Uber: Can autonomous driving really kill the "American Didi"?

As one of the most favored targets by Dolphin Research with long-term investment value, $Uber Tech(UBER.US) has seen its once bullish market sentiment fade amid concerns that rapidly developing autonomous driving technology (especially with Tesla's rising prominence and high-profile announcement of its Robotaxi plan) will bring revolutionary changes to the entire automotive and mobility industry. From October 14, 2024, to mid-December 2024, the stock price fell from $87 to below $60, representing a nearly one-third retracement, significantly underperforming the S&P index during the same period.

Nevertheless, the market's long and short battle over Uber remains quite intense. Notably, famous investor Bill Ackman has publicly announced his bullish stance on Uber, and JP Morgan included Uber as one of the most favored mid-cap targets in its investor survey at the beginning of January. Discrepancies in opinions are one source of opportunity, creating chances to invest in good companies that are unanimously favored but lack valuation appeal.

Therefore, taking this opportunity, Dolphin Research will explore whether Uber, after a significant correction, fully reflects the impact brought by autonomous driving technology. Is Uber currently offering clear value for money, or is it still standing on the "edge of a cliff," appearing to have "value" but being a "trap"?

From the perspective of analysis, this article will discuss the impacts of autonomous driving becoming a commonplace technology on mobility and the ride-hailing industry, the actual development path and timeline of autonomous driving technology, and which companies or technological paths will ultimately prevail are not within the scope of our discussion. Thus, we will make the following two assumptions as the basis for further analysis:

① Autonomous driving technology can reliably achieve driving capabilities that are not lower than, or even exceed, those of human drivers, in terms of safety, speed, and various other aspects. Furthermore, the government does not restrict the widespread implementation of autonomous driving;

② The autonomous driving industry will give rise to multiple suppliers (in the single digits or more) without significant technological disparities, some of which will provide these technologies to third parties.

The following is a detailed analysis:

1. How will the demand for ride-hailing change in the era of autonomous driving?

Before discussing the impact of autonomous driving on specific companies and the ride-hailing business model, Dolphin Research believes that the first question to answer is, what kind of impact does autonomous driving technology have on the total volume and structure of overall (automotive or urban) mobility demand? First, we believe that the fundamental change brought by autonomous driving technology is the liberation of the manpower and its associated costs required for driving. In other words, its innovation mainly manifests in the reduction of costs Based on this judgment, we believe:

The benefits of autonomous driving technology on the overall growth of travel demand should not be significant. The underlying logic is that travel is merely a tool rather than a goal in itself; few people travel "just to ride." Therefore, compared to technological innovations like cars vs. horse-drawn carriages or airplanes vs. cars that can significantly expand the destinations people can choose or greatly reduce travel time, we believe the reduction in driving costs brought about by autonomous driving technology will not have a noticeable positive impact on travel demand growth. From a medium to long-term perspective, if autonomous driving can completely change the current form of passenger cars or the operation of road traffic, it is more likely to lead to a more significant increase in total demand for car travel (not elaborated here).

The impact of autonomous driving technology on the travel market should be more reflected in the changes in the structure of travel modes (the proportion of various channels). First, from historical data, the proportion of various channels for passenger travel in China (by amount) has shown a trend of change from 2018 to 2023, where the proportion of private car travel in China is the highest and continues to rise (recently reaching about 85%); the proportion of public transportation continues to decline (from nearly 12% to about 5%); the overall proportion of ride-hailing and taxis remains stable at around 7% to 10%, with a trend of ride-hailing eroding the share of taxis internally.

Similarly, the commuting methods of American residents show that the proportion of private cars accounts for the vast majority (over 90%), with public transportation being the second (accounting for 3% to 5%), and the proportion of taxis and others (including ride-hailing, motorcycle taxis, etc.) being very low at only 1.4% to 1.8%.

