Everyone Wanted a Cheaper Tesla. Elon Musk Bet on Cybercab Instead: Why Autonomy Could Define Tesla’s Next Growth Era

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Zion Zhao Real Estate | 88844623 | 狮家社小赵 | wa.me/6588844623 |  https://linktr.ee/zionzhao

This post is for general information, education, and market literacy only. It does not constitute financial, investment, trading, legal, tax, accounting, or other professional advice, and is not an offer, solicitation, recommendation, or endorsement. Views expressed are personal, general in nature, and subject to change without notice. While reasonable care is taken, no representation or warranty is given as to accuracy, completeness, or reliability. Readers should conduct independent due diligence and seek professional advice. To the fullest extent permitted by law, no liability is accepted for any loss arising from reliance on this material.  

Tesla’s Missing Affordable Car May Explain Everything: The Cybercab Bet, Autonomous Mobility and the Next Phase of Growth

Everyone Wanted a Cheaper Tesla. Elon Had Other Plans: Why Cybercab May Be the Bridge to Tesla’s Next Growth Era

For years, the next step in Tesla’s growth story looked almost painfully obvious.

Build a smaller Tesla. Make it cheaper than the Model 3 and Model Y. Give it a steering wheel, pedals and Full Self-Driving as an option. Sell it globally in enormous volumes.

That was the vehicle many investors, customers and industry observers expected. It seemed like the natural successor to the Model 3 and Model Y, and the most straightforward route toward Tesla’s historical ambition of producing automobiles at a scale measured in many millions of units annually.

Instead, Elon Musk appears to have made a very different wager.

Tesla increasingly concentrated its strategic narrative around Full Self-Driving, Robotaxi and Cybercab, a purpose-built autonomous vehicle without conventional driver controls. The obvious affordable conventional Tesla did not arrive in the form many expected.

At first glance, that decision looks difficult to defend. Tesla’s vehicle growth slowed materially after 2023. Global electric vehicle competition intensified. Chinese manufacturers expanded aggressively. Tesla’s existing portfolio aged. Cybertruck failed to produce another Model Y-sized volume wave. A cheaper mass-market Tesla could potentially have filled that gap.

Yet there is another interpretation.

Tesla may not have abandoned the pursuit of affordable, high-volume transportation. It may have decided that the next generation of affordable vehicles should be designed around autonomy from the beginning, rather than around a human driver whose controls might eventually become redundant.

If that interpretation is correct, Cybercab is not merely a robotaxi.

It is potentially the first production experiment for a new vehicle architecture.

That distinction could determine whether Tesla’s recent slowdown becomes remembered as a strategic failure or as the painful transition between two eras of the company.

Tesla’s Growth Problem Was Real

The numbers explain why the missing affordable Tesla became so controversial.

Tesla delivered approximately 1.81 million vehicles in 2023. Deliveries then declined to approximately 1.79 million in 2024 and 1.64 million in 2025. Automotive revenue also weakened during this period, exposing how dependent Tesla remained on vehicle volume despite the growing contributions of energy storage, services and software (Tesla, Inc., 2024, 2025a, 2026a, 2026b).

The broader company remained substantial, but the extraordinary growth trajectory investors had associated with Tesla was interrupted.

That mattered because Tesla had previously framed its future around enormous manufacturing scale. Its 2020 Impact Report articulated an aspiration to sell 20 million electric vehicles annually by 2030, while subsequent corporate presentations emphasized next-generation manufacturing, lower costs and broader affordability (Tesla, Inc., 2021, 2023).

The next mass-market product therefore seemed essential.

Instead, Tesla ultimately introduced lower-priced Model 3 and Model Y Standard variants and expanded the Model Y family, including the longer Model Y L in China. These moves improved affordability and widened customer choice, but they did not constitute the clean-sheet compact Tesla that many expected.

The market did not stand still while Tesla made that choice.

According to the International Energy Agency, global electric car sales exceeded 20 million units in 2025, representing roughly one-quarter of new cars sold worldwide. China alone accounted for more than 13 million electric car sales, while nearly 1,000 electric car models were available globally. Chinese manufacturers represented more than half of worldwide battery electric vehicle sales (International Energy Agency [IEA], 2026).

Tesla therefore sacrificed something tangible by not rushing a conventional affordable model into the market.

Every year without such a vehicle gave competitors more time to scale, improve their products, strengthen brands, deepen supplier relationships and occupy lower price segments.

That opportunity cost should not be minimized.

What We Know About the Missing Affordable Tesla

The history of Tesla’s lower-cost vehicle requires careful fact-checking.

Reuters reported in April 2024 that Tesla had canceled a planned inexpensive vehicle and shifted resources toward robotaxi development. The reporting cited people familiar with Tesla’s plans and internal company communications. Elon Musk publicly disputed the report, although he did not provide a detailed public account of which elements he considered incorrect (Jin et al., 2024).

What cannot be responsibly claimed is that the public knows every detail of Tesla’s internal debate.

There is no verified evidence establishing that Tesla possessed a fully finalized smaller Model Y prototype, that most executives wanted to build it, or that Musk personally overruled a formally agreed management decision. Those details remain interpretation.

Tesla’s more recent disclosures are also more nuanced than the claim that it abandoned consumer vehicles.

