Tesla's Robotaxi Unveil: A Bold Move or Higher Risks?

By Norihiko Shirouzu and Chris Kirkham
(Reuters) – Tesla (NASDAQ:TSLA) aims to stun investors Thursday night with its long-awaited robotaxi unveil, a potential milestone after a decade of Elon Musk’s unfulfilled promises to deliver self-driving vehicles.

The automaker is widely expected to showcase a prototype called the Cybercab rather than a road-ready driverless taxi.

Convincing regulators and passengers of the vehicle’s safety could prove much harder and take much longer—while its main competitors, such as Alphabet’s (NASDAQ:GOOGL) Waymo, expand robotaxi fleets they're already operating in select cities today.

Tesla has pursued a technological path different from its rivals—one with potentially higher rewards but also higher risks to both its business and its passengers, based on interviews with industry experts and former Tesla engineers.

Tesla's strategy relies on computer vision, aiming to use cameras like human eyes, combined with an AI technology called end-to-end machine learning that translates images into driving decisions. Though this technology supports its Full Self-Driving feature, it cannot operate safely without a human driver. Musk claims Tesla is using the same approach to develop fully autonomous robotaxis.

Competitors, including Waymo and Zoox, use a mix of technology layered with radar, lidar, and sophisticated mapping to ensure safety and earn regulatory approval, leading to a more complex but safer system.

Tesla’s simpler, cost-effective strategy has two critical weaknesses; it struggles with rare driving scenarios, known as edge cases, and its reliance on black box AI makes it challenging to diagnose failures that cause accidents.

Nvidia’s CEO described the weaknesses of end-to-end technology similarly, noting that while it may yield the best driving decisions, a conservative approach is necessary for safety.

Robotaxi Pivot

Tesla's ability to deliver robotaxis grows crucial this year as it faces declining sales and fierce competition from Chinese EV makers. If Tesla can conquer its autonomous challenges, the payoff could be immense, with ambitions to offer affordable robotaxis that can operate anywhere.

However, Musk's history of bold promises raises skepticism. Predictions about delivering self-driving cars by 2018 and operational robotaxis by 2020 remain unfulfilled. The recent announcement came post the decision to abandon the Model 2 project, signaling a shift towards prioritizing self-driving technology.

Investors, meanwhile, continue to watch closely, with calls for Musk to convince them of the viability of his autonomous strategy.

Data Driven

Currently, Tesla only offers semi-autonomous solutions, leading to investigations into its marketing practices concerning safety claims. A recent NHTSA investigation noted numerous crashes involving its Autopilot and FSD features.

Tesla's use of semi-autonomous capabilities offers a significant advantage—access to extensive data collected from its vast fleet, which supports the development of self-driving tech. The cost-effectiveness of its technology compared to competitors like Waymo could enable future affordability for fully autonomous vehicles.

Nevertheless, experts argue Tesla faces a significant gap in achieving a safe, fully autonomous system. The company has removed some sensor technologies, leaving its AI-dependent approach prone to potential hazards. Studies indicate that computer vision can fail to recognize objects 3% of the time, raising safety concerns.

Former Waymo CEO, John Krafcik, emphasized the importance of additional sensors and technology transparency in ensuring safe navigation. The inability of Tesla's end-to-end systems to clearly explain errors presents an ongoing challenge in guaranteeing safety as they venture into this complex domain.

Conclusion

The road ahead for Tesla’s autonomous driving ambitions is fraught with high risks. While they pursue revolutionary technology with promises of affordable self-driving taxis, the questions around safety and reliability continue to loom large.