Porter’s Five Forces is one of the classic frameworks that business schools teach for evaluating the attractiveness of a business or industry.. Michael Porter, a professor at Harvard Business School, invented it.

The framework is, at its core, a five-item checklist:

1. Barriers to Entry
2. Substitution
3. Supplier Power
4. Customer Power
5. Existing Competition

I’m re-wording Porter’s original definitions to the phrases I think of when I step through the checklist, but that’s the gist of it.

I thought of this checklist during a recent conversation about strategy for Waymo (Google’s Self-Driving Car division).

One school of thought is that Google should position itself as the supplier of software to the automotive industry. That’s a position that’s worked well for Android, and it plays to Google’s strengths as a software company.

An alternative school of thought is that Google should build out its own transportation-as-a-service business, because car manufacturers are too smart to get trapped with Google’s software. They’ve seen how that played out for the mobile handset manufacturers, and they don’t want to get “Samsungized”.

Rather than choose between these two approaches, I want to focus here on the narrow question of whether the car manufacturers are “too smart” to get trapped with Google’s software.

The people I worked with at Ford are very smart, and I imagine the same is true at Toyota and GM and most other manufacturers.

But this is where Porter’s five forces comes in.

As a automotive software vendor, Google is in an industry with low “customer power”. There are a lot of different car manufacturers.

Some of those manufacturers are going to be way behind the curve in terms of developing autonomous vehicle software. And those manufacturers will, rationally, decide that their best bet for catching up with the pack is to partner with Waymo.

So regardless of how smart the car manufacturers are, there will be manufacturers out there who will be interested in using Waymo’s software.

This year was the first CES appearance for Waymo, although it has appeared in previous years under the name, “Google Self-Driving Car Program”.

Waymo CEO John Krafcik used the opportunity to shed some light on a perpetual parlor game for self-driving car enthusiasts: “what is Google’s strategy for self-driving cars?”

Google has had self-driving cars scooting around Mountain View for years, but it’s always been unclear what the go-to-market strategy would be, and when it would start rolling.

Krafcik’s statements indicate that Google’s long game may be as a provider of autonomous vehicle hardware and software, rather than as an auto manufacturer or a transportation-as-a-service provider.

Krafcik specifically highlighted Waymo’s gains with its in-house LIDAR sensor technology. Along with adding short- and long-range sensing units for better detection than its previous systems, the company has managed to slash the cost of its LIDAR by more than 90 percent in two years from about $75,000 per vehicle.

…

Krafcik’s language is telling — those “firsts” imply that this is just the start of Waymo’s autonomous partnerships, with many more to come. By focusing on the production of its own hardware along with software, Waymo won’t become a major automaker, at least not yet. Instead, it clearly intends to be the go-to supplier of autonomous driving systems for automakers that don’t want the expense of developing their own.

I’m not convinced the mystery has been solved yet, but it’s an important clue in the Google guessing game.

Nissan is considering building out its self-driving cars in conjunction with call centers staffed by representatives who can help the self-driving cars get out of sticky situations.

According to Wired, Nissan calls this system “teleoperation” and views it as unavoidable, at least in the short term. Weird things happen on the road and the car won’t be able to figure it all out on its own. If the car also doesn’t have a steering wheel, that leaves tele-drivers as the next best option.

On the one hand, this makes perfect sense. Wired draws an analogy to an elevator, which almost always has an emergency call button that presumably (I’ve never tried) dials somebody who can help.

The rub seems to come down to whether these call centers are staffed by representatives who only step in at critical junctures, or whether the vehicles are really “teleoperated”.

The latter doesn’t seem safe (latency being a big problem) and doesn’t seem like a big improvement over normal human driving, but it’s an interesting minimum viable product.

Frank Chen is a Partner at Andreesen Horowitz who publishes terrific summaries of exciting area of technology.

A while back we talked on the phone about a self-driving car presentation he was thinking of putting together.

He put it together and it’s a terrific discussion of 16 Questions About Self-Driving Cars.

1. Straight the Level 5 or not?
2. LIDAR or not?
3. Pre-computed HD maps, or build on the fly?
4. What blend of computation techniques?
5. How much real world vs. virtual world testing?
6. Will V2X radios play an important role?
7. Can we get rid of traffic lights and four way stops?
8. How will automakers “localize” their cars?
9. How will accident rates trend?
10. When will it become illegal to drive?
11. How will insurance change?
12. Who will win? Silicon Valley vs. China vs. Incumbents
13. Will we buy cars or transportation as a service?
14. How will commute times change?
15. How will cities change?
16. When will this start, and then how quickly will we change to autonomous cars?

Watch the whole presentation!

On Friday, January 20th, I will be speaking at the Global Artificial Intelligence Conference in Santa Clara on “How to Become a Self-Driving Car Engineer”.