In its 2026 filings, Tesla continued to describe its next phase of growth as being driven by advances in autonomy and the introduction of new products, including products based on its next-generation platform. It continued to emphasize affordability, manufacturing cost reduction and expansion of the product roadmap (Tesla, Inc., 2026e).

That suggests the fundamental question is not whether Tesla chose cars or robotaxis.

The more important question is sequencing.

Did Tesla decide that it needed to validate autonomy and next-generation manufacturing first, then build additional vehicles around that architecture?

That is the strategic thesis worth examining.

The Choice Was Not Simply Between Two Cars

Consider the difference between two hypothetical products.

The first is a conventional affordable Tesla. It is smaller and cheaper than a Model Y, but fundamentally familiar. It has a steering wheel, pedals, mirrors, driver-oriented safety systems and conventional controls. It can support advanced driver assistance, but a human remains responsible.

The second is Cybercab.

Cybercab begins from the assumption that there is no human driver.

That changes the design brief.

A conventional affordable Tesla asks how cheaply Tesla can manufacture a modern electric car.

Cybercab asks what a car should become when nobody needs to drive it.

These are not merely two price points. They are two different architectural philosophies.

The first optimizes the existing automobile.

The second attempts to redefine it.

That may explain why Musk could have considered a conventional bridge vehicle strategically distracting even if it would have been financially attractive.

If Tesla believes highly capable autonomous driving is inevitable and sufficiently close, building a new high-volume vehicle around human controls could appear like investing heavily in yesterday’s architecture immediately before the transition to tomorrow’s.

That is a radical assumption.

It may also be wrong.

But the logic is coherent.

Removing the Steering Wheel Does Not Simply Remove Complexity

One of the more seductive arguments around Cybercab is that removing driver controls makes the vehicle dramatically simpler.

There is some truth to that.

A conventional car requires a steering system, pedals, driver interfaces, visibility considerations, mirrors and various safety systems built around a human operator. Eliminating those requirements can create opportunities to redesign the cabin, simplify components and optimize manufacturing.

However, complexity does not disappear.

It migrates.

The human driver in a conventional vehicle is also the ultimate fallback system. If automation encounters a situation it cannot handle, the human can intervene.

Once the human disappears, the autonomous system has to deal with the entire driving task.

Software, computing hardware, sensors, braking, electrical architecture, redundancy, remote operations, communications and fleet systems become part of a safety-critical machine that must perform reliably without a human supervisor.

This is why Tesla itself distinguishes FSD (Supervised) from a true driverless robotaxi. Tesla states that FSD (Supervised) requires active driver supervision and does not make a vehicle autonomous (Tesla, Inc., 2025b).

Cybercab is fundamentally different.

It cannot simply ask a driver to take control.

The system itself has to solve the problem.

The Long Tail Is the Real Autonomy Problem

Most driving is relatively mundane.

The difficult part lies in rare situations.

Construction zones, emergency vehicles, damaged infrastructure, extreme weather, unusual pedestrian behavior, temporary road layouts, human-directed traffic, unexpected objects and ambiguous signage may individually be uncommon, but collectively they create the long tail of autonomous driving.

That makes proving safety exceptionally difficult.

Kalra and Paddock (2016) demonstrated that because serious and fatal road accidents are relatively rare, using real-world mileage alone to statistically prove autonomous vehicles safer than human drivers could require extraordinarily large driving distances. Their conclusion was not that autonomous vehicles cannot be safe, but that simulation, scenario testing, engineering validation and other methods must supplement raw mileage.

There is also evidence that properly constrained autonomous systems can perform strongly.

Kusano et al. (2024) examined millions of rider-only Waymo miles and found lower police-reported and injury-reported crash rates compared with selected human-driving benchmarks. The findings are important, but they do not prove Tesla’s safety because Waymo and Tesla use different technologies, vehicles, operating domains and deployment strategies.

The relevant lesson is that autonomous mobility has moved beyond science fiction.

It can increasingly be measured scientifically.

Tesla now has to produce its own evidence.

Cybercab Has Crossed an Important Line

This is where the story became materially more interesting in 2026.

Cybercab is no longer merely a concept displayed on stage.

Tesla began Cybercab production and expanded Robotaxi operations. In September 2026, members of the public began riding in purpose-built Cybercabs in limited parts of Austin. Reuters reported that Texas records listed dozens of Cybercabs among Tesla’s broader autonomous vehicle fleet in the state (Kirkham et al., 2026).

That is a significant milestone.

A physical vehicle without traditional driver controls is carrying real passengers on public roads.

But deployment should not be confused with proof of generalized autonomy.

The service remains constrained. Geographic limits matter. Software maturity matters. Fleet size matters. Weather matters. Regulatory permissions matter. Operational support matters.

The real significance of the Austin deployment is that Tesla can now validate software, hardware, manufacturing and fleet operations simultaneously.

Every commercial trip can expose new failure modes.

Every production vehicle can reveal manufacturing problems.

Every maintenance event provides durability information.

Every intervention provides data about where the autonomy stack still struggles.

Tesla is therefore no longer merely promising the architecture.

It is beginning to test it under real operating conditions.

Regulation Is Now Part of the Engineering Challenge

Cybercab also illustrates something often underestimated in technology commentary.

A vehicle can be technically impressive and still face legal barriers.

