When a massive blackout plunged San Francisco’s streets into darkness, autonomous vehicles were put to a stringent test. Residents witnessed rare scenes as traffic signals failed citywide, creating a unique evaluation ground for self-driving systems. This real-world scenario, unplanned by engineers, highlighted both the strengths and the limitations of current AI-driven mobility. Questions about artificial intelligence’s reliability in critical urban infrastructure failures have never felt more relevant, as both Tesla and Waymo vehicles responded in noticeably different ways.
Earlier demonstrations of self-driving capabilities, such as those carried out by Tesla FSD and Waymo, typically occurred under ideal conditions or in mild weather challenges. Reports had indicated that both systems could encounter difficulties with unusual road markings, emergency vehicles, or construction zones. The recent blackout, however, exposed contrasting operational responses under sustained and widespread loss of urban lighting, marking a new chapter in the public assessment of autonomous vehicle adaptability.
How Did Tesla’s FSD Perform with No Lights?
Tesla’s Full Self-Driving (Supervised) system, equipped on a Model Y, continued navigating city streets with minimal external light, as revealed in dashcam footage shared on social media. Streetlights and traffic signals were inactive, yet the FSD system processed its surroundings and drove at a cautious pace. Supporters noted that the car appeared to act similarly to an attentive human driver, choosing routes and speeds proactively while maintaining composure in unpredictable situations.
What Issues Did Waymo’s Vehicle Face?
Waymo vehicles, which operate as robotaxis using the Jaguar I-PACE platform, experienced more pronounced difficulties. Several cars halted mid-intersection following established protocols, treating inactive signals as four-way stops but remaining stationary for extended periods. This led to significant traffic delays and required staff intervention to manually recover immobilized vehicles. Company representatives acknowledged the challenging circumstances, noting the “sheer scale of the outage” as a contributing factor.
What Do Tesla and Waymo Say About These Events?
Tesla’s public communications emphasized the steady performance of its FSD system during the incident.
“FSD is trained on billions of real-world miles, including power outages,”
highlighted the company’s emphasis on broad data-driven learning. Elon Musk reinforced this point by stating,
“Tesla Robotaxis were unaffected by the SF power outage.”
Meanwhile, Waymo’s spokesperson addressed the consequences, stating the company is “focused on rapidly integrating the lessons learned” and is committed to regaining community trust after the disruptions.
These events offer insight into the varying degrees of resilience incorporated into autonomous vehicle systems. Tesla continues refining its vision-only navigation, relying on AI trained with extensive real-world data to adapt in uncertain conditions. Waymo integrates multiple sensor modalities with set decision processes, which, while safe in standard scenarios, can be less flexible in unexpected citywide failures such as blackouts. Autonomous vehicle buyers and fleet operators may find such operational distinctions pivotal, particularly for deployment in urban areas historically vulnerable to power disruptions. For readers considering the practical deployment of driverless technology, instances like this highlight the necessity of preparing for real-world extremes, not just theoretical benchmarks, when evaluating autonomy features and reliability.
