Tesla cannot impact UBER's base in the short term

Focus:

Demand side: Passengers may focus on efficiency and price

Efficiency (average waiting time) lies in the supply of vehicles and the rationality of vehicle distribution. In terms of quantity, the number of self-driving taxis may be difficult to reach that of traditional vehicles (due to the cost of purchasing/manufacturing vehicles, and the gig economy of traditional vehicles is more flexible). In terms of rationality of vehicle distribution, self-driving vehicles may have more advantages (idle vehicles can be deployed based on big data algorithms, and traditional drivers may be relatively more easy-going)

In terms of price, self-driving may have more advantages in the long run (positive factors mainly come from saving labor costs, and negative factors mainly come from the high purchase cost of self-driving vehicles, which requires more trips to be amortized, so the key point is whether the number of trips can fully amortize fixed costs)

Supply side: technology maturity, cost

Technology maturity: The technology behind Tesla robo taxi is relatively complex. Although Tesla has made significant progress in self-driving technology, achieving fully autonomous driving (Level 5) without supervision is still a development obstacle for Tesla and the entire automotive industry.

Cost:

First, in terms of fixed costs, the purchase cost of self-driving cars is higher than that of private cars that drivers can own in the gig economy;

Second, in terms of maintenance costs, similarly, in the gig economy, car owners pay for maintenance themselves, while self-driving cars need to pay for it themselves;

Third, in terms of operating costs, insurance premiums may be higher for self-driving cars in the short term, and will gradually decrease as the safety of self-driving cars is recognized. Whether it is lower than the insurance premium of traditional cars depends on the relative size of the accident rate. Fuel costs are paid by traditional car owners themselves, while self-driving electric cars need to be borne by enterprises. Self-driving cars do not need to pay for labor costs.

Regulatory issues:

In terms of safety standards and testing, regulators need to develop specific safety standards for self-driving vehicles, and the testing standards before approving them to drive on public roads are not yet mature.

In terms of liability, the regulatory issue of determining liability when a self-driving taxi has an accident has yet to be resolved, and the legal framework regarding who is responsible (manufacturer, software developer or operator) has not yet been perfected.

In terms of data privacy, self-driving taxis collect and process large amounts of data to operate safely and efficiently, and concerns about data privacy and the possibility of hacker attacks also pose certain regulatory risks.

Possible future development:

Based on the above analysis, Tesla needs to meet the following conditions to develop the taxi market alone:

1. A sufficient amount of trips to share the costs of car manufacturing and various costs, so it may be necessary to have enough robo taxis in the short term to ensure customers' efficiency requirements;

2. Public acceptance. Currently, autonomous driving accidents are still frequent, and public acceptance is difficult to improve in the short term.

Therefore, at least in the short term, Tesla needs to pay a lot of costs to gain the market. In the long run, if it can prove to be better than traditional taxis in terms of price, it will be sustainable.

(Uber and Tesla have previously cooperated: In December 2023, Uber Japan announced a partnership with Tesla to deploy 100 Tesla Model Y vehicles in Tokyo by the end of 2024. This move is mainly to promote green urban transportation solutions)

Uber's autonomous driving technology progress:

At the end of 2020, Uber officially announced that it would abandon the research and development of autonomous driving technology, and at the same time sold its autonomous driving department ATG (Advanced Technologies Group) established in 2016 to its competitor Aurora in exchange for 26% of Aurora's equity. Uber said that through cooperation with Aurora, it hopes to fulfill its promise of autonomous driving faster.

Currently, Uber has not disclosed the subsequent progress of autonomous driving. If the technology is not too far behind Tesla, Uber can also develop autonomous driving vehicles in the future. Tesla's main advantage is the economy of scale in car manufacturing. Uber can rely on the existing MAPC quantity advantage to complete the penetration of autonomous driving more steadily.