Waymo’s Quiet Dominance

While headlines focused on setbacks at other companies, Alphabet’s Waymo has been steadily building the first successful commercial autonomous vehicle network. The company now operates in San Francisco, Phoenix, Los Angeles, and Austin, completing over 150,000 paid rides per week—a number that would have seemed impossible just two years ago.

The Technology Divide: Lidar vs. Vision

The industry remains split on the fundamental approach to autonomy. Waymo and most traditional automakers use lidar-based systems that create detailed 3D maps of the environment. Tesla famously relies on cameras and neural networks alone, arguing that if humans can drive with just vision, so can AI.

“We’ve crossed the threshold where our vehicles are demonstrably safer than human drivers. The technology works—now it’s about scaling responsibly while maintaining that safety record.”

— Tekedra Mawakana, Co-CEO of Waymo

Cruise’s Rocky Comeback

GM’s Cruise is plotting its return after a 2024 incident in San Francisco led to a regulatory suspension and leadership changes. The company has retooled its safety protocols, appointed new leadership, and is gradually resuming operations with enhanced human oversight during the recovery period.

The incident highlighted how quickly public trust can evaporate—and how regulatory goodwill is fragile. Cruise’s path back demonstrates that even well-funded AV programs operate on a knife’s edge. A single high-profile incident can erase years of progress and billions in investment.

GM has committed to continuing Cruise development despite the setbacks, though the timeline for commercial scale has been pushed back significantly. The company’s willingness to absorb ongoing losses reflects both the strategic importance of autonomy and the limited exit options for a program so deeply developed.

Tesla’s Different Path

Tesla’s Full Self-Driving (FSD) system represents a fundamentally different approach to autonomy. Rather than geofenced robotaxi services in limited areas, Tesla aims for a generalized system that works everywhere its cars can drive. The vision-only approach, if successful, would enable massive scale at minimal hardware cost.

However, FSD remains classified as Level 2 driver assistance, requiring continuous driver attention and intervention capability. Tesla’s marketing and Elon Musk’s claims have faced regulatory scrutiny and consumer confusion about the system’s actual capabilities versus its aspirational name.

The FSD V12 update, based on end-to-end neural network control, has shown substantial improvement according to enthusiasts and reviewers. Whether this approach can achieve the safety thresholds required for true autonomy—without lidar’s redundancy—remains the central technological question in autonomous vehicles.

Regulatory Landscape Evolving

Federal regulators are developing new frameworks for autonomous vehicles, attempting to balance innovation encouragement with public safety. NHTSA investigations into Tesla’s FSD claims and Cruise’s incident response have intensified scrutiny on the entire industry.

States continue to take varied approaches, creating a patchwork of regulations. California remains the most stringent, while Arizona has been more permissive—leading companies to strategically choose testing and deployment locations. This regulatory arbitrage affects where autonomous vehicles operate and which companies can scale fastest.

The liability framework remains unsettled. When an autonomous vehicle causes an accident, who bears responsibility? The manufacturer, the software developer, the owner, or some combination? Insurance models are evolving, but legal precedents are still being established through litigation and regulatory guidance.

The Robotaxi Business Model

Waymo’s expansion tests whether robotaxis can operate profitably at scale. The economics are challenging: expensive vehicles, high maintenance costs, and the need for remote monitoring and support staff. However, eliminating the driver—who represents 60-70% of traditional rideshare costs—creates potential for substantial margins at volume.

Pricing strategies vary. Waymo charges comparable rates to Uber and Lyft in most markets, suggesting current economics are sustainable even without the theoretical cost advantages of full scale. Premium features like cleanliness, predictability, and privacy justify equal or higher pricing for many customers.

The competitive dynamic with Uber and Lyft is complex. Both companies have invested in autonomy and maintain partnerships with AV developers. Their existing rider networks and demand aggregation platforms could become valuable distribution channels for autonomous fleets. The ultimate market structure may involve AV manufacturers, technology companies, and rideshare platforms all playing roles.

Autonomous Trucking: The Quieter Revolution

While robotaxis attract attention, autonomous trucking may reach commercial viability sooner. Highway driving is simpler than urban navigation—fewer pedestrians, predictable patterns, and better-defined rules. Companies like Aurora, TuSimple, and Plus are focusing on long-haul freight routes.

The trucking business case is compelling. Driver shortages, hours-of-service regulations, and labor costs create substantial motivation for automation. An autonomous truck can operate nearly continuously, dramatically improving asset utilization. The addressable market in trucking exceeds $800 billion annually in the U.S. alone.

Near-term deployments focus on hub-to-hub routes between distribution centers on highways. Human drivers handle the first and last miles in complex urban environments. This hybrid approach captures many economic benefits while avoiding the most challenging technical problems.

Investment Implications

Direct autonomous vehicle investment options are limited. Waymo remains private within Alphabet, providing indirect exposure through GOOGL. Cruise is embedded within General Motors. Tesla represents a bet on the vision-only approach and the eventual deployment of the promised robotaxi network.

The supply chain offers alternative exposure. Companies providing lidar sensors (Luminar, Ouster), computing platforms (NVIDIA), and mapping data (TomTom, HERE) benefit from industry growth regardless of which AV approaches succeed. These picks-and-shovels plays carry lower binary risk than bets on individual AV developers.

The timeline for significant AV industry revenue remains uncertain. Waymo is proving that the technology works at commercial scale, but profitability and geographic expansion will take years. Investors should maintain long time horizons and size positions for the extended development period ahead.