Automotive regulation developed around the assumption that cars have human drivers. Steering controls, mirrors, pedals, visibility standards and other requirements are embedded in decades of regulation.

The United States has already begun modernizing some standards for vehicles without traditional controls. In 2022, the National Highway Traffic Safety Administration amended certain occupant-protection standards to address automated vehicles designed without conventional driving controls (NHTSA, 2022).

Cybercab has now pushed further into that boundary.

On September 4, 2026, NHTSA announced an Audit Query into Tesla’s self-certification of Cybercab’s compliance with applicable Federal Motor Vehicle Safety Standards. The agency said it would examine the technical data and processes Tesla used to certify a vehicle without traditional human controls and Tesla’s interpretation of which standards applied (NHTSA, 2026).

This does not mean Cybercab will fail.

It means regulation has become part of product development.

Tesla is simultaneously building the vehicle, operating the service, accumulating evidence and testing the legal architecture.

That makes the real development process far less sequential than a simple six-step roadmap suggests.

Software development, manufacturing, deployment and regulation are interacting in real time.

Why Musk May Have Preferred an All-In Bet

The organizational logic behind Tesla’s strategy deserves attention.

Management research has long studied the tension between exploiting successful businesses and exploring new ones.

March (1991) described this as the balance between exploitation and exploration. Exploitation focuses on improving known products, processes and businesses. Exploration involves experimentation, uncertainty and the development of future capabilities.

Tesla could have exploited its existing architecture.

It could have produced a smaller Model Y, improved batteries, reduced costs, expanded financing and sold additional conventional vehicles globally.

Instead, Cybercab represents a more radical exploratory effort.

One interpretation is that Musk believed splitting Tesla’s engineering resources between a conventional new high-volume platform and a purpose-built autonomous platform would reduce urgency.

A backup plan can reduce existential pressure.

If Cybercab were only one of several equal programs, delays might have been tolerable.

If Cybercab were central to Tesla’s future, delays would become organizationally unacceptable.

There is some strategic logic here. Startups often gain advantage through extreme focus because a single technical objective dominates the company.

But this argument should not become mythology.

Focus does not guarantee success.

O’Reilly and Tushman’s work on organizational ambidexterity shows that companies can sometimes exploit existing businesses while simultaneously exploring disruptive new ones (O’Reilly & Tushman, 2013).

Tesla may have been capable of building both products.

A conventional affordable vehicle might have financed autonomy, defended market share and reduced the consequences of software delays.

The claim that Tesla had no choice but to burn the metaphorical lifeboat is therefore not established.

The decision only looks brilliant if autonomy was sufficiently close to commercial readiness.

If autonomy was ten years away, foregoing a conventional volume platform would be much harder to justify.

Timing is everything.

Cybertruck Did Not Solve the Volume Problem

Cybertruck also demonstrates the importance of separating innovation from scale.

Tesla built a remarkable and unconventional vehicle, but Cybertruck did not generate the next global Model Y-sized growth wave.

Tesla reports Cybertruck together with Model S, Model X and other lower-volume vehicles rather than publishing standalone delivery figures. For 2025, Tesla delivered only 50,850 vehicles across its combined “Other Models” category. Tesla had also listed annual installed Cybertruck manufacturing capacity above 125,000 vehicles, materially below the scale of its Model 3 and Model Y operations (Tesla, Inc., 2025b, 2026a).

Whatever one thinks about Cybertruck as a product, it did not fill Tesla’s high-volume gap.

That made Cybercab increasingly important.

The Hidden Prize May Be Manufacturing

Autonomy receives most of the attention because it is more dramatic.

Manufacturing may be just as important.

Tesla has tied Cybercab to its proposed “unboxed” manufacturing process. Instead of assembling almost the entire vehicle sequentially through a conventional line, large sections can be produced in parallel and later joined together. Tesla argues that this could reduce production time, factory floor space and cost (Tesla, Inc., 2025c).

If it works, the real breakthrough may not simply be a cheap Cybercab.

It may be a cheaper way of building vehicles.

That matters because Tesla’s earlier growth was not driven only by desirable products. It was driven by Tesla’s ability to industrialize them.

A successful manufacturing architecture could eventually be applied to other products.

This is where the Cybercab-first thesis becomes far more compelling.

Tesla may be using one vehicle to validate several technologies simultaneously: autonomous software, next-generation manufacturing, fleet operations and new vehicle architecture.

If all of them work, Tesla gains more than one product.

It gains a platform.

Cybercab Could Be the Beginning of a Family

This is the strongest long-term interpretation.

Assume Tesla proves the autonomous driving system.

Assume the vehicle meets regulatory requirements.

Assume unboxed manufacturing works.

Assume fleet economics become attractive.

Tesla would then possess a validated architecture that could theoretically be adapted to other vehicles.

The company could build larger passenger vehicles, family crossovers, autonomous shuttles, delivery products and other mobility formats around the same core systems.

Tesla’s own 2026 filings are consistent with this possibility. The company continues to state that future production growth will involve autonomy and new products using next-generation technology (Tesla, Inc., 2026e).

That does not confirm a secret pipeline of autonomous SUVs and sedans.

It simply means Cybercab and future consumer products do not need to be mutually exclusive.

Cybercab could be the first expression of a broader architecture.

But Fleet Success Does Not Guarantee Consumer Success

There is an important complication.

