I am excited to head to Auckland, New Zealand, tomorrow, where I will be participating in the inaugural Workshop on Education in Autonomous Driving Technologies!

I will present Teaching Autonomous Driving at Massive Scale at 9am on Sunday, October 27. WEinADT (as it is called) is part of the larger IEEE Intelligent Systems Transportation Conference.

Professor Alexander Carballo has done terrific work organizing the workshop and I am lucky to be a part of the agenda!

This will be my first time visiting New Zealand, and I am super-excited to participate in WEinADT and ITSC. If you’re going to be at ITSC, please swing by my presentation at 9am on Sunday to say hello!

If you happen to be in New Zealand, even if you won’t be attending ITSC, send me (david.silver@udacity.com) an email! I’d be delighted to meet some friendly faces in Auckland.

Reilly Brennan, a venture capitalist at Trucks.VC and one of the movers and shakers in the world of autonomous vehicles (seriously, look at that investment portfolio!), has a short post critiquing the naming regulations for advanced driver assistance systems.

“We’re probably using [driver assistance systems] the wrong way and I believe a significant contributor to that problem is the branding and marketing of these systems.”

In particular, Reilly points out that USDA food labeling standards are much more stringent than labeling standards for driver assistance systems, which don’t even really exist.

“But if you want to brand your car’s systems as Auto-magic-pilot-drive-yourself, there is little today that the US Department of Transportation or Federal Trade Commission will do to prevent you.”

He doesn’t quite prescribe a solution, but calls for “equal attention” between food labeling and vehicle systems, particularly because vehicle systems can kill other people on the road besides just the customer of the system.

I’m genuinely uncertain how to handle this myself, and the post is worth a read and a ponder.

On a recent episode of MergeNow, Ed Niedermeyer interviewed Jon Mullen of RightHook, an autonomous vehicle simulation startup. I worked with Jon at Ford, so I was particularly interested.

Jon was on the show describing ScenarioScript, “an open format scenario-describing language.” Think of ScenarioScript as a format for describing traffic scenarios for autonomous vehicles, including variables like weather, road dimensions, and other relevant parameters.

Early in the show, Ed asked Jon if the release of ScenarioScript is an attempt to move everyone onto RightHook’s ecosystem. Jon said that was not the case, and it’s worth listening yourself to hear why and decide whether you believe that.

What struck me, though, was the question of whether and why it ever would be remunerative for a company to move the world onto its chosen open-source ecosystem.

The best example I can think of this is Bell Labs, where Unix, C, and C++ were invented, along with lots of other things. Bell Labs seems to me to be understudied — the Wikipedia section on Nobel Prizes and Turing Awards is tremendous and must outstrip any other non-university in the world, certainly any for-profit entity.

But it’s less clear how much Bell (later AT&T, and now Nokia) benefited from these inventions. At the very least, the through-line from open-source creation to corporate profit requires some thinking.

Another, smaller, example is Willow Garage, the technology incubator that at one time maintained ROS, OpenCV, and PCL. All of those projects have been critical for self-driving car development, and robotics more generally. But Willow Garage dissolved as an entity in 2014.

The list could keep going. The success of Java was, at least, insufficient to prop up SUN. JavaScript didn’t save Netscape, or its eventual acquirer, AOL.

Perhaps the most prominent counterexample is Android, which has made Google lots of money (I think) via Google Play commissions on apps.

Other companies are centered around developing hosting and services for a particular open-source project. MongoDB Inc. does this for MongoDB, Elastic does this for Elasticsearch, and Databricks does this for Apache Spark. All of these companies have been quite successful, but in the long run, Amazon Web Services and other cloud providers look like real threats.

Looking over this list, I actually think the invention of JavaScript at Netscape is the most instructive. JavaScript was transformational for the browser industry, and the Internet generally. But the open-source nature of the tool may have limited the value that Netscape specifically was able to capture.

A similar case might pertain to Unix, C, and C++ at Bell Labs.

These tools were a tremendous benefit to the entire industry, and perhaps helped Netscape and Bell at the expense of alternative (TV and postal mail, respectively?). However, the benefit accrued to the entire industry, not only to the company that invented to the technology.

To bring this full circle, if you go back and listen to Jon Mullen’s rationale for open-sourcing ScenarioScript, that’s what he says 😉

Dan Primack has been writing about the stumbles of VC-backed companies that have grown tremendously but struggle with unit economics. WeWork is the poster child of the moment, but per Primack:

“There are dozens, if not hundreds, of other mature startups caught with their income statements down.”