In terms of trends, the most significant change has been a substantial increase in the proportion of working from home (WFH) (5.7%/17.9%/13.8% in 2019/2021/2023 respectively), leading to a decrease in the original proportions of other travel modes. Excluding the impact of WFH, the main changes before and after the pandemic are the increase in the proportions of private cars and taxis & others, while public transportation is the main loser in terms of share. However, as the impact of the pandemic fades, by 2023, a considerable portion of the growth in shares for private cars and taxis has already returned to public transportation. (It should be noted that the above data only pertains to commuting scenarios and may underestimate the share of ride-hailing & taxis across all scenarios.)

From the above, in recent years, whether in China or the United States, the changes in travel structure are characterized by a decline in the share of public transportation and an increase in the shares of private cars and ride-hailing. (Of course, there is an influence from the COVID-19 pandemic leading to a preference for privacy in travel.) In the short to medium term, the impact of autonomous driving on travel structure is likely to be: ① Private cars & ride-hailing continue to encroach on the share of public transportation, ② Ride-hailing accelerates the replacement of human-driven taxis. ③ However, due to the significant benefits of autonomous driving technology for private cars and ride-hailing services, it is still difficult to say who will benefit more after the technology becomes widespread, and we do not attempt to make a judgment on this.

We believe that autonomous ride-hailing can replace public transportation for the following reasons:

First, according to research, the two most common reasons people use ride-hailing services (instead of other modes of transportation) are: ① Ride-hailing is cheaper than taxis and private cars, ② Ride-hailing is more convenient than public transportation and private cars. In summary, there are two key points—affordable prices & greater convenience.

As autonomous driving becomes more widespread, ride-hailing services are expected to not only be more convenient than public transportation but also have operating costs that are close to those of public transportation. According to ARK's estimates, once autonomous driving technology matures and scales up, the operating cost of driverless ride-hailing services can be reduced to about $0.25 per mile (our calculations yield a similar figure, but it is important to note that this number only considers costs and does not account for the profit margin of the operators), which is nearly indistinguishable from the average price of $0.22 to $0.23 per mile for subways and buses.

4. From a quantitative perspective, how much incremental market space can autonomous driving technology bring to the ride-hailing industry?

① Incremental market space gained by eroding public transportation's share: Based on previous data, in the commuting scenario in the United States, the usage share of public transportation is around 4%. Considering that the usage rate of public transportation in other scenarios should be lower, we assume that the overall usage share of public transportation is about 3% (approximately 70% to 80% of 4%).

After the maturity of autonomous driving, we believe that it is feasible for private cars and ride-hailing services to capture about 50% of the current public transportation share. (However, due to congestion and other reasons, it is unlikely that autonomous vehicles will completely replace buses or subways.) We assume that 50% of the public transportation usage scenarios will be replaced by autonomous vehicles, with private cars and commercial vehicles capturing it in a 50%/50% ratio.

According to the calculations in the chart below, the usage scenarios taken from public transportation can enhance the current market size (by volume) of ride-hailing + taxi operations by 40% in incremental market space.

② Within the operating vehicle sector, ride-hailing continues to capture the share of taxis: According to data from official New York City departments, traditional taxis still hold about 20% of the market share between 2023 and 2024. According to domestic experience, the market share of taxis across the United States should be lower than that of New York City (many small cities may not have taxi operations, but the concept of ride-hailing operations may be higher). Considering that human-driven taxis are unlikely to be completely replaced, we estimate that after the popularization of autonomous driving technology, the share of ride-hailing in operating vehicles will increase from 80%+ to 95%+.**

In addition to capturing public transportation market share externally and continuing to replace traditional taxis internally, from a static perspective (not considering the natural growth of the industry), taking the United States as an example, autonomous driving technology may promote the market size of ride-hailing to increase by approximately 66% in terms of quantity.

II. In the era of autonomous driving, how will the competitive landscape and business model of ride-hailing change?

1. Different pricing = Different platform revenue

According to the previous analysis, autonomous driving technology is expected to increase the usage of the U.S. ride-hailing industry by about two-thirds, but the prerequisite is that ride-hailing pricing must significantly decrease compared to the current levels; therefore, a simple increase in volume does not necessarily mean an increase in the overall profit margin of the ride-hailing business model. The key question is, in the era of autonomous driving, how will the UE model of the ride-hailing business model change?