The ideal robotaxi is not necessarily the ideal privately owned vehicle.

Cybercab has two seats. That makes sense if Tesla optimizes for many urban journeys involving one or two passengers. Smaller vehicles can potentially use fewer materials, consume less energy and cost less to build.

But families often need four or five seats, luggage space and flexibility.

A Tesla-operated fleet also gives the company enormous control.

Tesla can determine where the vehicles operate, how they are maintained, when software is updated, how sensors are cleaned and which environmental conditions are acceptable.

Private ownership introduces variability.

Owners might neglect maintenance. Sensors could become obstructed. Vehicles might travel into unsupported areas or difficult weather. Insurance and liability structures would become more complex.

Who bears responsibility when a privately owned autonomous vehicle crashes?

The vehicle owner?

Tesla?

The software developer?

The insurer?

A maintenance provider?

Those questions are unresolved at scale.

Cybercab could therefore succeed as a commercial fleet vehicle without immediately becoming a mass-market consumer product.

A broader consumer lineup may require derivatives designed around different use cases.

The Bigger Economic Bet Is Cost Per Passenger Mile

The most disruptive element of autonomy may not be the sticker price.

It may be transportation economics.

Traditional automakers largely make money when a vehicle is sold.

An autonomous fleet can potentially generate revenue repeatedly over the vehicle’s life.

That changes the metric from price per automobile to cost per useful passenger mile.

But the economics cannot be evaluated using driver elimination alone.

Analysts ultimately need to know utilization, paid miles, empty miles, electricity costs, charging downtime, maintenance, insurance, cleaning, tires, depreciation, remote assistance and vehicle lifespan.

A cheap robotaxi with poor utilization can still be a bad business.

A more expensive autonomous vehicle with exceptional utilization can potentially produce superior economics.

That is why Tesla’s real Robotaxi business will eventually have to be judged using operating data, not presentation-day assumptions.

The Bull Case: Tesla Is Changing the Unit of Competition

If Tesla succeeds, the company may stop competing solely on range, price, acceleration and vehicle design.

The competitive metric could increasingly become cost per mile of transportation delivered.

That would expand Tesla’s addressable opportunity beyond conventional automobile sales.

Tesla could potentially compete with taxis, ride-hailing, rental cars, privately owned vehicles and portions of public transportation.

The automobile would become a revenue-producing physical asset controlled by software.

A successful Cybercab network could also create reinforcing loops.

More vehicles generate more real-world data. Better data improves software. Better software expands operating territory. Broader territory improves customer utility. Greater demand improves vehicle utilization. Higher utilization improves economics. Better economics support additional deployment.

That is the optimistic case.

It could be extraordinarily powerful.

The Bear Case: Tesla Gave Up a Proven Opportunity for an Unproven One

The strongest criticism is equally straightforward.

Tesla already knew how to build electric cars.

It had enormous factories, global brand recognition, a charging ecosystem and one of the world’s most successful electric crossovers.

A lower-cost conventional vehicle represented a far more understandable opportunity.

Instead, Tesla accepted the risk of autonomy, regulation and new manufacturing simultaneously.

Meanwhile, the EV market expanded without it.

If autonomy takes significantly longer than Tesla expects, the company may have sacrificed valuable years in an increasingly competitive market.

The Cybercab bet therefore cannot be evaluated against doing nothing.

It must be evaluated against the vehicle Tesla could have built instead.

That opportunity cost is enormous.

Another Risk: Successful Robotaxis Could Reduce Vehicle Ownership

There is also a deeper strategic paradox.

If autonomous ride-hailing becomes extremely efficient, consumers may need fewer privately owned vehicles.

A highly utilized robotaxi can theoretically replace several low-utilization privately owned cars.

That could be excellent for a dominant fleet operator while reducing the total number of vehicles society needs.

Tesla’s old ambition of selling tens of millions of vehicles annually therefore does not necessarily align perfectly with a future built around shared autonomous transportation.

The relevant metric may shift from vehicles sold to transportation services delivered.

Tesla’s strategic identity could change accordingly.

That is one reason the old 20-million-vehicles narrative should not simply be treated as a current forecast.

The company’s more recent disclosures emphasize autonomy, AI, Robotaxi deployment, new products and services rather than repeatedly anchoring investors to that earlier annual target.

Capital Intensity Is Also Rising

Autonomy is often described as a software business, but Tesla’s current transition is extraordinarily capital-intensive.

Tesla reported $8.28 billion in capital expenditure during the first half of 2026 and said full-year capital expenditure could exceed $25 billion. Investments include AI computing infrastructure, data centers, manufacturing, robotics, charging, semiconductor initiatives and fleet assets (Tesla, Inc., 2026e).

Second-quarter 2026 revenue grew strongly to $28.24 billion, but operating income fell to $398 million as Tesla increased spending on AI, software and future capacity.

That financial picture captures the strategic bet.

Tesla is generating more revenue again, but it is spending heavily to construct its next technology stack.

This is not a low-risk transition.

The Six Gates That Actually Matter

Rather than treating Tesla’s roadmap as six perfectly sequential steps, I would evaluate the strategy through six overlapping gates.

First, Tesla must prove that autonomous, rider-centric transportation is important enough to justify redesigning the automobile around it.

Second, the software, computing hardware, vehicle systems and manufacturing architecture must work together reliably.

