Tesla’s Robotaxi service faced several technical challenges during its inaugural day of operations in Austin, with invitation-only Tesla fans public video footage capturing multiple concerning incidents. Issues ranged from steering anomalies to operational shortcomings that highlight the complexities of transitioning from prototype to production-ready autonomous taxi service.
The most alarming incident occurred during a left turn maneuver when the vehicle abruptly swerved the steering wheel multiple times—an unsettling behavior that raises questions about the underlying software’s decision-making process. This type of erratic steering behavior is exceptionally rare in other autonomous driving systems and hasn’t been documented in previous Tesla FSD versions, suggesting a potential flaw in the current model’s training algorithms.
Tesla’s decision to deploy Robotaxi using the base FSD v13 model rather than the more advanced FSD v14 has drawn scrutiny from industry observers. Upcoming FSD v14 is expected to feature 4.5 times more parameters than the current generation, potentially offering significantly improved generalization capabilities.
The steering anomaly appears to be a critical software bug that shouldn’t have survived testing protocols. Such issues are typically identified and resolved during development phases, making their appearance in a public service concerning for both safety and reliability perspectives.
Beyond the technical steering issue, Tesla’s Robotaxi encountered two operational problems that reflect the company’s inexperience in ride-hailing services. In one documented case, a vehicle stopped directly in the middle of an intersection after a user tapped the “Stop” button in the app—a dangerous response that demonstrates inadequate safety protocols for user-initiated stops.
Additionally, multiple testers reported localization drift issues, requiring users to walk around to locate their assigned vehicles after summoning them. This problem, while less dangerous than the intersection stopping, creates user experience friction that established ride-hailing platforms have long since resolved.
These operational shortcomings underscore Tesla’s decision to build its own ride-hailing platform rather than partnering with established services like Uber or Lyft. Tesla must now independently develop the operational expertise that these platforms have refined over years of service.
Issues such as precise vehicle positioning, safe stop protocols, and user interface optimization represent foundational capabilities that any successful ride-hailing service requires. Tesla’s learning curve in these areas will likely extend beyond technical vehicle automation to encompass customer service, fleet management, and regulatory compliance.
The resolution of these issues may depend on the rollout of FSD v14, expected by the end of this year. Next-gen v14 promises enhanced capabilities that could address current limitations while potentially enabling Tesla to eliminate safety drivers entirely.
Whether FSD v14 can scale Robotaxi operations to multiple cities and support a full rollout of FSD Unsupervised remains uncertain. Current issues suggest that Tesla’s path to fully autonomous operations involves more than just improving the driving algorithms—it requires mastering the complete service delivery ecosystem.
Tesla’s Robotaxi effort represents an ambitious attempt to repurpose mass-produced vehicles for autonomous taxi services, which is undeniably impressive from an engineering perspective. However, the first day’s technical and operational challenges demonstrate that even the most advanced autonomous driving technology requires careful integration with robust service platforms. As Tesla continues refining its approach, the company will need to prove that its Robotaxi service can operate safely and reliably—ensuring that passengers don’t experience any more robot-taxi moments of uncertainty.
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