The talk will be similar to one I gave for the Bay Area AI Meetup, but with a new live-coding exercise!

Come out to say hello and learn how to become a self-driving car engineer with Udacity’s Self-Driving Car Engineer Nanodegree Program.

Our partner HARMAN has a new concept out for how to handle human-vehicle interaction in a Level 3 autonomous vehicle!

Full Windshield Heads-Up Display: Oasis utilizes the full windshield to project navigation prompts and other information to the driver, while also simultaneously projecting entertainment or information to the passenger.

Autonomous Drive Readiness Check — Handover to Manual: One of the most critical concerns of autonomous vehicles is how to ensure the transition between autonomous mode and manual mode is handled seamlessly. HARMAN’s solution combines haptic feedback, eye gaze tracking, and the driver’s cognitive load readiness through pupil monitoring, to ensure that the driver is truly engaged and able to safely take control of the steering wheel.

Augmented Reality Concierge: This solution addresses the need to support increased productivity in the car while minimizing distraction. A voice-controlled virtual assistant functions as a concierge, automatically suggesting and displaying personalized points of interest while enabling advanced in-vehicle productivity to join conference calls, update calendars and more. Through Skype connectivity, the system can even translate telephone conversations — in real time — with colleagues speaking different languages.

Predictive Collision Prevention: V2X (vehicle-to-vehicle and vehicle-to-infrastructure) technologies detect objects on a collision course and offer corrective action.

Intelligent E-Mirrors: Mirrors that are automatically activated/dimmed based on user gaze.

On the first day of 2017, here’s what I think the year to come has in store for self-driving cars.

In the style of Scott Alexander, I attach confidence levels to my predictions.

1. 1 Udacity Self-Driving Car Engineer Nanodegree Program student will start a new, permanent, full-time autonomous vehicle job: 99%
2. Level 4 self-driving cars will be available for ridesharing on public roads somewhere in the world: 90%
3. Level 4 self-driving cars will be available for ridesharing on public roads somewhere in the United States: 90%
4. Ford will not push back its 2021 target launch for Level 4 vehicles: 90%
5. 100 Udacity Self-Driving Car Engineer Nanodegree Program students will start new, permanent, full-time autonomous vehicle jobs: 90%
6. No US highway will have a speed limit for autonomous vehicles that is faster than the speed limit for human-driven vehicles: 90%
7. 1000 Udacity Self-Driving Car Engineer Nanodegree Program students will start new autonomous vehicle jobs (possibly contract roles or internships): 80%
8. Level 4 self-driving cars will be available for ridesharing on public roads in Singapore: 80%
9. A company will be acquired primarily for its autonomous vehicle capabilities with a valuation above $100 MM USD: 80%
10. No company will sell a vehicle with autonomous technology that exceeds what Tesla offers: 80%
11. At least 1 company that has not done so before will complete a continuous US coast-to-coast demonstration trip in a fully autonomous vehicle: 80%
12. Level 4 self-driving cars will be available for ridesharing on public roads in California: 70%
13. Conditional on Level 3 self-driving cars being legal somewhere, Tesla will enable Level 3 autonomy in that location: 70%
14. Google will offer rides to the public in its self-driving cars: 70%
15. No member of the general public will die in a Level 4 vehicle: 70%
16. 2500 Udacity Self-Driving Car Engineer Nanodegree Program students start new autonomous vehicle jobs (possibly contract roles or internships): 60%
17. Level 4 self-driving cars will be available for ridesharing on public roads somewhere in Europe: 60%
18. Level 4 self-driving cars will not be available for ridesharing on public roads somewhere in China: 60%
19. No company will be acquired primarily for its autonomous vehicle capabilities with a valuation above $500 MM USD: 60%
20. A new autonomous vehicle startup will form and raise money at a valuation above $75 MM USD: 60%
21. Ford will commit to launching Level 4 vehicles before 2021: 50%
22. Level 4 self-driving cars will be available for ridesharing on public roads somewhere in the world, without a safety driver: 50%
23. Level 3 self-driving cars will be available for private ownership somewhere in the United States: 50%
24. Somebody will die in a Tesla Autopilot crash: 50%
25. Level 4 autonomous vehicles will be available for public ridesharing when snow is on the ground: 50%

Note: Udacity has partnerships with several companies I mention here, and I used to work at Ford, but none of these predictions stem from non-public information.

Update: The SAE definitions are here: https://en.wikipedia.org/wiki/Autonomous_car#Classification

Basically, a Level 3 vehicle is fully self-driving, but the driver must be able to take control of the vehicle at a moment’s notice.

A Level 4 vehicle is fully self-driving in most situations, and the driver does not need to be ready to regain control of the vehicle.