Third, Tesla must prove safety and service quality in progressively more difficult real-world operating environments.

Fourth, regulators must accept the technology across sufficiently large markets.

Fifth, the economics must work after including the full costs of ownership and fleet operation.

Finally, Tesla must demonstrate that Cybercab’s architecture can expand beyond a limited two-seat urban robotaxi into products and services capable of supporting genuinely enormous scale.

Tesla is already working across several of these gates simultaneously.

None has been fully conquered.

What Investors and Industry Observers Should Watch

The most useful questions are now empirical.

Can Cybercab production scale without manufacturing problems?

Does unboxed manufacturing materially reduce capital requirements and unit costs?

How quickly can Tesla expand autonomous territory?

How often do vehicles require remote intervention?

What happens to safety performance as operating domains become more complex?

How does NHTSA’s Cybercab inquiry conclude?

What are the true fleet economics after charging, maintenance, insurance and empty mileage?

Will Tesla sell autonomous vehicles directly to consumers?

Will privately owned Teslas eventually participate in the Robotaxi network?

Most importantly, does Tesla unveil additional vehicles derived from Cybercab’s architecture?

Those questions will determine whether the strategy works.

Debating whether Elon Musk is simply a genius or simply reckless tells us very little.

Conclusion: The Cheap Tesla May Not Be Missing. It May Be Being Redefined.

Everyone expected Tesla to build the obvious product.

A smaller vehicle. A lower price. A steering wheel. Pedals. Familiar ownership. Millions of units.

That would have been the safer path.

It might even have been the better one.

Instead, Tesla increasingly placed its strategic emphasis on autonomy, Robotaxi and Cybercab.

The short-term cost was real.

Vehicle deliveries weakened after 2023. Automotive revenue declined. Competition intensified. Cybertruck did not create another mass-market growth cycle. The conventional inexpensive Tesla many expected did not arrive.

But Cybercab has now crossed from concept into production and limited public service.

Tesla is testing autonomous software, purpose-built hardware, fleet operations and new manufacturing methods simultaneously. Regulators are now engaging directly with the novel questions created by vehicles without traditional controls.

That makes the strategy increasingly testable.

The central question is therefore no longer simply, “Where is Tesla’s cheap car?”

It is this:

Is Cybercab the first production platform from which Tesla intends to build its next generation of affordable vehicles?

If the answer is yes, the recent product gap begins to make more strategic sense.

Tesla may not have abandoned high-volume automobiles. It may have delayed the conventional route because Musk believed the company first needed to solve the architecture that comes after human driving.

That is an extraordinarily risky decision.

If autonomy matures too slowly, regulation becomes restrictive, fleet economics disappoint or manufacturing fails to scale, Tesla may discover that it sacrificed a highly valuable conventional growth opportunity for a future that arrived later than expected.

But if Tesla can make autonomous driving reliable, Cybercab manufacturable, regulators comfortable and fleet economics compelling, the company could possess something far more powerful than a single inexpensive car.

It could possess an entirely new transportation platform.

Five or ten years from now, Tesla’s decision may look either like one of the greatest acts of strategic concentration in modern automotive history or one of its most expensive opportunity costs.

The difference will not be determined by narrative.

It will be determined by execution.

And that is precisely why Cybercab matters.

It is not merely a bet on whether Tesla can build a robotaxi.

It is a bet on what the automobile becomes when driving is no longer the defining function of the automobile itself.

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References

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Jin, H., Shirouzu, N., & Klayman, B. (2024, April 5). Tesla scraps low-cost car plans amid fierce Chinese EV competition. Reuters.

Kalra, N., & Paddock, S. M. (2016). Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transportation Research Part A: Policy and Practice, 94, 182–193. https://doi.org/10.1016/j.tra.2016.09.010

Kirkham, C., Shirouzu, N., & Roy, A. (2026, September 3). Tesla starts Cybercab rides in Austin, drawing U.S. safety agency interest. Reuters.

Kusano, K. D., Scanlon, J. M., Chen, Y.-H., McMurry, T. L., Chen, R., Gode, T., & Victor, T. (2024). Comparison of Waymo rider-only crash data to human benchmarks at 7.1 million miles. Traffic Injury Prevention, 25(sup1), S66–S77. https://doi.org/10.1080/15389588.2024.2380786

March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71

Milakis, D., van Arem, B., & van Wee, B. (2017). Policy and society related implications of automated driving: A review of literature and directions for future research. Journal of Intelligent Transportation Systems, 21(4), 324–348. https://doi.org/10.1080/15472450.2017.1291351

National Highway Traffic Safety Administration. (2022). NHTSA finalizes first occupant protection safety standards for vehicles without driving controls. U.S. Department of Transportation.

National Highway Traffic Safety Administration. (2026). NHTSA opens investigation into Tesla Cybercab self-certification following Austin deployment. U.S. Department of Transportation.

O’Reilly, C. A., III, & Tushman, M. L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. https://doi.org/10.5465/amp.2013.0025

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From Affordable EVs to Autonomous Mobility: Why Tesla May Be Rebuilding Its Growth Strategy Around Cybercab

Tesla may not have abandoned the affordable mass-market car. It may be rebuilding it around autonomy. Cybercab concentrates Tesla’s bet on driverless software, next-generation manufacturing and fleet economics. If execution succeeds, it could unlock a broader vehicle platform. If not, the lost conventional growth opportunity could prove costly.