In simple terms, this is a trade-off between retaining more net income for the platform (more profit) and adopting lower prices to attract users (lower pricing). We provide a simplified UE model in the table below, which includes only four factors: labor costs (which can be replaced by autonomous driving technology), non-labor costs (depreciation, energy, and other costs that cannot be replaced by autonomous driving), platform retained earnings, and the price paid by end consumers.

Looking at the different pricing standards for autonomous ride-hailing under different scenarios, we can see how the retained income for ride-hailing platforms will change compared to the current situation:

① U.S. Market: According to ARK's estimate, the cost of Robotaxi (referring to autonomous ride-hailing) in a mature state is $0.16 per kilometer (equivalent to $0.25 per mile). If in the era of autonomous driving, the platform's net income (after deducting driver shares) remains at the current Uber level of about $0.35 per kilometer, the end pricing would be ($0.51 per kilometer), which is about 41% of the current ride-hailing price, indicating a considerable discount.

However, it is important to note that this pricing ($0.51) is still higher than the private car usage cost of $0.43 per kilometer and less than the public transportation cost of less than $0.25 per kilometer. Therefore, from another perspective, if we increase the pricing of autonomous ride-hailing by 30% based on public transportation costs, which would be $0.30 per kilometer (equivalent to 70% of the current private car cost), then the net income retained by the platform and operators would only be $0.14 per kilometer, which is about 40% of the current level. ② Chinese Market: According to estimates from Dolphin Research (also referencing other institutions), under fully mature technology conditions, the operating cost of domestic ride-hailing can be as low as 0.7 to 0.8 yuan per kilometer, approximately $0.1. The key assumptions behind this include that the cost of a typical Robotaxi drops to about 150,000 yuan, no safety personnel are required, and operational costs such as insurance and maintenance are about 20,000 yuan per vehicle per year (55 yuan per day).

Under the above assumptions, if Robotaxi maintains Didi's current platform net income of about 0.04 yuan per kilometer, the terminal pricing for Robotaxi would be $0.14 per kilometer, which is 40% of the current ride-hailing price and 61% of private car costs.

③ From the commonalities observed in the markets of China and the United States, after the technology matures and scales up operations, even if its terminal pricing is about 60% cheaper than the current ride-hailing pricing, the Robotaxi operators can maintain a per-unit income comparable to the current ride-hailing platforms, providing significant price attractiveness.

2. How will the current market structure change in the new era?

The above analysis views the ride-hailing industry as a whole. However, with the popularization of autonomous driving technology, it will inevitably introduce more industry participants (including but not limited to autonomous driving technology providers, operators of unmanned ride-hailing vehicles, etc.), significantly altering the currently relatively stable competitive landscape.

The primary influencing factor among these is how autonomous driving technology providers will position themselves when entering the ride-hailing industry, which can be roughly divided into the following scenarios:

① Autonomous driving technology is monopolized by a few oligarchs and is completely closed-source, such as Tesla and a few other car manufacturers/autonomous driving technology unicorns. While this scenario cannot be completely ruled out, Dolphin Research believes the likelihood is low. If this were to happen, there is a considerable chance that the ride-hailing industry could be monopolized by these technology oligarchs, and this article will not discuss this scenario further.

② Autonomous driving technology providers build their ride-hailing platforms and compete directly: Autonomous driving technology providers (such as currently leading companies like Tesla or Waymo) leverage their technological or hardware advantages to compete directly or exclusively with existing ride-hailing platforms by building their ride-hailing matching platforms or large-scale self-operated fleets (for example, not allowing their autonomous vehicles to join third-party ride-hailing platforms).