While he’s not quite willing to come out and make a bold prediction, he hints that maybe, possibly, things might be tough for certain types of startups:

“For companies with reasonable controls and paths to profitability, all systems remain go….But for unicorns that never looked beyond the trough, it could be slaughter season.”

Where I think this intersects with autonomous vehicles is that so many AV startups have raised huge amounts of money without a clear path to revenue, much less profitability.

This aligns with another trend, which is the increasingly common belief that the deployment of driverless (i.e. no safety operator) Level 4 vehicles is going to take a while.

Yesterday I quoted an estimate from Aurora:

“We expect to see small-scale deployments of self-driving vehicles in the next five years, and then see the technology phase in over the next 30 to 50 years.”

Autonomous vehicles have tremendous capital requirements, which have thus far been financed either by automotive companies or VC firms. This has, in some cases, been spectacularly successful for early investors.

But if the funding well dries up, and we’re looking at 30 to 50 years until meaningful deployment, there’s going to be a push for revenue in the near term.

I’m interested to watch those revenue sources emerge.

Aurora founder and CEO Chris Urmson is one of the most experienced and most respected self-driving car engineers in the world. His team authored a safety report earlier this year: “The New Era of Mobility.”

Recently, Urmson followed up that report with a summary of Aurora’s approach to safety:

1. CULTURE: Practice a culture of safety
2. TECHNOLGY: Develop the technology safely
3. METRICS: Establish safety metrics
4. COLLABORATION: Engage and educate

The post is worth insightful and worth reading.

Safety culture, in particular, is a critical input to safe autonomous vehicles, and one that is easy to overlook. Aurora’s focus on this is reassuring.

I would love to see more detail around metrics. Urmson states,

“At Aurora, we’ve made a commitment: We won’t deploy our self-driving vehicles on public roads without human safety drivers until our technology is safer than a human driver. Which begs the question, what does safer than a human driver actually mean?”

A few sentences later, he seems to concede that Aurora hasn’t yet zeroed in on a meaning: “we continue to focus on identifying these metrics.”

Earlier in the post, Urmson reveals:

“We resist the urge to put more and more cars on the road in an effort to ramp up on-road miles. Instead, we use on-road testing to validate our virtual tests.”

This seems in tension with the commitment to ensure super-human safety prior to deployment. In order to truly validate that Aurora’s technology is “safer than a human”, it seems like that technology is eventually going to have to go on the road in a big way.

The search for coherent AV safety standards continues.

And it might take a while:

“We expect to see small-scale deployments of self-driving vehicles in the next five years, and then see the technology phase in over the next 30 to 50 years.”

The Society of Automotive Engineers just updated their guidance for testing automated driving systems. The report, J3018, costs $81 to view and summary seems more concerned with what the report does not cover as what it does.

“This document provides safety-relevant guidance for on-road testing of vehicles being operated by prototype conditional, high, and full (Levels 3 to 5) ADS, as defined by SAE J3016. It does not include guidance for evaluating the performance of post-production ADS-equipped vehicles. Moreover, this guidance only addresses testing of ADS-operated vehicles as overseen by in-vehicle fallback test drivers (IFTD).

These guidelines do not address:

– Remote driving, including remote fallback test driving of prototype ADS-operated test vehicles in driverless operation. (Note: The term “remote fallback test driver” is included as a defined term herein and is intended to be addressed in a future iteration of this document. However, at this time, too little is published or known about this type of testing to provide even preliminary guidance.)

– Testing of driver support features (i.e., Levels 1 and 2), which rely on a human driver to perform part of the dynamic driving task (DDT) and to supervise the driving automation feature’s performance in real time. (Refer to SAE J3016.)

– Closed-course testing.

– Simulation testing (except for training purposes).

– Component-level testing.”

I have not purchased the report, so I can’t speak toward its contents. I can say that the SAE Autonomy Levels, although controversial, have been tremendously helpful in establishing a vocabulary for the industry.

Lots of automotive groups are grasping toward any sort of guidance around testing and certification. Getting the industry to converge seems like a key milestone in deploying production-level self-driving cars to the public.

The SAE might gain more by suggesting testing guidelines in the public domain, rather than behind a paywall.