Looking Beyond Property, Understanding the Bigger Picture

Real estate decisions should not be made in isolation.

Singapore property is influenced by interest rates, liquidity, global capital flows, geopolitical risk, currency movements, taxation, regulation, equity-market sentiment and the broader economic cycle. That is why I believe clients should work with a real estate professional who understands not only property, but also the wider investment landscape.

As a Singapore real estate salesperson, I dedicate hours each day to studying macroeconomics, global affairs, equities, digital assets, portfolio construction, asset allocation, Singapore property law and relevant regulations. I also invest significant time researching and writing these market essays because informed advice requires continuous learning, independent due diligence and disciplined analysis.

For Family Offices, 13O and 13U structures, GIP and VCC-related investors, international and Mainland Chinese clients, Southeast Asian families, ultra-high-net-worth individuals, institutional investors, overseas students and accompanying parents considering Singapore, I aim to provide a broader perspective on how real estate may fit within an overall wealth, residency and long-term asset-planning strategy.

Property can potentially provide portfolio diversification, relatively lower volatility than some traded assets, rental-income potential and long-term capital appreciation, although returns are never guaranteed and every investment requires proper suitability assessment and due diligence.

If you are considering buying, selling, renting or investing in Singapore property, I would be honoured to assist you with a research-driven, commercially grounded and client-first approach.

Zion Zhao | 赵峻慷
Singapore Real Estate

所有人都在等一辆更便宜的特斯拉，马斯克却押注 Cybercab：他真正想造的，可能根本不是下一辆车

人人都想要一辆更便宜的特斯拉，但马斯克另有打算：为什么 Cybercab 可能定义特斯拉的下一轮增长周期

多年来，特斯拉的下一步看起来非常明确：推出一款比 Model 3 和 Model Y 更小、更便宜的车型，保留方向盘和踏板，把 Full Self-Driving，也就是 FSD 完全自动驾驶能力作为选装功能，然后在全球市场实现大规模销售。

然而，埃隆·马斯克（Elon Musk）似乎选择了一条更激进的路线：Cybercab、Robotaxi 无人驾驶出租车，以及一套从一开始就围绕“未来不再需要人类驾驶”这一前提设计的全新汽车架构。

这个决定付出了真实代价。

特斯拉 2023 年交付约 181 万辆汽车，2024 年下降至约 179 万辆，2025 年进一步下降至约 164 万辆。汽车业务收入一度承压，全球竞争持续升温，而 Cybertruck 也没有创造出另一个类似 Model Y 的销量增长周期。与此同时，全球电动车市场仍在迅速扩张。2025 年全球电动车销量超过 2,000 万辆，中国汽车制造商在全球纯电动车市场中的份额继续扩大（International Energy Agency [IEA], 2026; Tesla, Inc., 2024, 2025, 2026）。

因此，那辆迟迟没有出现的平价特斯拉，成为特斯拉产品战略中最重要的缺口之一。

路透社在 2024 年报道称，特斯拉已经取消一项原定的低成本车型计划，并将更多资源转向 Robotaxi 开发，但马斯克公开否认了该报道。至今仍无法确认的是特斯拉内部具体如何作出这一决定。目前没有确凿的公开证据证明，特斯拉当时已经拥有一款准备量产的紧凑型 Model Y，也没有证据证明管理层普遍支持该项目，而马斯克个人否决了集体决定（Jin et al., 2024）。

与此同时，特斯拉近年来的正式披露也远比“放弃消费者汽车业务”复杂。

特斯拉 2026 年的文件继续表示，公司未来的增长将同时来自自动驾驶技术的发展，以及采用下一代技术的新产品。

这引出了一个更值得思考的命题。

特斯拉可能从来没有放弃平价、高销量汽车。它可能只是决定，下一代大众车型应该从一开始就围绕自动驾驶进行设计。

传统平价特斯拉提出的问题是：

我们能以多低的成本生产今天这种汽车？

Cybercab 提出的问题则是：

如果未来根本不再需要任何人驾驶，汽车到底应该变成什么？

这一区别，会改变整辆车的设计逻辑。

取消方向盘和踏板确实能够简化部分硬件，但并不会消除复杂度，而是把复杂度转移到其他系统。

在传统汽车里，人类驾驶员是最终的安全后备。如果自动驾驶系统遇到无法处理的问题，人类可以接管。

但在专门为无人驾驶设计的汽车中，软件、计算硬件、传感器、制动系统、冗余系统、通信能力以及车队运营体系，都必须共同完成全部驾驶任务，而不能依赖人类干预。

这正是为什么特斯拉会明确区分 FSD (Supervised)，也就是“FSD 完全自动驾驶能力监督版”，与真正意义上的无人驾驶系统。FSD (Supervised) 依然要求驾驶员持续监督，并不会让汽车成为真正的自动驾驶车辆。

自动驾驶真正困难的地方，在于所谓的“长尾问题”。

道路施工、紧急车辆、异常行人行为、损坏的道路设施、复杂临时路况和极端天气，这些事件单独发生的概率可能并不高，但累积起来，就构成了自动驾驶最难解决的部分。

学术研究也解释了为什么仅仅依赖累计里程无法完全证明自动驾驶的安全性。Kalra 和 Paddock（2016）指出，要从统计意义上证明自动驾驶车辆比人类驾驶更安全，可能需要极其庞大的真实道路行驶里程，因此还必须结合模拟、场景测试和工程安全验证。

