The Driverless Digest Podcast

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

Join panelists at the Urban Autonomy Summit in Austin as they discuss the infrastructure, operations, and partnerships needed to scale autonomous vehicles. This panel featured Yulia Shveyko (Head of Public Affairs, Avride), Ben Seidl (CEO & Co-Founder, Autolane), Nick Allen (Head of AV / Mobility, TaskUs), and Daniel Severin (Head of Global Mobility Insurance, The Ride Platform), and was moderated by Julia Pickar (Transportation & Technology Journalist, NPR / Marketplace).

The conversation explores why Texas has become a hub for AV deployment and what it will take to support larger fleets, from charging and depot capacity to remote assistance and rider support. Panelists discuss how operators handle unexpected road conditions, the business opportunities emerging in autonomous delivery and fleet services, and how automation can bring operating costs down. They also examine the regulations shaping expansion, common misconceptions about driverless technology, and what will signal that autonomous vehicles have truly gone mainstream.

Chapters

* (00:00) Introduction

* (01:38) Why Texas Is a Hub for Autonomous Vehicles

* (04:13) The Infrastructure Needed to Scale AVs

* (06:09) Handling Road Closures and Unexpected Situations

* (09:23) Learning From AV Edge Cases

* (11:26) Business Opportunities in Autonomous Delivery and Fleet Operations

* (15:04) Cutting Costs Through Automation

* (16:09) How Regulation Helps or Hinders AV Growth

* (21:28) The Biggest Misconceptions About Autonomous Vehicles

* (26:01) When Will Autonomous Vehicles Become Mainstream?

- Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Ethan McKanna, an autonomous vehicle power user, industry observer, and the creator of Robotaxi Tracker. Ethan returns to the podcast to share what inspired him to build the platform and how he gathers data to track autonomous vehicle deployments.

We discuss the metrics Robotaxi Tracker covers, how Tesla’s fleet numbers compare with Waymo’s, and the methods Ethan uses to identify and count vehicles. Ethan also explains some of the common misinterpretations of the data and the steps he takes to help people understand what the numbers actually tell us.

We also explore how companies, cities, and the press interact with Robotaxi Tracker, and how the platform could help cities better understand autonomous vehicle activity on their streets. Ethan shares how much time goes into maintaining the project, his thinking around monetization, and what could make the data more accurate.

Finally, we discuss potential new features, why utilization is such an anticipated metric, and what Ethan’s data reveals about other operators, including Zoox and Avride.

Chapters

* (00:00) Introduction to Ethan McKanna

* (01:39) What inspired Ethan to build Robotaxi Tracker

* (03:29) The main use cases for Robotaxi Tracker and its goal

* (04:45) What metrics does Robotaxi Tracker cover?

* (07:25) How Robotaxi Tracker focuses on objective data points for AV deployments

* (08:50) Overview of the Robotaxi Tracker user interface/experience

* (09:40) Tesla’s Robotaxi/Cybercab fleet numbers and how they were gathered

* (15:07) Tesla vs. Waymo fleet numbers

* (17:37) What is the most popular/cited data from Robotaxi Tracker?

* (18:27) What data should we watch out for?

* (20:30) What do people get wrong about the AV data on Robotaxi Tracker?

* (22:20) Steps Ethan takes to curb misinterpretation of the AV data on Robotaxi Tracker

* (23:35) How Ethan uses cameras along with other methods to identify/analyze AV fleet numbers

* (24:30) How Ethan interacts with the major AV stakeholders, including companies, cities, and the press

* (25:45) How Robotaxi Tracker could help cities understand AV deployments

* (27:02) How much time Ethan spends on Robotaxi Tracker

* (27:35) Are there any downsides for AV operators to having their data published on Robotaxi Tracker?

* (28:29) How Ethan is thinking about the business aspect of Robotaxi Tracker and monetization

* (29:35) What could make Robotaxi Tracker more accurate?

* (31:34) What new features Ethan might add to Robotaxi Tracker

* (33:00) Why utilization could be the most anticipated feature on Robotaxi Tracker

* (35:06) What his data reveals about AV operators like Zoox and Avride

* (38:53) Conclusion and final thoughts

Notes/Links:

* You can find Ethan on LinkedIn and Twitter/X.

