Waymo與特斯拉Robotaxi之間的差異，不僅體現在技術實現方式上，也反映出兩家公司在商業模式、風險取向與市場策略上的根本不同。

Waymo是Alphabet（Google母公司）旗下的自駕車公司，自2009年起就開始自動駕駛技術的開發，是業界公認的先驅者。該公司採用高度保守、穩健的方式來測試與部署自駕系統。經過多年封閉測試與實地運營，Waymo於2018年在美國亞利桑那州鳳凰城正式推出Robotaxi服務，並於後續擴展至舊金山與洛杉磯。然而，儘管投入超過十年，Waymo截至2024年也僅部署約1500輛自駕車，累計1千萬載客次數。且運營區域受限，需仰賴高精度地圖與嚴格劃定的地理圍欄。其L4等級的自駕系統，在特定區域內可以實現完全無人駕駛，但一旦離開熟悉區域，系統表現就會大幅下降。因此，Waymo選擇將安全性置於擴展速度之上，市場評價雖正面，但也普遍認為它的成長緩慢、缺乏商業化突破。

特斯拉的Robotaxi構想則走向截然不同的道路。馬斯克主張「純視覺方案」（Tesla Vision），完全放棄LiDAR與高精度地圖，改以攝影機與AI神經網路模型進行學習與決策。這使特斯拉的自駕系統能夠在全球各地道路環境中累積大量數據，持續優化其Full Self-Driving（FSD）系統。根據馬斯克的說法，特斯拉FSD Beta已於全球數百萬輛車中收集超過十億英里以上的數據，並透過OTA（空中軟體更新）持續迭代升級。

2025年6月，馬斯克宣佈將在五天內啟動Robotaxi服務，此舉震驚市場，主要原因有幾點。首先，特斯拉本身已擁有龐大的車主基礎，許多已購買FSD的車主只需透過軟體更新，即可開啟Robotaxi功能，無需等待車輛更換或複雜硬體改裝。其次，馬斯克將Robotaxi定義為一種「共享經濟」平台，允許車主將閒置車輛投入自動營運獲利，這種模式降低資本投入門檻，也加速服務規模化。

再者，特斯拉的自駕系統雖尚未獲得美國運輸部正式L4認證，但其「監督式自動駕駛」模式（Supervised autonomy）可以在短時間內上線並由車主在初期階段進行監控，逐步過渡至無人操作，這也是一種策略上的模糊地帶運作方式。雖然引來部分安全爭議，但也讓特斯拉在法規未完全明確的情況下，搶佔先機。

特斯拉Robotaxi的快速上線並非完全技術成熟的結果，而是依靠其龐大資料、靈活平台化架構，以及馬斯克一貫高風險、高回報的策略思維。對比Waymo穩健保守的方式，特斯拉選擇快速試錯與市場推廣先行。這種做法引來兩極化評價，一方面被視為顛覆傳統、具有革命性潛力；另一方面也被質疑安全與監管風險是否足夠嚴謹。

總結而言，Waymo與特斯拉代表自駕車產業中兩種截然不同的發展邏輯：前者以工程穩定與法規合規為重，後者則以平台擴張與用戶數據為本。特斯拉Robotaxi五天內上線之所以成為可能，是因為它並非從零開始，而是建立在長年FSD系統部署與用戶車輛資料積累的基礎上，同時搭配極具侵略性的市場策略與鬆動的法規界線所實現的結果。未來，究竟誰的模式能真正主導自駕出行市場，仍有待時間與實際安全記錄來驗證。

The differences between Waymo and Tesla’s Robotaxi lie not only in their approaches to autonomous driving technology, but also in their business models, risk tolerance, and market strategies. These fundamental contrasts have led the two companies down very different paths in the self-driving vehicle industry.

Waymo, a subsidiary of Alphabet (Google’s parent company), began developing autonomous driving technology as early as 2009, making it one of the industry’s recognized pioneers. The company has taken a cautious and methodical approach to testing and deploying its self-driving systems. After years of closed-track testing and controlled real-world trials, Waymo officially launched its Robotaxi service in Phoenix, Arizona in 2018, later expanding to San Francisco and Los Angeles. However, despite more than a decade of development, Waymo had only deployed around 1,500 autonomous vehicles by 2024, with a cumulative total of 10 million passenger trips. Its operations remain confined to specific geofenced areas that rely heavily on high-definition maps. While its Level 4 (L4) autonomy allows fully driverless operations in certain zones, the system’s performance drops significantly outside these pre-mapped areas. As a result, Waymo has prioritized safety over rapid scaling. Although it receives positive market reviews, it is often criticized for slow growth and limited commercial breakthrough.

In contrast, Tesla’s vision for Robotaxi has followed a radically different trajectory. Elon Musk advocates for a “vision-only” approach known as Tesla Vision, which completely abandons LiDAR and high-definition mapping in favor of cameras and AI neural networks for decision-making and environmental understanding. This approach enables Tesla’s autonomous system to collect massive amounts of real-world driving data from diverse road conditions worldwide, continuously improving its Full Self-Driving (FSD) software. According to Musk, Tesla’s FSD Beta has already logged over one billion miles of data across millions of vehicles, with ongoing upgrades delivered via over-the-air (OTA) software updates.

In June 2025, Musk announced that Tesla’s Robotaxi service would launch within just five days—a move that stunned the market. Several factors contributed to this bold timeline. First, Tesla already has a large base of vehicle owners, many of whom have purchased the FSD package. These owners can activate the Robotaxi functionality simply through a software update, without the need for vehicle replacement or significant hardware modifications. Second, Musk has positioned Robotaxi as a “sharing economy” platform, where car owners can monetize their idle vehicles by allowing them to operate autonomously and generate income. This dramatically lowers capital requirements and accelerates scalability.

Furthermore, although Tesla’s autonomous system has not yet received formal Level 4 certification from the U.S. Department of Transportation, its “supervised autonomy” model allows the Robotaxi feature to launch under human oversight. In the early phase, vehicle owners are expected to monitor the system, with a gradual transition to full autonomy over time. This ambiguous regulatory position has drawn criticism regarding safety and legal compliance, but it has also allowed Tesla to move faster than competitors in an uncertain legal environment.

Tesla’s rapid Robotaxi rollout is not purely a result of technical maturity, but rather the culmination of vast data collection, a flexible platform-centric design, and Musk’s high-risk, high-reward strategic thinking. Unlike Waymo’s cautious and compliance-driven methodology, Tesla favors rapid iteration and market-first deployment. This strategy has yielded polarized responses—celebrated by some as disruptive and revolutionary, and questioned by others for potential safety and regulatory lapses.

In summary, Waymo and Tesla represent two fundamentally different philosophies in the autonomous vehicle space. Waymo focuses on engineering stability and strict regulatory compliance, while Tesla emphasizes platform expansion and data-driven learning. The fact that Tesla’s Robotaxi could launch in just five days is not due to starting from scratch, but rather the result of years of FSD development, extensive user data, aggressive market positioning, and strategic exploitation of regulatory grey areas. Whether Tesla’s bold approach or Waymo’s conservative path will ultimately dominate the future of autonomous mobility remains to be seen—and will be determined by both technological performance and long-term safety records.