Navigating the Future: Tesla’s Full Self-Driving (Supervised) – A Decade in the Driver’s Seat
For the past ten years, I’ve been immersed in the evolving landscape of automotive technology, from the first tentative steps of advanced driver-assistance systems (ADAS) to the sophisticated AI currently shaping our roads. My journey has been one of critical observation, often marked by a healthy skepticism, particularly when claims of autonomy are presented with the fanfare Tesla often employs. This past November, I had the opportunity to spend considerable time with a Tesla Model Y equipped with their latest iteration of “Full Self-Driving (Supervised),” or FSD (S). The experience was, in a word, profound. For roughly 145 out of 150 miles, I relinquished control, observing as the system navigated a complex ballet of traffic, traffic lights, and pedestrian crossings with a grace that, at times, felt genuinely autonomous. Yet, despite its undeniable advancements, my verdict remains firm: I would not purchase it, nor would I recommend it without significant caveats.
The Uncanny Valley of Autonomy: Beyond Expectations, Yet Short of True Freedom
Tesla has consistently proven to be a master of exceeding expectations, often leaving its critics, myself included, in a position of having to acknowledge progress. I recall reviewing early iterations of Tesla’s Autopilot for major automotive publications back in the early 2010s. Even then, the system, while impressive for its time, struck me as overly confident, its marketing name misleading, and its capabilities far from true legal autonomy. Fast forward to today, and while those fundamental criticisms still hold water, the evolution of Tesla’s technology, particularly its AI-powered driver assistance, has brought it closer to the promised land of self-driving than many predicted possible in a consumer vehicle.
The leap from basic lane-keeping and adaptive cruise control to what is now termed “Full Self-Driving (Supervised)” is staggering. This advanced system, designed to operate under constant human oversight, now tackles a far broader spectrum of driving scenarios, extending well beyond the divided highways where early systems found their footing. The intervening years have been fraught with legal battles and tragic accidents, many of which, in my professional opinion, could have been averted with a more cautious deployment of these powerful technologies. However, the progress the technology itself has made is, without question, awe-inspiring.
The current pricing structure for Tesla FSD subscription or a one-time purchase can be substantial. While Tesla has started bundling FSD with higher-end models like the Model X and Model S, the upfront cost for other vehicles, or the recurring monthly fee, presents a significant investment. Furthermore, the longevity of the “lifetime” access is a pertinent question. As Tesla develops new hardware generations (moving beyond “hardware 3”), the practical compatibility with older vehicles and the availability of sophisticated software updates remain uncertain. This raises concerns about future software updates for Tesla vehicles and whether older models will truly receive the same level of advanced features indefinitely. Despite these considerations, the sheer capability offered by Tesla’s driverless technology at this price point is unmatched in the consumer automotive market.
My experience was with FSD 13.2.9, a version predating the absolute latest release, yet it provided a compelling glimpse into the sophisticated AI driving Tesla’s vision. The system’s performance on freeways was generally exceptional, with only a single instance of questionable merging behavior requiring my intervention. In urban environments, FSD (S) demonstrated a commendable degree of caution at blind intersections and exhibited patience at stop signs. Navigating ambiguity and unpredictable situations appeared to be handled with remarkable adeptness in the majority of circumstances. This refinement in Tesla’s AI driving system is a testament to years of data collection and iterative development.
The Perilous Gamble: When Confidence Leads to Complacency
The core challenge with systems like Tesla FSD (S) lies in their inherent unpredictability. While the car often defaults to the safest course of action, there are moments where it can, and does, err significantly. The critical issue is that without a deep understanding of the system’s internal workings, anticipating these critical failure points becomes a formidable task. This necessitates unwavering vigilance from the human supervisor – a level of attentiveness that the average driver, potentially influenced by misleading marketing, may not be prepared to provide.