* Check out Robotaxi Tracker (link).

* Ethan’s earlier episode on the podcast (link).

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

This week’s edition is brought to you by Terawatt – purpose-built charging for autonomous vehicle fleets.

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Nat Beuse, Chief Safety Officer at Aurora. Nat shares his background in vehicle safety across the public and private sectors, the lessons he’s learned along the way, and how those experiences shape his approach to autonomous trucking.

We dive into Aurora’s fully driverless operations and the steps the company took to close its safety case. Nat explains the operating conditions its trucks are designed to handle, how Aurora plans for edge cases, and how it tracks uptime, reliability, and other metrics. We also discuss the company’s latest milestones and what changes as its fleet scales.

The conversation explores public perception, how autonomous vehicle companies balance competition with collaboration on safety, and Aurora’s approach to sharing knowledge and safety information with the public. Nat also discusses the benefits of being a publicly listed company and the importance of transparency as driverless operations expand.

Finally, we look at the regulatory landscape for autonomous trucking and the hurdles to establishing a federal framework.

Chapters

* (00:00) Introduction to Nat Beuse

* (02:07) Nat’s background in vehicle safety, across the public and private sectors

* (05:57) Nat’s safety philosophy and what he’s learned from working on vehicle safety over the years

* (09:55) Aurora’s operations and the safety case for its driverless operations

* (12:50) Facts and figures from Aurora’s fully driverless operations

* (15:55) The steps Aurora took to close its safety case

* (19:20) Aurora’s operational design domain (ODD) and the various use cases for its customers

* (22:12) The operational limits of Aurora’s driverless trucks and how they plan for edge cases

* (24:05) How Aurora tracks uptime, reliability, and other metrics

* (25:50) Aurora’s latest milestones and what changes as its fleet scales

* (28:00) The importance of public perception and how it changes as the business scales

* (30:15) How AV companies collaborate on safety and the role of competition in the space

* (33:27) How Aurora contributes to knowledge sharing across the AV industry

* (34:55) The benefits of being publicly listed and sharing Aurora’s safety case with the public

* (37:30) The current regulatory landscape for autonomous trucking

* (41:09) The hurdles to establishing a federal regulatory framework for autonomous trucking

* (43:19) Conclusion and final thoughts

Designing Charging Hubs for Autonomous Fleets

We are excited to partner with Terawatt this week, one of the leading charging infrastructure providers. To learn more about Terawatt’s nationwide real estate portfolio and track record of cutting cost per mile for AV fleet operators, reach out to Peter Cohen at [email protected]

Notes/Links:

* You can find Nat Beuse on LinkedIn.

* Aurora’s website (link).

* Dave Ferguson of Nuro’s interview with Aurora CEO Chris Urmson, mentioned at the 05:43 timestamp (link).

* Aurora’s Safety Case Framework, mentioned at the 10:41 timestamp (link).

* The independent assessment of Aurora’s safety case, mentioned at the 18:00 timestamp (link).

* Aurora’s voluntary safety self-assessment, mentioned at the 36:24 timestamp (link).

* Feel free to leave us a review on our Apple Podcasts page, then send us a screenshot in an email reply to score some TDD swag!

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Armir Harris, founder and CEO of CharterUP. Armir breaks down the company’s group transportation business, the customers it serves, and why it has built its platform without owning any buses. Armir will also be speaking at our upcoming Austin Urban Autonomy Summit on October 14th, on the panel “From Long Haul to Last Mile: AVs Take on New Form Factors.” Apply to attend here so you don’t miss out!

We explore how CharterUP is preparing for autonomy, including its partnership with HOLON and plans to bring autonomous shuttles into its network. Armir shares where he sees the biggest opportunities for autonomy to impact the business, the limitations of automating mass transit, and what autonomous group transportation could offer customers.

We also discuss how autonomous shuttles could fit into the broader transportation network alongside robotaxis and human-driven vehicles. The conversation covers the potential safety benefits of autonomous buses, the role people will continue to play in deploying and operating these services, and how CharterUP is approaching that transition.

Finally, Armir discusses CharterUP’s first autonomous vehicle deployment, future deployment timelines, and what it will take for autonomous shuttles to become a mainstream transportation option in the coming years.