与此同时，无人驾驶交通也已经不再只是理论。

Kusano 等人（2024）针对 Waymo 完全无人驾驶运营的同行评审研究发现，在特定运营条件下，其事故率低于部分人类驾驶基准。这并不能直接证明特斯拉的安全性，因为 Waymo 和 Tesla 采用不同的技术、车辆和运营模式，但它说明无人驾驶交通已经可以通过真实世界数据进行客观评估。

如今，特斯拉也开始进入这一阶段。

截至 2026 年 9 月，Cybercab 已经不再只是概念车，而是进入生产，并在美国奥斯汀部分地区展开有限的公众载客运营。

这是一个重要转折点，因为特斯拉现在可以同时验证软件、硬件、制造流程和车队运营。

但开始运营，并不等于已经解决通用自动驾驶问题。

服务范围仍然受到地理限制，软件成熟度、车队规模、天气条件、后台运营以及法规都依然重要。

监管甚至已经直接成为工程问题的一部分。

2026 年 9 月，美国国家公路交通安全管理局（National Highway Traffic Safety Administration, NHTSA）针对 Cybercab 根据适用《联邦机动车安全标准》（Federal Motor Vehicle Safety Standards, FMVSS）进行的自我认证启动 Audit Query 审查。

这并不意味着 Cybercab 已经无法合规。

真正的含义是，无传统驾驶控制装置车辆所涉及的法律框架，现在正在与技术本身同步接受检验（NHTSA, 2026）。

真正容易被忽视的价值，可能是制造方式

Cybercab 最吸引眼球的是自动驾驶，但制造技术可能同样重要。

特斯拉将 Cybercab 与其所谓的 Unboxed Manufacturing，也就是“Unboxed 模块化并行制造方式” 联系在一起。

其思路不是完全依赖传统汽车流水线逐步组装整车，而是让大型车辆模块并行制造，再在后续阶段组合。

如果这一模式成功，真正的战略突破可能并不只是“造出一辆更便宜的 Cybercab”。

而是：

找到一种更便宜、更高效的方式去制造未来所有汽车。

如果特斯拉能够通过 Cybercab 同时验证自动驾驶、下一代制造、车队运营和法规适应能力，那么 Cybercab 的价值可能远远超过一款单独车型。

它可能成为一个平台。

多头逻辑：特斯拉可能正在改变汽车行业的竞争单位

如果特斯拉成功，未来汽车竞争可能不再只是续航、售价、加速性能和外观设计。

真正的核心指标可能变成：

每一个有效客运里程的成本。

这意味着特斯拉未来竞争的市场，不只是传统汽车销售。

它甚至可能开始与出租车、网约车、租车服务、私人汽车拥有模式以及部分公共交通形成竞争。

汽车可能从一种一次性出售的耐用消费品，变成一种由软件控制、能够持续产生收入的实体资产。

如果 Cybercab 网络成功，还可能产生正向飞轮。

更多车辆带来更多真实道路数据，更多数据改善软件，更好的软件扩大运营区域，更大的运营范围提高用户价值，更高需求提升车辆利用率，而更高利用率则改善经济模型。

这是最乐观的情景。

潜在价值非常巨大。

空头逻辑：特斯拉放弃了一个已知机会，去追逐一个未知未来

但反方逻辑同样有力。

特斯拉早就已经证明自己能够制造电动车。

它拥有庞大工厂、全球品牌、充电网络，以及全球最成功的纯电 SUV 之一。

推出一款传统意义上的平价车型，是一个相对成熟、更加容易理解的商业机会。

然而，特斯拉却选择同时承担自动驾驶、制造创新和监管三种风险。

与此同时，其他电动车公司并没有停下来等待特斯拉。

因此，Cybercab 不能与“什么都不做”相比。

真正应该比较的是：

Cybercab 与那辆特斯拉原本可能已经卖出数百万辆的平价车型，哪一个能够创造更大的长期价值？

这才是这场战略赌注真正的机会成本。

还有一个悖论：Robotaxi 越成功，私人买车需求可能越低

如果无人驾驶网约车最终变得极其高效，家庭可能根本不需要拥有那么多私人汽车。

一辆高利用率的 Robotaxi，理论上可以替代多辆每天大部分时间都停着不用的私人车辆。

这对于一个主导无人驾驶交通网络的运营商可能是极好的商业模式，但却可能降低全社会对汽车总量的需求。

因此，特斯拉未来最重要的指标，可能不再只是卖出了多少辆汽车。

它可能变成：

整个网络提供了多少交通服务。

这意味着特斯拉可能逐渐从一家以汽车制造为主的企业，转型为一家交通平台公司。

那将是一家完全不同的特斯拉。

资本开支正在快速增加

自动驾驶经常被视为高毛利的软件业务，但特斯拉目前的转型却高度依赖资本投入。

2026 年上半年，特斯拉资本开支达到 82.8 亿美元，公司预计全年资本开支可能超过 250 亿美元，投资领域包括 AI 算力、数据中心、制造、机器人、充电基础设施、半导体项目以及车队资产（Tesla, Inc., 2026）。

