Cruise paid robotaxi just opened for business in San Francisco this Jun. That’s a small step for a company, one giant leap for the robotaxi business. Why is this significant? What will the future hold?
1st public beta
On Jun. 2, 2022, the California Public Utilities Commission (CPUC) issued the 1st driverless permit for GM Cruise to provide the robotaxi service to the public. On Jun. 22, 2022, Cruise got paid for the 1st robotaxi ride in San Francisco, a giant leap to commercialize robotaxi indeed. Even though Cruise is authorized to collect fares, it’s more of a “public beta” in terms of scope & scale because the service is still very limited, as:
- With the maximum speed being 30 mph, the initial service area is only about 1/3 of the city in northwest San Francisco.
- A fleet of 30 GM Chevrolet Volt EVs serves in less busy hours from 10 p.m. to 6 a.m.
- Under good weather without heavy rain, heavy fog, heavy smoke, hail, sleet, or snow.
Two towers
LiDAR & Camera are the 2 critical sensing technologies for Self-Driving(SD). Because of their pros & cons, 2 different approaches to SD prefer one over the other.
- Consumer first: the camera is preferred because of its low cost & scalability, such as Tesla. This starts from L2+ and will gradually improve to reach higher levels of autonomy as computer vision technology advances and fidelity, coverage & realtime of the dataset increase.
- Robotaxi first: LiDAR is the choice because its accuracy is better. This camp shoots for L4+ directly, such as Cruise & the rest players. Because robotaxi can be a paid service, it’s better for the operators to pay more for a much lower risk.
So, which is the one most likely commercializing SD this round? With Cruise’s first public beta, it does seem the “Robotaxi first camp” leading the way for now. However, the public beta is just the beginning. Who will reach the end first is still TBD? What do you think?
This time is different
My bet is on the “Consumer first camp” for the long run. If all other things are equal, my 2 key hypotheses are:
- The raising of Sharing Economy has transformed the taxi business. For example, Uber & Lyft build fleets without owning the cars nor hire drivers directly. These have been the key advantages for them to complete with the incumbents. So if you are serious about the robotaxi business, you better factor this in rather than model your business based on the old taxi operation model.
- Camera & computer vision have the potential to pull the Low-end disruption trick. Especially for the SD, “data is the new oil”. With a mass & growing distribution to harvest real-time data, a player can improve SD much faster than others don’t. Assuming the Camera & Computer Vision systems improvement iteration outpaces the LiDAR system significantly. So far, it’s the case.
Game on
Luckily, we don’t need to pick in a free market. A health competition will get us there sooner. So, how can robotaxi first camp play better? My 2 cents:
- Focus on metropolitan areas to build the critical mass & better “last miles” experience first. This is an important strategy because it’s so tempting to sidetrack for wider areas. It may be nice later, but for now, the complexity will just make the service & tech mediocre.
- Play the long game to transform the city first. Robotaxi will only cost less than a taxi significantly after a certain critical mass because its low marginal cost comes from a high Non-Recurring engineering Expense. Therefore, pursuing ROI prematurely will cost you long-term opportunities. Why not push forward to make the city mobility 10x better instead? e.g. what-if parking is obsolete in the city, how much value can you unlock? What-if buses are replaced, how convenient can it be for passengers? What-if human drivers are not needed in the city, how much safer can the transport system can be?
The opportunity window will not open forever. This Apr., Tesla also announced its robotaxi will reach volume production in 2024. Which will be a 5x-10x reduction of the cost per mile & accessible to everyone. Let’s wish the best business wins.
Full Disclosure
The opinions stated here are my own, not those of my company. They are mostly extrapolations from public information. I don’t have insider knowledge of those companies, nor a whatever expert.