Chapters

* (00:00) Introduction to Armir Harris

* (01:08) What is CharterUP and what does it do?

* (03:01) CharterUP’s footprint, offerings, and customers

* (05:07) Why CharterUP doesn’t own any buses and the advantages of its business model

* (06:00) Armir’s thoughts on the current autonomy landscape and how it could impact CharterUP’s business

* (08:18) How CharterUP’s business is evolving to embrace autonomy

* (09:40) Where Armir sees the biggest impact of autonomy on CharterUP’s business

* (11:02) The limitations of automating mass transit

* (12:30) CharterUP’s partnership with HOLON and their plans to advance autonomous group transport

* (15:43) Who are the leaders in the autonomous group transportation space?

* (17:28) What is CharterUP’s most compelling value proposition for its customers?

* (19:38) Would autonomous buses be safer than human driven ones?

* (20:25) The role of humans in deploying autonomous group transportation and how CharterUP is looking at the transition

* (23:30) Autonomous group transportation vs. robotaxis

* (24:20) How autonomous shuttles fit into the transportation network alongside robotaxis and human-driven vehicles

* (25:19) CharterUP’s first AV deployment and future deployment timelines

* (26:04) Armir’s outlook for autonomous shuttles and what it’ll take for them to go mainstream in the coming years

* (27:50) Conclusion and final thoughts

Notes/Links:

* You can find Armir Harris on LinkedIn/X.

* CharterUP’s website (link).

* The CharterUP-HOLON partnership mentioned at the 12:30 timestamp (link).

* You can find some of our previous coverage on shared autonomous transport:

* The Real Impact of Autonomy Will Come From Buses (link).

* Redefining Travel Time with PIX Moving’s Autonomous Shuttles (link).

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, The Driverless Digest Editor Ben Hubbard speaks with Augustin Friedel, an expert in software-defined vehicles (SDV) and AI-enabled mobility. Augustin shares his background in the industry and examines Europe’s autonomous vehicle landscape, including how it compares with the rest of the world and what it will take to move from pilots to commercial deployments.

They take a closer look at the Uber-Verne-Pony.ai pilot in Zagreb, Uber’s role in accelerating autonomous vehicle deployment, and Bolt’s position in the European robotaxi market. Augustin also discusses whether Europe’s autonomous vehicle demonstrations can become scalable businesses and the concerns surrounding partnerships with Chinese developers.

Finally, they explore the infrastructure needed to support robotaxi fleets, including the challenges of finding suitable sites in cities like London. They discuss where the real value lies in the robotaxi business, from technology and fleet operations to customer demand, before closing with Augustin’s outlook for Europe’s progress over the next year.

Chapters

* (00:00) Introduction to Augustin Friedel

* (01:32) Augustin’s background in the mobility/autonomy space

* (04:51) The autonomy landscape in Europe and how it compares to the rest of the world

* (06:46) The Uber-Verne-Pony.ai AV pilot in Zagreb and the state of AV pilots/deployments in Europe

* (09:51) What’s needed to scale AV deployments in Europe

* (11:20) Can European AV demos become scalable businesses?

* (14:02) Uber’s role in accelerating AV deployment in Europe

* (16:00) Bolt’s position in the European robotaxi landscape

* (17:50) Is Europe at risk of becoming a market for boring AV technology?

* (20:41) Are there concerns about partnering with Chinese AV companies?

* (21:59) The state of the European AV infrastructure landscape and how it could evolve

* (26:40) Realities and challenges of siting AV infrastructure in European cities like London

* (30:54) Where the real value lies in the robotaxi business: fleet operations, demand, tech, etc.

* (35:00) What progress can Europe make over the next year?

* (36:38) Conclusions and final thoughts

Notes/Links:

* You can find Augustin on Linkedin.

* Check out our previous guest podcast with Augustin and Daniel (link).

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Raquel Urtasun, Founder and CEO of Waabi. Raquel shares how she got into the self-driving field, why she left Uber to build Waabi, and what she believes sets the company apart. We also discuss Waabi’s current operations and footprint, its philosophy, and the three pillars Raquel sees as essential to commercial scale.