③ Car manufacturers or other Robotaxi providers establish cooperative relationships with ride-hailing platforms, avoiding direct competition: As autonomous driving technology becomes widespread, autonomous driving capacity enters the ride-hailing industry through various channels, including official cooperation with existing ride-hailing platforms, third-party operators purchasing (leasing) autonomous vehicles to join ride-hailing platforms, and some autonomous driving companies also attempting to build their platforms to serve consumers directly

Although it is difficult to assert how the market landscape of the ride-hailing industry will change in the era of autonomous driving, Dolphin Research speculates that the future will likely be dominated by collaborations between autonomous driving technology providers and existing platforms (Scenario ③), with autonomous driving technology providers building their platforms as a secondary option (Scenario ②).

In terms of pace, we believe that current leaders—Waymo and Tesla have the opportunity to leverage their first-mover advantage (Waymo) and sufficient consumer awareness (Tesla) to accumulate enough user recognition and traffic before autonomous ride-hailing becomes widespread, establishing the capacity for supply and user aggregation needed on both the supply and demand sides of the closed-loop ride-hailing business model, thereby creating a new platform that can operate independently. However, later autonomous driving unicorns will likely enter the ride-hailing industry primarily as capacity providers, needing to collaborate with existing ride-hailing platforms that have aggregation capabilities.

Depending on the different positioning of new entrants, the impact on existing ride-hailing platforms like Uber will manifest in two aspects:

① Firstly, simply and directly, unicorns or car manufacturers that adopt an independent operation model will directly compete for consumer sources and market share, affecting the market share of existing ride-hailing platforms.

② As autonomous ride-hailing replaces individual drivers, there may likely emerge corporate-operated autonomous vehicle fleets. The upstream capacity providers will shift from independent and dispersed individual drivers to scaled autonomous ride-hailing fleets, which will weaken the bargaining power of ride-hailing platforms over upstream providers, potentially reducing the share of profits that platforms retain in the ride-hailing business. In other words, this will affect the average revenue and profits retained by ride-hailing platforms.

Logically, the more developers of autonomous driving technology there are in the future, the less significant the technological gap, and the lack of a clear industry leader, the smaller the impact on existing ride-hailing platforms like Uber will be.

3. How much impact will "newcomers" in ride-hailing have on "oldcomers"?

This section will explore the two perspectives provided at the end of the previous paragraph: ① Can leading autonomous driving unicorns capture a significant market share from current ride-hailing leaders? ② What impact will the entry of autonomous driving capacity into the market have on platform profitability?

1. The road to developing and operating autonomous vehicles is not easy

Firstly, from the perspective of autonomous driving developers operating independent ride-hailing platforms, although there are quite several companies currently developing autonomous driving technology independently (mainly domestic car manufacturers, while overseas it is primarily third-party unicorn organizations), a considerable portion of their development journeys have not been smooth, and there are very few that can currently provide autonomous ride-hailing services to the public. Specifically, among the leading autonomous driving technology developers in the European and American markets (excluding Tesla), only Waymo and Zoox have achieved results in the operation of unmanned ride-hailing services, with the former gradually expanding its operational scale and the latter only conducting small-scale pilot projects. Meanwhile, Cruise, Motional, and Aurora have generally suspended or terminated their unmanned ride-hailing operations, either reducing expenditures and returning to a pure technology research and development focus, or shifting their emphasis from passenger ride-hailing to the development of unmanned truck technology for goods transportation. Major companies like Apple and Uber that have developed their autonomous vehicle projects have also failed and been cut.

It is evident that perhaps due to the enormous capital investment required for independently operating ride-hailing platforms and fleets, independent ride-hailing operations have not been a common choice for autonomous driving developers so far (which aligns with our view). Therefore, in the following text, we will focus on Waymo to observe the current situation of unmanned ride-hailing operations.

2. The lone Waymo adopts a dual approach of 1P/3P

The following chart briefly outlines Waymo's development history since its establishment in 2009 as a Google autonomous driving project department, its first public unmanned ride-hailing service launch in Phoenix in 2020, and its expansion to provide public services in four markets to date, which we will not elaborate on.