The history of accidents involving these advanced driver-assistance systems is undeniable. Many lawsuits and tragic outcomes have centered around allegations of wrongful death and negligence. Tesla’s consistent legal stance is that the systems are not operating autonomously and that the onus of supervision remains entirely with the vehicle owner. While the specific circumstances of each incident are unique, and the software has undoubtedly improved, the technology has entered an unsettling “uncanny valley.” The very fact that the Tesla Model Y I piloted so rarely made mistakes began to lull me into a false sense of security. Then, without warning, a critical intervention was required – a sudden need to prevent a collision with a merging vehicle, or an alarming moment where the car attempted a left turn against a red light, even in the absence of cross-traffic.
This duality is the crux of the problem: the system performs competently enough to foster a sense of reliance, yet it lacks the infallibility required for true trust. Without a predictive model of its potential failures, your vigilance must be absolute. And if you are truly engaging with the system as intended – constantly assessing its trajectory, anticipating potential issues, keeping your hands poised for immediate takeover, and meticulously checking your mirrors – is this truly more relaxing than simply driving the vehicle yourself?
For me, the mental load of trying to predict the errors of a highly capable, yet inherently imperfect, AI was, frankly, as stressful as conventional driving. However, it was also profoundly more tedious. The inability to engage with my phone, to glance away, or to simply allow my mind to wander created an environment that felt simultaneously safer in theory and more burdensome in practice. The passage of time often felt elongated, as I strived to maintain a state of engaged observation.
The ultimate aspiration, of course, is the complete removal of the human driver from the equation. This is the driving force behind Tesla’s robotaxi pilot program in Austin, Texas, and the long-standing vision that Elon Musk has championed for years. While this future appears closer than ever, it remains tantalizingly out of reach for consumers. For now, the expectation is a state of quiet, watchful anticipation, a constant battle against both unexpected hazards and the encroaching tide of boredom.
The Unsettling Equilibrium: Trust Versus Vigilance in the Age of Supervised Autonomy
The early iterations of Autopilot, while less sophisticated, were paradoxically easier to manage from a psychological standpoint. I understood its limitations, and thus, I used it as an enhanced form of cruise control. There was a clear, definable boundary between what the system could handle and where human intervention was essential.
Today, however, that line has blurred into an indistinguishable haze. FSD (S) is so proficient in a vast array of driving scenarios that the natural inclination is to relax and surrender control. Yet, because the decision-making process of the AI remains opaque, true trust – the kind that allows for genuine disengagement – is impossible to achieve. This is particularly true when the safety of those around you hangs in the balance. The result is a state of hyper-vigilance, a perpetual waiting game for the system to falter.
But what if these failures are genuinely rare? In my 150 miles of driving, I encountered two clear instances requiring intervention. I was alert and able to react before these situations escalated into serious incidents. However, consider the implications if this is the accepted baseline. We are essentially asking the general public to function as vigilant supervisors for an advanced AI that, by its very nature, can exhibit unexpected behaviors. My approximately five hours of cumulative driving time in and around San Diego translates to, on average, an intervention-requiring event every 2.5 hours. Imagine the mental fatigue of being in a state of constant, unimpeded supervision for that duration. By the time a critical error occurs, how likely is it that you will still be fully engaged and prepared to react effectively?
This creates a profoundly concerning paradox: a system that is trustworthy enough to erode our natural caution, yet not sufficiently safe to be deployed without constant, demanding human oversight. The promise of autonomous vehicle technology is undeniable, but achieving it responsibly requires a more transparent and predictable human-AI interface, especially when navigating the complexities of urban driving assistance and highway navigation. The current iteration of FSD (S), while technologically impressive, demands a level of vigilance that undermines the very relaxation it purports to offer, leaving drivers in an unsettling balance between wonder and worry. For those considering the leap into advanced automotive AI, understanding these nuances is paramount. Exploring options for ADAS safety training or seeking out expert reviews on self-driving technology can provide valuable context before making a significant investment in vehicles like the Tesla Model Y or other electric vehicles with advanced driver assistance.