Raquel explains how much human supervision Waabi’s trucks require today and the final milestone before the company can operate without a driver. We dig into the metrics Waabi uses to measure progress, its hardware approach, and its partnership with Volvo Autonomous Solutions. She also discusses Waabi’s other truck manufacturer partnerships and how quickly the Waabi Driver can transfer between vehicle platforms.

The conversation then turns to how Waabi tests its claims about zero-shot transfer across truck platforms and why Raquel chose trucking as the company’s starting point. We compare trucking with other autonomous vehicle markets and discuss Waabi’s fundraising and its partnership with Uber to deploy robotaxis. Finally, Raquel shares her perspective on what it will take to bring autonomy to more vehicles at scale.

Chapters

* (00:00) Introduction to Raquel Urtasun

* (01:50) Raquel’s background and how she got into the self-driving field

* (04:35) Why Raquel Urtasun left Uber to build Waabi

* (07:20) How Waabi stands out from its competitors

* (09:20) Waabi’s current operations, footprint, and philosophy

* (11:30) Waabi’s three pillars for commercial scalability

* (16:07) What level of human supervision is involved in Waabi’s current product?

* (16:30) Waabi’s final milestone before full driverless operations

* (20:30) What drives Waabi’s scalability, and which KPIs does it track?

* (22:40) Waabi’s hardware and partnership with Volvo Autonomous Solutions

* (24:45) Waabi’s other OEM partnerships

* (25:35) How quickly the Waabi Driver transfers between vehicle platforms

* (28:30) How Waabi scientifically tests zero-shot transfer across OEM truck platforms

* (30:45) How Raquel ranks different autonomy verticals and why Waabi started with trucking

* (36:50) Waabi’s fundraising and their partnership with Uber to deploy robotaxis

* (40:45) Conclusion and final thoughts

Notes/Links:

* You can find Raquel Urtasun on LinkedIn/X.

* Waabi’s partnership with Volvo Autonomous Solutions, mentioned at the 22:40 timestamp (link).

* Waabi’s announcement of the Waabi Driver’s zero-shot transfer between truck platforms, mentioned at the 25:18 timestamp (link).

* Waabi’s latest fundraising and partnership with Uber, mentioned at the 36:48 timestamp (link).

* Waabi’s website (link).

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Thanks to Jonah Bliss for originally covering this on The Curbivore - Let Them Linger? The Surprising Case for Robotaxis at the Curb

In a new study, Associate Professor Michael Hyland at UC Irvine explains why giving robotaxis somewhere to wait between rides could be crucial to avoiding unnecessary miles on city streets.

Where should a robotaxi go after dropping off a passenger?

It could wait at the curb, head back to a depot or it could simply keep moving.

A new study from researchers at UC Irvine and UC Berkeley examines what happens when shared autonomous vehicles are prevented from resting (otherwise known as staging) at the curb in San Francisco. The researchers simulated a fleet of 1,700 robotaxis serving 68,000 daily trips. In the no-staging scenario, the fleet traveled 564,650 kilometers per day. Allowing the vehicles to stage at the curb reduced daily vehicle miles traveled (VMT) by nearly 60%.

Michael Hyland, Associate Professor of Civil and Environmental Engineering at UC Irvine and one of the researchers behind the study, spoke to The Driverless Digest Editor Ben Hubbard about why curb access matters for robotaxis, how cities should manage valuable curb space, and what the rise of personally owned driverless vehicles could mean for congestion.

The Driverless Digest: Tell us about your role?

Michael Hyland: My research is broadly on modeling and analyzing transportation systems. I tend to focus on innovations in the transportation space, such as driverless vehicles, both in terms of shared fleets and personally owned, but also technologies like e-scooters, e-bikes, ride-hailing and micro-transit. My work involves how to operate these systems efficiently, how to design them effectively, and then I also try to understand their impact on people living in cities.

You’ve recently conducted a pretty comprehensive study on managing curb usage. Can you explain the experiment and what you set out to understand?

The idea was to test the impact of banning shared automated vehicles from using the curb. So this is not when they pick up and drop off passengers, but for what we call staging or parking between one drop-off and the next pickup. Essentially, the time when the vehicle doesn’t have anything to do.

