February 8, 2026
Finance

Waymo and Tesla Diverge on Autonomous Vehicle Safety and Sensor Strategies

Industry Leaders Debate the Path to Safer, More Cost-Effective Self-Driving Technologies

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Summary

Waymo and Tesla represent two leading philosophies in autonomous driving development. Waymo emphasizes surpassing human safety through an extensive sensor suite and iterative cost reduction, aiming for high safety standards. Tesla focuses on camera-based AI perception, asserting that cameras alone suffice for autonomous driving. These contrasting approaches continue to shape the discussion around sensor technology, software quality, and the benchmarks for autonomous vehicle safety.

Key Points

Waymo sets a safety performance bar higher than human driving, utilizing a multi-sensor suite including cameras, lidar, and radar to enhance AI perception.
Waymo aims to reduce sensor costs and quantity in future models while improving software quality through iterative innovation.
Tesla advocates for a camera-only sensor approach, asserting that solving autonomy is primarily an AI challenge rather than a sensor limitation.
Discussions around autonomous vehicle safety standards and sensor strategies remain active, with both companies reinforcing their respective philosophies.

The race to perfect autonomous driving technology has positioned Tesla Inc. and Waymo, the self-driving division of Alphabet Inc., at the forefront of industry innovation. Despite shared goals, these companies adopt fundamentally different strategies to achieve safe, reliable autonomy.

During a recent interview, Waymo’s vice president of onboard software, Srikanth Thirumalai, underscored that autonomous system safety goals should exceed human driving standards. He articulated, "I think the bar is higher than human driving. Given where the technology is right now, the question is what is it going to take for that product to be safe?" This sets a high benchmark that informs Waymo’s technical development.

Waymo deploys a comprehensive array of sensing hardware designed to support its artificial intelligence perception capabilities. Their current platform integrates 29 cameras, five lidar sensors, and six radar units. This multi-sensor configuration provides diverse data streams to enrich environmental understanding.

Thirumalai emphasized that safety remains the prime objective amid efforts to optimize design and cost. He explained that Waymo intends to reduce sensor quantities over time for future robotaxi models while enhancing software sophistication. "So you work backwards from that safety bar and say, ‘What does it take to build a safe product?’ And then keep pushing and iterating and innovating to reduce the cost of the sensors, and to improve the quality of the software and how it uses the sensors," he remarked.

Furthermore, Waymo actively defines safety metrics by analyzing driving scenarios with aspirations to minimize incident rates. However, Thirumalai also acknowledged the practical limitations, conceding that absolute perfection in robotaxi safety is unlikely and that incidents will inevitably occur despite rigorous standards.

Contrasting Waymo's approach, Tesla takes a distinct position on sensor strategy and autonomy philosophy. At the ScaledML Conference, Tesla's vice president of AI, Ashok Elluswamy, articulated that autonomous driving should primarily rely on camera technology, mirroring human vision. Elluswamy contended, "It’s so obvious you can solve this with cameras. Why wouldn’t you solve with cameras? It’s 2026. The self-driving problem is not a sensor problem, it’s an AI problem. The cameras have enough information already. It’s a problem of extracting the information, which is an AI problem." This perspective minimizes the need for additional sensors such as lidar or radar, focusing on improving artificial intelligence to interpret visual data effectively.

The debate between Tesla and Waymo over the optimal autonomous vehicle technology has persisted over time. For instance, in July 2025, Tesla's CEO Elon Musk publicly expressed skepticism about Waymo's reliance on lidar by sarcastically responding to a Waymo robotaxi video, reigniting the longstanding lidar versus camera discussion. Musk maintains that Tesla's safety improves by employing a camera-only system and disabling radar sensors.

The broader autonomous driving industry is also evolving. Market observers have noted that Tesla will not be alone in achieving viable autonomy. Technologies such as Nvidia Corp.'s Alpamayo suggest that advancements in unsupervised autonomy may soon become widely accessible. Additionally, industry leaders like Uber Technologies Inc. CEO Dara Khosrowshahi stress that attaining "superhuman levels of safety" remains a critical objective, a claim that Waymo asserts is achievable given their current safety framework.

This ongoing divergence highlights the complexity of balancing safety, cost, and technological sophistication within autonomous driving development. As companies iterate on sensor configurations and software algorithms, the debate about the fundamentals of autonomy—whether through camera-exclusive systems or sensor-rich platforms—continues to shape industry trajectories.

Risks
  • The perfect safety outcome for autonomous vehicles is unattainable; incidents involving robotaxis are considered inevitable despite rigorous standards.
  • Reducing the number of sensors must be balanced carefully against maintaining or improving safety performance, posing technical and operational risks.
  • Relying exclusively on camera-based systems may limit the detection capabilities compared to multisensor setups, which could impact safety or system reliability.
  • The differing approaches may lead to fragmentation in industry standards and slow widespread adoption if consensus on safety and technology is lacking.
Disclosure
Education only / not financial advice
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