What we are more concerned about is that Waymo itself is exploring and testing different operational models. It can be seen that based on the different combinations of who bears the responsibilities of the "platform party (responsible for customer acquisition and order dispatch)" and the "fleet management party (responsible for capacity management and maintenance)," Waymo has explored four models, which include:

① A pure 1P model where both the platform and fleet are managed entirely by Waymo; ② A pure 3P model where customer acquisition and fleet management are entirely handled by Uber (Waymo only provides autonomous driving technology and vehicles); ③ A 1P/3P hybrid model where the fleet is managed by Waymo but can acquire customers from both its platform and Uber's platform; ④ A model where Waymo's platform acquires customers but the fleet is managed by a third party, Moove, similar to a light asset model like model ①.

Thus, even though Waymo has chosen to build its platform and operate independently, and is leading the industry in progress, it still chooses to collaborate with third-party platforms or fleet management parties. Therefore, we believe that even after the widespread adoption of unmanned ride-hailing, it is highly likely that a 1P/3P hybrid operational model will still be adopted.

3. Rapidly Growing Waymo is Not Far from Uber/Lyft

So what is Waymo's current operational status and scale? To summarize, in terms of operational scope, Waymo mainly operates in the four regions listed in the table above; in terms of fleet size, according to news reports, Waymo currently operates only a few hundred autonomous ride-hailing vehicles (possibly around 700 to 1,000 vehicles), while in terms of order volume, it is reported that by the end of March 2025, Waymo's total order volume in the four operational regions has reached 200,000 orders per week.

Although its absolute scale still has a significant gap compared to the daily order volume of several hundred thousand for Uber and Lyft in California, when considering the limited number of operational vehicles and cities, the operational efficiency of autonomous ride-hailing vehicles may not show a significant difference compared to human-driven ride-hailing vehicles like Uber and Lyft. From the current situation, as long as autonomous ride-hailing vehicles expand their fleet size and operational market, there is a considerable probability of reaching a scale comparable to those of leading companies like Uber and Lyft.

According to official data from California, by the end of 2024, the average number of orders per autonomous vehicle per day in California has approached 24. Assuming each order takes about 30 minutes (which may be on the shorter side), plus an estimated 20% to 30% idle waiting time, it means that the "effective" operating time of autonomous ride-hailing vehicles in California has reached 15 hours per day. Additionally, news reports indicate that human drivers working long hours only complete about 25 to 30 orders a day. This shows that the utilization rate of autonomous ride-hailing vehicles deployed in California is quite high, and the local demand for autonomous ride-hailing services can be said to be relatively strong (at least under the current supply conditions).

Moreover, according to research, the strong demand for autonomous ride-hailing vehicles in California is not based on significant price discounts. As shown in the figure below, Waymo's per-mile usage price in the Los Angeles area is about $6 (which is about $3.5 per kilometer), which is comparable to Lyft's standard pricing and only about 10% lower than Uber's standard pricing. This indicates that without a significant price advantage, autonomous ride-hailing vehicles in California already possess effective customer acquisition capabilities (not fully relying on third-party platforms like Uber for customer acquisition).

According to Yipit data, by the end of 2024, Waymo's market share in the ride-hailing market in San Francisco (based on order volume) has caught up with Lyft, with a market share slightly above 20%. Correspondingly, the market shares of Uber and Lyft have both decreased by about 10% from their peaks in 2023. It can be seen that at least in the San Francisco area, Waymo has already created significant competition for existing ride-hailing platforms and has reached a comparable scale.

Therefore, under the assumption of future technological development, the user experience of autonomous ride-hailing will be fully on par with, or even superior to, that of human-driven ride-hailing. We believe that it is possible to subsequently develop one (or two to three) autonomous ride-hailing platforms that can achieve a market share comparable to current ride-hailing platforms. At the same time, based on the premise that autonomous driving technology will become an infrastructure rather than being monopolized by a few corporate platforms, existing ride-hailing platforms can also utilize autonomous driving capacity. Thus, the probability of new platforms completely disrupting existing leaders like Uber is also low.