The main result, of course, is that it has pretty big implications on what these vehicles do with their time. When they can’t stage, they just circle around the transportation network. In this case, they dramatically increased vehicle miles traveled on the roadway network in San Francisco. We don’t model congestion in our study, but the implications for congestion, I think, are somewhat obvious directionally. It would make congestion worse, most likely in some of the most congested parts in San Francisco.

We ran some other scenarios related to weekends versus weekdays, preventing vehicles from staging at night versus only during the day. Most of the results were pretty similar. If you’re strategic with where you ban the robotaxis from using the curb, the size of the VMT impact is much smaller, but there still is an adverse impact.

Plenty of people have probably wondered where an AV goes after it has dropped off a passenger. Do they just drive around in circles? Do they wait? Could you explain how this study came about because I can imagine this is going to become a really important topic when AVs take off.

Yeah, that’s right. As there are more fleets, the impact will be much larger. The study actually came from Waymo reaching out to us here at UC Irvine via Susan Shaheen’s group at UC Berkeley. They knew we did modeling and they asked us to interview stakeholders in cities to understand how they’re thinking about regulating the curb and using the curb for not just robotaxis but also Uber and Lyft-type vehicles, and micromobility too.

They came to us and said, “Hey, we think it’s mutually beneficial for us at Waymo and for cities for our vehicles to be able to use the curb when we’re not serving passengers,” as opposed to just driving around or even going a long distance back to an off-street parking lot. We co-designed the experiments. We made the final choices, of course. That’s the backstory of how the study came to be.

So is it entirely independent? When a company like Waymo approaches a university to produce a study, there’s always a feeling that the results might be tailored in their favor.

I can see that’s the impression. The main thing Waymo was pushing back on when we were writing up the report was that they said: “Well, we didn’t give you any data, so don’t make it seem like we did give you any data.” All this data is synthetic. We got the parking data from INRIX. We got the ride-hailing trip data from a company called Replica. Waymo really didn’t give us any data, which was fine with us. They gave us order-of-magnitude information about their fleet size, which is publicly available.

As far as the results, I mean I hate to undercut our study, but the directional impact was kind of obvious going into the study. We knew that by banning these vehicles from using the curb, it was going to increase VMT. It was really the magnitude that was the interesting part. Was it going to be a 10% increase? 30%? We found a pretty large number, which was a 60% increase in total vehicle miles traveled with this policy. And that came directly from the results. We didn’t rerun any scenarios or rerun the experiments with Waymo’s input.

Where do all those extra miles come from?

There are all these peaks and valleys throughout the day in terms of the demand for robotaxis. Everyone knows when the big peaks are for regular travel, right? So the morning peak, and then you have the afternoon peak. But for a service like Uber, Lyft or Waymo, there’s even little peaks and valleys that occur throughout the day, and spatially these occur throughout different parts of the region.

But when you have these vehicles out on the road and you get a little bit of a dip in demand, there’s nowhere for them to go. They’re not serving passengers, so they need to find somewhere to go. And if you don’t allow them to use the curb, what the software we use does is just gives them short “fake” trips to take throughout the network, circling around where they expect the future demand to be. And that, as the results suggest, leads to a lot of cumulative extra miles traveled in the network.

Some observers might believe these vehicles would just go back to a depot. Did you measure that?

Unfortunately, we didn’t create scenarios around the vehicles going back to the depot. I wish we could have but we ran out of budget.

Given that there are relatively few Waymo depots across the entire 49-square-mile San Francisco area, I suspect this would reduce VMT somewhat, but probably not by much. I’m not sure exactly how many depots Waymo has, but let’s say somewhere between two and five. Whenever a vehicle became empty, it would likely have to travel a fairly long distance to reach a depot, perhaps a mile and a half on average. It would then have to travel another mile and a half or so to pick up customers once a new request came in. So I think there’d be a pretty negative impact if the vehicles were always returning to the depot as well. Maybe you could bring that 60% number down to like 40-45%.

To reduce the VMT, you’d need to have depots all over the city then?

Yeah, I don’t think they [Waymo] are really into real estate development. They could partner with other companies, though. One thing we learned throughout the study is that the price of off-street parking is clearly time-dependent. In some parts of the city, such as commercial districts, parking might be very cheap to access at night but very expensive during the day. In residential areas, it’s usually expensive no matter what, and there are rarely large enough areas for a depot to be set up.