2026 年第二季度，特斯拉收入强劲增长至 282.4 亿美元，但营业利润下降至 3.98 亿美元，因为公司正在大幅增加人工智能、软件和未来产能投入。

这组数据很好地概括了特斯拉现在的战略。

收入正在重新增长。

但与此同时，公司正在投入巨额资本去建造下一代技术体系。

这显然不是一场低风险转型。

真正应该关注的是证据，而不是叙事

现在评价特斯拉，最没有价值的方式，就是简单争论马斯克究竟是“天才”还是“鲁莽”。

真正的问题应该是可以被验证的。

Cybercab 能否安全扩大规模？

Unboxed Manufacturing 能否真正降低制造成本？

特斯拉能够多快扩大无人驾驶运营区域？

车辆需要多少远程人工介入？

NHTSA 最终如何处理 Cybercab 的认证问题？

把充电、维护、保险、清洁、折旧和空驶里程全部计算进去以后，Robotaxi 的真实经济模型能否成立？

特斯拉未来会不会直接向消费者销售无人驾驶汽车？

私人拥有的特斯拉能否加入 Robotaxi 网络？

最重要的是：

特斯拉会不会推出更多基于 Cybercab 架构的新车型？

这些问题的答案，最终才会决定战略成败。

结语：便宜的特斯拉可能并没有消失，而是在被重新定义

因此，现在最值得问的问题，已经不只是：

“特斯拉那辆便宜车到底去哪里了？”

而是：

“Cybercab 会不会正是特斯拉下一代平价汽车的第一个量产平台？”

如果答案是肯定的，那么特斯拉并没有真正放弃高销量汽车战略。

它只是试图重新定义实现规模化增长的方法。

如果自动驾驶成熟速度低于预期，这个决定可能成为特斯拉历史上最大的机会成本之一。

但如果特斯拉成功解决安全、制造、监管和经济效益问题，那么 Cybercab 就可能成为一道真正的桥梁。

桥的一端，是一家销售电动车的特斯拉。

桥的另一端，是一家销售自动驾驶交通服务的特斯拉。

最终决定结果的，不会是故事。

不会是情绪。

也不会是关于马斯克个人的崇拜或批评。

而是执行。

这正是 Cybercab 真正值得关注的地方。

它下注的并不仅仅是特斯拉能不能造出一辆 Robotaxi。

它真正下注的是一个更深层的问题：

当“驾驶”本身不再是汽车最核心的功能时，汽车究竟应该变成什么？

参考文献 References

International Energy Agency. (2026). Global EV outlook 2026. International Energy Agency.

Jin, H., Shirouzu, N., & Klayman, B. (2024, April 5). Tesla scraps low-cost car plans amid fierce Chinese EV competition. Reuters.

Kalra, N., & Paddock, S. M. (2016). Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transportation Research Part A: Policy and Practice, 94, 182–193. https://doi.org/10.1016/j.tra.2016.09.010

Kusano, K. D., Scanlon, J. M., Chen, Y.-H., McMurry, T. L., Chen, R., Gode, T., & Victor, T. (2024). Comparison of Waymo rider-only crash data to human benchmarks at 7.1 million miles. Traffic Injury Prevention, 25(sup1), S66–S77. https://doi.org/10.1080/15389588.2024.2380786

National Highway Traffic Safety Administration. (2026). NHTSA opens investigation into Tesla Cybercab self-certification following Austin deployment. U.S. Department of Transportation.

Tesla, Inc. (2024). Tesla vehicle production and deliveries and date for financial results and webcast for fourth quarter 2023. Tesla Investor Relations.

Tesla, Inc. (2025). Q3 2025 update. Tesla Investor Relations.

Tesla, Inc. (2026). Quarterly report for the quarter ended June 30, 2026. U.S. Securities and Exchange Commission.

便宜特斯拉为什么迟迟不来？答案可能藏在 Cybercab 里：马斯克正在重写汽车的下一条增长曲线

特斯拉或许并未放弃平价大众车型，而是在以自动驾驶重新定义它。Cybercab 集中押注无人驾驶软件、下一代制造与车队经济模型。若执行成功，它可能开启更广泛的新车型平台；若失败，错失传统大众市场增长的机会成本将十分高昂。

看房地产，也要看懂房地产背后的大局

房地产决策，从来不应该脱离宏观环境单独判断。

新加坡房地产受到利率、流动性、全球资本流向、地缘政治风险、汇率、税务政策、监管制度、股票市场情绪以及整体经济周期等多重因素影响。

因此，我始终认为，客户在选择房地产专业人士时，不应只关注对方是否熟悉楼盘和交易流程，也应关注其是否真正理解更广泛的投资环境、资产配置逻辑和全球经济变化。

作为一名新加坡房地产销售人员，我每天都会投入数小时持续研究宏观经济、国际局势、股票市场、数字资产、资产配置、投资组合构建、新加坡房地产法律及相关法规。我也长期投入大量时间撰写市场分析文章，因为我相信，专业服务必须建立在持续学习、独立研究、尽职调查和理性分析之上。

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如果您正在考虑在新加坡买房、卖房、租房或进行房地产投资，我非常愿意以研究驱动、商业务实、客户利益优先的方式，为您提供专业协助。

Zion Zhao｜赵峻慷
新加坡房地产专业服务