4. Decline in platform bargaining power?

As mentioned at the beginning of this section, in the era of autonomous driving, in addition to the possibility of new platforms emerging to directly seize market share from existing ride-hailing platforms, the revenue share occupied by platforms that match demand and supply in the ride-hailing business model is likely to decline.

Logically, the current ride-hailing platforms have most of their upstream demand and downstream supply composed of dispersed and independent individual passengers or drivers. In this case, both upstream and downstream are "loose sand," and the platform naturally has the strongest bargaining power.

However, in the era of autonomous driving, as personal drivers are replaced as supply, there is a higher likelihood of bulk purchasing or leasing autonomous vehicles to participate in supply-demand matching in the form of fleets. In this case, due to the increased concentration of the supply side, and as we deduce, it is likely that several new platforms will emerge in the market. Therefore, in the era of autonomous driving, in the revenue distribution remaining from "user payment price - vehicle operating cost," the share occupied by pure platform roles may be lower than in the current human-driven era. Meanwhile, the vehicle operating parties (currently individual drivers, but more likely to be enterprises in the future) may see a decrease in absolute revenue (thus both pricing and costs have decreased), but the proportion of revenue allocated to them may increase.

Of course, in this case, platform parties will likely directly intervene in the operation and management of fleets to gain more revenue and bargaining power, at the cost of making the platform's business model heavier. This will not be discussed further.

Fourth, where is Uber's safety price in the era of autonomous driving?

Based on the qualitative and quantitative discussion above regarding the impact of autonomous driving technology on the ride-hailing business, we will explore the final question—does Uber's current pricing offer value for money?

1. Current valuation cannot be considered cheap. First, from a static perspective, that is, without considering the impact of autonomous ride-hailing cars that may only have a significant effect in 2 to 3 years, we will only look at the profit expectations for the next one or two years; at the same time, we will not use Non-GAAP metrics or adjusted EBITDA, which are somewhat "modified" indicators, as the basis for valuation; instead, we will revert to the most straightforward but also the most referential GAAP net profit valuation.

According to the calculations by Dolphin Research, the net profit forecasts for Uber in 2025 and 2026 are $6 billion and $8.2 billion, respectively, corresponding to a recent total market capitalization of approximately $137.3 billion (stock price of $65.6), with 2025e PE and 2026e PE being 23x and 17x, respectively.

Purely looking at the valuation level, this generally belongs to a relatively mature company that still possesses certain competitive advantages and barriers, which is viewed neutrally by the market. That is, the price range of $60 to $65 roughly corresponds to a valuation that has squeezed out optimistic sentiment but does not have obvious cost-effectiveness. Moreover, a PE valuation of 17x to 23x generally corresponds to market expectations for subsequent profit growth rates of about 15% to 20%. In other words, the current price does not significantly account for the potential impacts—positive or negative—of autonomous driving technology on performance.

In summary, since we cannot yet clearly see the impact of autonomous driving, performance forecasts will still extrapolate based on current trends, but the valuation is squeezed to a relatively neutral price, avoiding "high-position standing" to adapt as technology evolves.

2. How to price the impact of autonomous driving?

Estimating the value of Uber in the era of autonomous driving is a question that currently cannot be answered precisely, to the extent that the market has given up trying to solve it (giving up may be a rational choice). However, as the value of this article, and to provide a rough reference for everyone, Dolphin Research will also offer a thought process for answering this question. It should be noted that the following calculations are less about predicting what will happen in the future and more about providing logically coherent and somewhat conservative assumptions to observe where the company's safe valuation should be under these assumptions.

First, our prediction period starts from 2027 to 2031, assuming that the impact of autonomous driving on the ride-hailing industry will be gradually fully released within these five years.

So, the first step in solving the problem—what impact will autonomous driving have on Uber's ride-hailing order volume? Based on the analysis above, we make the following assumptions:

① In the era of autonomous driving, ride-hailing will capture all of the taxi market and half of the public transportation market, and under the condition that autonomous ride-hailing and autonomous private cars do not encroach on each other, the ride-hailing market is expected to gain a maximum of 66% incremental order volume.