Acquiring land is also expensive. I imagine they’re trying to minimize the amount of land they need to acquire and be strategic about where they park their vehicles. They’d have to consider both the location and whether they’d have to pay for parking there.

Were there any other major findings?

The other major finding, which Waymo liked a lot, was related to a metric we used called curb productivity.

We measure curb productivity as the number of passengers who move between the transportation system and their destination per unit of time a robotaxi occupies the curb, including time spent staging and picking up or dropping off travelers.

We found that robotaxis were about eight to ten times more productive than personal vehicles in terms of how they use the curb. A personal vehicle spends about one-and-a-half hours at the curb on average, whereas a robotaxi spends eight to ten times less time there, around eight minutes per ride served on average.

If you’re concerned about one of a city’s most valuable assets, the curb, it seems that robotaxis use that asset much more productively than personal vehicles do. Personal vehicles can simply park at the curb and stay there for a very long time. Obviously, people can get out and walk around and do many things while their vehicle is parked, but you still have a very valuable piece of land being occupied by a vehicle that isn’t actively serving passengers.

And I should say that buses are much more productive than robotaxis, which in turn are much more productive than personal vehicles. A bus is only at the curb for a very short period of time, but it can have many people getting on and off during that time.

What can cities do in terms of regulating the curb?

I’m not sure how many cities were considering banning robotaxis from using the curb, but if they were, I would say don’t do that. They might be increasing congestion a bit, but I think they’re providing valuable mobility to a large number of people in urban environments.

Moving beyond our study, I am generally in favor of having designated pick-up and drop-off zones where it is easy for robotaxi, ridehailing and taxi vehicles to get to the curb quickly, pick up a passenger quickly, and exit very quickly. So individual vehicles are not having to fight for curb space, and the vehicles are not spending much time at the curb at all. They’re just getting the passenger in the vehicle and moving away quickly.

I don’t think I’d be in favor of having designated staging locations for robotaxis or ride-hailing or taxi vehicles in general. But I think just allow these vehicles to use the curb for short-term parking, in the same way that private vehicles can.

What about personally owned driverless vehicles? What impact could they have on VMT?

That’s another area of research for my group. I’m not going to make a forecast as to when Waymo or Toyota or another company is going to be selling these vehicles to individual households. But let’s say in 10 to 15 years they do sell them to households. I think in that scenario, we have a lot of benefits to households in terms of mobility, but we have some very big potential implications for congestion and vehicle miles traveled.

What we’re seeing in our modeling results is that households absolutely will have the vehicle drop off one household member at work, drive home, pick up another household member, take them to an activity, whether that’s school or some after-school activity, and then drive back home empty again. In this case, a household might actually be able to own fewer vehicles because these vehicles can travel empty and deadhead back to the household. But that’s going to significantly increase VMT and congestion, unless of course there are some policies to make it more expensive to drive and make it more expensive to congest the roadways. So I think that’s a particularly important policy question for cities and states going forward.

This is like the Airbnb model for driverless taxis. We’re already sharing our homes, our parking spaces and if I buy an autonomous vehicle why would I let it sit in the car parking space when it could be out making me money, right?

We’re a little bit skeptical that people will be willing to give their $80,000 to $120,000 assets to strangers. But we do think there’s maybe an opportunity to get more use out of these valuable assets.

I’d be willing to lend my vehicle out occasionally or semi-occasionally to friends and family that live nearby, which maybe prevents them from buying a third vehicle or a second vehicle here in California. So I think there’s a nice opportunity there for some sharing of these personally owned driverless vehicles. But we’re a little bit skeptical of the model Tesla has discussed, where a Tesla owner lends their vehicle to a ridehailing fleet operator where anyone could be throwing up or using your vehicle for any type of purpose.

Yeah, you also have issues about cleanliness too. Any final thoughts?

I’ve been asked a number of times about whether cities should be charging robotaxis to use the curb and to drive around in urban areas and my answer is yes, but not just robotaxis. In my opinion, robotaxis should be subject to the same rules as all passenger vehicles in urban areas. If a passenger vehicle has to pay to park, a robotaxi should have to pay to park.

