For the first fifteen years of my career in software, I barely used algebra. Web development requires plenty of abstract reasoning, but not higher math. Since working on autonomous vehicles, however, I constantly find myself revisiting topics I last touched in high school.

Pythagorean Theorem is a great example.

a*a + b*b = c*c

When on earth would you actually use this in “real life?” A few years ago I might have said never. Now I use it all the time.

Imagine I’m trying to calculate a vehicle’s acceleration, and the sensors tells me it’s accelerating 1 meter per second in the x-direction and 0.5 meters per second in the y-direction. What is the acceleration in the vehicle’s own frame of reference?

I’d use Pythagorean Theorem to find the answer. You can try it with an online calculator. What’d you get?

Volkswagen has released a rendering of its 2025 self-driving car, which will be based on the ID. Buzz electric vehicle platform, which itself is a re-imagining of the iconic VW Bus. The autonomy software stack will come from Argo, which Volkswagen partially owns.

A major notable feature of this vehicle is that it is uni-directional with front-facing seats. In this respect, it resembles Waymo’s active driverless vehicles, which are based on the FCA Pacifica minivan platform, and the Jaguar I-PACE SUV platform. In contrast, both Cruise and Zoox have announced new vehicle platforms, specifically designed for autonomy, that are bi-directional, with no front or rear.

Just as the original automobiles were “horseless carriages”, designed to resemble horse-drawn carriages, it makes sense both that early self-driving vehicles would resemble traditional automobiles, and also that we will soon find form-factors more conducive to a driverless vehicle. What that more conducive form factor is, remains to be decided.

Reilly Brennan’s Future of Transportation newsletter included links to the pitch decks that Joby and Lucid used in their recent SPACs. In an alternate universe, these would have been the pitch decks presented to growth- and late-stage venture capitalists, and wouldn’t have been available to the public. Because both Joby and Lucid went public via reverse mergers with SPACs, their pitch decks are also public.

The Joby deck has forty beautiful slides and a ton of information. I found it a little hard to parse, though, perhaps because I’m not used to navigating decks of companies at this stage.

I did not a few items:

• Joby plans to start generating revenue in 2024, and to reach “scale” in 2026.
• The pro forma financials call for revenue growth from $0 in 2023 to $2BB+ (!!) in 2026.
• At scale, they anticipate the vehicle to cost $1.3MM.
• The projected returns for investors seem maybe not that great? Again, I found this hard to parse, but I think they hypothesize that if they hit their 2026 goals, and if the stock market applies a 25–30x P/E multiple (!!), then investors today would see a 20% (annual?) return. Lots of caveats.
• They forsee a robust market for intra-city transport.

• They will focus on “meaningfully” penetrating each city before moving on to the next, and thus only anticipate penetrating 20 cities in the next ten years.
• They project an average trip length of 24 miles, with an average “passenger load” of 2.3, and a price point of $3 per “seat mile.” Each vehicle will have 4 passenger seats, so the price point per “vehicle mile” is presumably $12. For a hypothetical 24 mile trip, the price would then be $288 total, but potentially as low as $72 per passenger, split four ways. They present this as “cheaper than Uber black for an individual.”

I am spending most of today “in the field,” at The Villages, San Jose, where Voyage is preparing to launch a driverless robotaxi service for senior citizens.

This is my first trip to The Villages, and my first time riding in a Voyage vehicle. I love it!

I’ve been fine-tuning the brake control parameters for our 3rd-generation vehicles, largely from home (everyone works from home right now), using data collected in the field by our operations team. Today was an opportunity to ride along in the vehicle itself and see how well the brakes perform.

Riding in the vehicle is such a different and more visceral experience than sitting at a desk, working with data files on a computer. I could really feel what was comfortable and what wasn’t, in a way that normally gets relayed second-hand from our operations team.

And, since this was my first trip to The Villages, I got a much better understanding of the streets and the environment where we operate. Reviewing top-down maps or even vehicle sensor feeds just doesn’t provide the same level of context and being in the operational design domain (ODD).

This is a big part of what makes working on self-driving cars so much fun!