However, the prerequisite for this situation is that the pricing of autonomous ride-hailing must be close to the cost of using public transportation. Although this pricing can theoretically be achieved (due to the extremely low operating costs of autonomous vehicles), the profit margin left for operators will be relatively limited. Considering this, we account for the positive effect to reach a maximum of 33% by 2031 ② In the era of autonomous driving, the ride-hailing market will see the emergence of two new autonomous ride-hailing platforms from the currently prevalent dual oligopoly model. Although current experiences suggest that C2C business models like ride-hailing, which have low economies of scale, can generally only support two players, the reduction in vehicle operating costs brought about by autonomous driving, along with a shift from C2C to B2C to some extent (where the capacity provider may shift from individual drivers to corporate fleet managers), makes it possible for the market to support 3 to 5 players.

Moreover, the market share pattern will change from the current Uber vs. Lyft situation of 70%: 30% to something like 50%: 20%: 15%: 15%, or 40%: 30%: 15%: 15%. Therefore, Uber's market share (which is likely to remain the lowest in the industry) will be approximately 50% to 70% of the current level. Taking the average, we assume that by 2031, the market share will be 60% without the impact of autonomous driving.

Considering the above two points, we estimate that under the influence of autonomous driving, Uber's ride-hailing order volume in 2031 will be 80% of the previously predicted figure.

The second step in solving the problem—How will Uber's average revenue/profit per ride-hailing service change in the era of autonomous driving? This question is likely more difficult to answer than the order volume. It involves two sub-questions: How much will ride-hailing pricing decrease compared to the current level in the era of autonomous driving? Based on the new pricing, what will be the net revenue that the platform can retain?

① Although the actual pricing of autonomous ride-hailing is difficult to predict, we can conclude from previous analyses that: ideally, autonomous ride-hailing can reduce terminal pricing by 60% while keeping the net income of the operators unchanged; and in the era of autonomous driving, the revenue share allocated to vehicle operators by the platform may increase compared to the current level, meaning the proportion retained by the platform itself may decrease.

Therefore, for conservative considerations, although the pricing of autonomous ride-hailing may not necessarily need to be about 60% lower than the current level, we still assume it will be priced this way, meaning that after excluding vehicle operating costs, the average retained income for operators (including the platform and fleet managers) will remain consistent with the current level. Furthermore, we assume that the platform will need to allocate 20% of the retained income to fleet managers, changing from the current 100% retention. (In this case, the platform does not directly participate in fleet operations, which may not align with reality).

Assuming that Uber's average revenue gradually decreases by 20% during the forecast period, while Uber's average expenditure (referring to marketing, customer service, and management) theoretically will not directly decrease due to the impact of autonomous driving, we only assume a 10% reduction compared to the original expected value during the forecast period. Thus, under the aforementioned conservative driving assumptions, Uber's average profit (represented by adj. EBITDA) in the era of autonomous driving may decrease by approximately 40% After accounting for the above impacts, Uber's adjusted EBITDA for 2031 will be only about 46% of the original forecast.

In terms of the final valuation, ① For the food delivery business, we still value it based on the current profit expectations for 2026, giving 18x PE based on the adjusted EBITDA for 2026 after deducting equity incentives, amortization, depreciation, and taxes. Although the market currently does not believe that autonomous driving will directly affect the food delivery business, we consider the weakening of the ride-hailing driving effect and calculate the final valuation at 90%.

② As for the ride-hailing business, we adjust the calculated adjusted EBITDA for 2031 after fully releasing the impact of autonomous driving to net profit and apply a 15x PE based on mature steady-state operations, discounted back to 2026 using WACC.

Some companies have net cash and short-term investments that do not exceed their liabilities, so net cash is not counted. After summing the above-distributed valuations, the calculated safe price for Uber, affected by autonomous driving, is $47.3 per share, which represents a potential decline of about 20% compared to the previous low of $60. Although the actual development path of autonomous ride-hailing may differ significantly from our assumptions, this price can serve as a signal for bottom-fishing in a pessimistic scenario.