So, as a transportation analyst, I am in favor of congestion pricing. I think it’s worked very well in London. It worked very well in New York City. I think it can work in other large, dense areas, including Los Angeles and San Francisco. But I wouldn’t subject robotaxis to additional fees and additional taxes that you’re not subjecting personal vehicle owners to. If you actually want to reduce congestion, you need to charge all of the personal passenger vehicles for using very valuable space in urban areas.

Michael, it’s been a fascinating conversation. Thanks so much for coming on.

This interview has been edited for clarity and length.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Dave Ferguson, Co-Founder and Co-CEO of Nuro. Dave reflects on Nuro’s first decade, what has kept him motivated through the AV industry’s ups and downs, and how Nuro’s co-CEO structure works in practice. We also discuss the differences between leading the technical and business sides of an AV company and how Dave’s role has evolved over time.

Dave explains what makes Nuro’s approach to autonomy unique and takes us inside the company’s partnership with Lucid and Uber. We explore the vehicle’s hardware stack, how Nuro plans to differentiate as AV hardware becomes cheaper, and the latest milestones on the path toward fully driverless testing/deployment. Dave also shares how the Nuro Driver can generalize across different vehicle platforms and draws on Nuro’s previous driverless deployments to explain Nuro’s driverless capabilities.

The conversation also examines whether the AV industry is moving toward full vertical integration or greater specialization, how building the software and hardware stacks compares, and how Nuro’s partnership with Uber could expand over time. Finally, Dave shares Nuro’s broader goals and what comes next for the company.

Chapters

* (00:00) Introduction to Dave Ferguson

* (01:30) Nuro’s past decade, and the experiences thus far

* (03:05) What keeps AV company execs motivated in the long run?

* (05:28) How Nuro’s Co-CEO setup works, including the advantages, disadvantages, and roles

* (10:10) Comparing the technical vs. business sides of running an AV company

* (12:30) What makes Nuro’s approach to autonomy unique, and the Nuro–Lucid–Uber partnership

* (14:45) The most compelling aspect of the Nuro–Lucid–Uber partnership

* (15:35) Is the AV industry moving toward full vertical integration or greater specialization and partnerships?

* (18:06) The software vs. hardware aspects of AV development

* (20:45) The hardware stack on the Nuro–Lucid–Uber robotaxi

* (22:50) How to stand out in the era of cheaper AV hardware

* (24:48) The latest milestones in the Nuro–Lucid–Uber partnership

* (27:32) What it’ll take to remove the safety driver, achieve fully driverless testing, and Nuro’s past driverless deployments

* (30:05) How the Nuro Driver generalizes and transfers between different vehicle platforms

* (33:50) Nuro’s relationship with Uber, how their partnership could evolve, and Nuro’s goals

* (37:30) Conclusion and final thoughts

Notes/Links:

* You can find Dave Ferguson on LinkedIn/X.

* My previous interview with Nuro’s COO Andrew Chapin, mentioned at the 12:32 timestamp (link).

* Nuro, Lucid, and Uber announced plans to launch their robotaxi service in Houston in mid-2027 (link, no paywall).

* Nuro’s website (link).

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Peter Ludwig, co-founder and CTO of Applied Intuition. Peter shares how the company has evolved since its founding, the idea behind it, and its mission to accelerate the adoption of safe and intelligent machines worldwide. We also explore physical AI, how it differs from digital AI, and Applied Intuition’s partnership with HUMAIN.

Peter breaks down Applied Intuition’s work in autonomous trucking, including its partnerships, current deployments, plans for global scale, and what it will take to remove the safety driver and achieve fully driverless operations. He also explains the most common causes of failure in autonomous vehicle deployments, the role simulation plays in safely validating AV systems, and how much technology can transfer between different autonomous driving applications, such as trucks and robotaxis.

The conversation also covers end-to-end AI, Applied Intuition’s approach to commercializing and deploying the technology, and how the company works with partners to bring consumer products to market. Finally, Peter explains closed-loop simulation with reinforcement learning, reflects on lessons from nearly a decade in the industry, and shares his outlook on the future of autonomous vehicles.

