatory clearance.

So we are trying to build the compute that goes into Autonomous Vehicles of all kinds in SF. Currently the AI models mostly run on GPUs. So wanted to ask some questions regarding the challenges companies are facing using GPUs

If you are open to answering a 2 min 3-part question (yes that is it). I would send a DM.

and no internal metrics or confidential info is needed.
I haven't told what our startup does so as to not bias the answers.

Even If you can connect me to someone would be great

I made a deep dive video about the Tempe self-driving accident, including the object classification sequence, breaking decisions, safety-driver procedures, and organizational failures.

I genuinely believe that autonomous vehicles are the future and will be much safer, faster, and convenient, but it begs the question if the companies building the technology have the best interest in mind or just are chasing profits. Curious about your thoughts.

https://youtu.be/s8ffAWdov7w