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.

Indeed, the world’s largest job search engine, reports that Aptiv is posting far and away the most self-driving car job openings. Aptiv spun out from Delphi, a Tier 1 auto supplier, a few years ago. They also acquired nuTonomy, which at the time of acquisition had logged more self-driving car miles than all but a handful of competitors.

Following Aptiv on the list is NVIDIA, and then SAIC Innovation Center (the Chinese auto supplier, not the US government contractor of the same acronym).

It would be interesting to get an absolute number of jobs from this report, rather than a percentage. When I search Indeed for jobs at SAIC Innovation Center, I only see a handful of listings. But maybe the number has waxed and waned over time.

Bosch and Daimler, which are partnering hand and glove on autonomous technology, come in at 4 and 5.

Meanwhile, Cruise Automation, which is has plastered hiring billboards up and down highway 101 in Silicon Valley, only rings at number 6, followed by GM.

The rankings don’t really match my intuition of who is hiring and how much, but presumably Indeed has data that I don’t.

The report also lists the top geographies for these jobs.

Silicon Valley — Technically this covers two places on the list: #1 San Jose and #4 San Francisco. A combination of Stanford, UC-Berkeley, Google, and a lot of venture capital and software engineers has made this the new center of robotics.

Pittsburgh — Carnegie Mellon University has spawned a bunch of corporate robotics teams, notably Uber ATG, Argo AI and Aurora.

Detroit — The center of the automotive industry, dating back to Henry Ford.

Portland — I assume this is mainly on the list due to Daimler Trucks?

Boston — MIT has not spun out quite as many robotics efforts as CMU, but nuTonomy counts for a lot, and there are other groups, too.

Baidu’s Apollo program has announced a self-driving car test in Changsha, Hunan, China, that is open to the general public. The program features 45 self-driving L4 Hongqi EV vehicles, the result of a joint partnership with FAW Group.

It’s always a little hard to know exactly what’s happening in China, because the non-Chinese press struggles with both access and language. The articles I’ve read use phrases like, “debuted”, “are being released”, and “kicked off”. Sounds like the program is already underway?

There is a human safety driver onboard, of course, and the geofence is limited to about 30 miles, although Baidu intends to expand.

Self-driving car deployments are trickling out, albeit not quite as fast as many of us had hoped. Opening up programs to the general public, as opposed to a limited and pre-screened group, is a big step forward.

I’m excited that Baidu is doing this. And I would love to see a video or writeup of what it’s like.