Chapters

* (00:00) Introduction to Peter Ludwig

* (01:19) How the vision and operations at Applied Intuition have evolved from inception to today

* (03:54) Applied Intuition’s global footprint

* (04:16) Peter’s past work experience and the idea behind Applied Intuition

* (06:17) Applied Intuition’s mission

* (07:32) What is physical AI, and how does it compare to digital AI?

* (09:20) Applied Intuition’s partnership with HUMAIN

* (10:41) Details of Applied Intuition’s trucking vertical and how it will scale globally

* (14:00) Applied Intuition’s trucking partnerships and deployments

* (16:20) What it’ll take to remove the safety driver and achieve fully driverless operations

* (18:37) The most common causes of failure in AV deployments

* (20:25) The role of simulation in safely deploying AV systems

* (23:20) How much technology can transfer between different autonomous modalities, like trucking and robotaxis

* (26:50) Lessons learned from nearly 10 years of operations

* (29:12) End-to-end AI and Applied Intuition’s approach to commercializing and deploying it

* (31:09) Applied Intuition’s B2C approach and how it collaborates with partners to launch consumer products

* (33:15) Applied Intuition’s future plans and Peter’s outlook on the future of AVs

* (35:40) What is closed-loop simulation with reinforcement learning?

* (37:23) Conclusion and final thoughts

Notes/Links:

* You can find Peter Ludwig on LinkedIn.

* Applied Intuition’s website (link).

* Applied Intuition’s partnerships mentioned in the episode:

* HUMAIN, mentioned at the 9:20 timestamp (link, no paywall).

* Isuzu Motors, mentioned at the 14:14 timestamp (link).

* Stellantis, mentioned at the 31:17 timestamp (link).

* This partnership was extended in May 2026 (link).

* Applied Intuition’s SDS for Automotive, mentioned at the 29:51 timestamp (link).

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com

Listen to this episode on Apple Podcasts, YouTube, Spotify, and Substack. Transcripts are also available by clicking on the “transcripts” button in the top right corner of this post on the app/web version. You can also access them from the email version by clicking here.

In today’s episode, I’m speaking with Frank Reig, CEO of Voltera. Frank explains how the merger between Voltera and Revel came together and how the combined company is building the infrastructure needed to support autonomous vehicle fleets at scale.

We discuss where the industry currently stands in the AV deployment timeline, what has surprised Frank since entering the fleet-charging space, and why AV infrastructure development often takes much longer than vehicle deployment. Frank also breaks down what goes into developing a full-stack AV depot, from finding suitable real estate and securing power to providing charging, maintenance, and operational support. He explains how Voltera evaluates potential locations, works with customers to plan their infrastructure needs, and differentiates itself from other charging and depot providers.

We also explore the operational challenges these facilities will face, how depots can adjust to shifting ride-hail demand, and what AV fleets could look like as they reach greater scale. Finally, Frank shares the trends he expects to shape AV infrastructure and what’s next for Voltera.

Chapters

* (00:00) Introduction to Frank Reig

* (01:45) The Voltera-Revel merger and how it came together

* (04:26) Voltera’s footprint, operating domain, and current focus

* (05:13) What phase are we in the AV deployment timeline?

* (06:38) What has surprised you since entering the AV fleet charging space?

* (07:30) What actually goes into setting up an AV depot?

* (10:04) How AV vehicle and infrastructure deployment timelines differ

* (10:43) How Voltera supports its AV fleet partners with full-stack AV depots, including charging, maintenance, and operations

* (12:04) The unexpected challenges of building out AV depots

* (13:21) What factors do you consider before developing an AV depot at a location?

* (16:01) How customers typically approach AV depot development with Voltera

* (17:30) The strategy behind selecting the best sites for AV depots

* (20:42) How Voltera stands out among its competitors

* (22:30) Potential challenges in AV depot operations

* (24:19) What Voltera does and what it doesn’t do

* (25:50) What will AV fleets of the future look like, and what are the benefits of scale?

* (28:02) Future trends in AV depot development

* (29:30) How AV fleet infrastructure adjusts for shifting ridehail demand

* (31:03) Voltera’s roadmap and future plans

* (32:10) Conclusion and final thoughts

Notes/Links:

* You can find Frank Reig on LinkedIn.

* Voltera’s website (link).

-Harry

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thedriverlessdigest.com