One year ago today, I tried Tesla Full Self-Driving. It changed how I see every road trip—freedom, adventure, and a new way to travel. Discover what it’s like to let autonomy take the wheel.

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Real moments from the road—events, milestones, and stories from the Full Self-Driving journey. Curious what all the hype is about? See for yourself at Tesla.
Roger
This short clip captures my very first experience with Full Self-Driving. The car took me on a route from Shawnee Mission Parkway to I-35, then onto 169, across 435 East, and down State Lane Road—delivering me right into the parking lot of the Kansas City Tesla dealership. It was slightly frightening and an extraordinary joyride all at once.

Morgan Ellis
Hear about unforgettable cross-country adventures and how Full Self-Driving made every mile smoother, safer, and more fun.

Jordan Avery
Reflect on a year of Full Self-Driving—over 13,000 miles, new perspectives, and the freedom to enjoy every journey.
Real FSD stories, real freedom
Meet the amazing folks who make this journey possible—enthusiastic Tesla fans, adventurous road trippers, and dedicated FSD supporters who inspire me every day.
Real talk from the passenger seat—here’s what you need to know before you trust your journey to Full Self-Driving. Answers from the road, for the road.
How Tesla Full Self-Driving Works
Tesla's Full Self-Driving system operates through a sophisticated integration of vision-based perception, custom silicon, and end-to-end neural network processing—a fundamentally different approach than competitors who rely on lidar and high-definition maps.
Vision-Only Perception
Tesla vehicles are equipped with eight exterior cameras providing 360-degree visibility around the vehicle. This camera array captures over 200 frames of video per second, feeding raw visual data directly into the system. Tesla made the deliberate decision to eliminate radar and ultrasonic sensors, betting that camera-based perception—the same method humans use to navigate—combined with sufficiently advanced AI can match or exceed multi-sensor approaches.
End-to-End Neural Network Architecture
The breakthrough in recent FSD versions (V12 and beyond) is the transition from rule-based programming to a unified end-to-end neural network. Previous iterations relied on approximately 300,000 lines of explicit C++ code defining how the vehicle should respond to specific scenarios. The current architecture replaces this with a neural network trained on millions of video clips of expert human driving.
The system now takes raw camera inputs and directly outputs vehicle control commands—steering angle, acceleration, and braking—without intermediate hand-coded rules. Rather than programming the car to recognize a roundabout and then consulting a rulebook for how to navigate it, the network learns driving behavior holistically by observing how humans drive.
Custom Hardware
Tesla designed its own silicon to run these demanding neural networks in real-time. The FSD Computer features custom-designed chips fabricated by Samsung, functioning as neural network accelerators. Hardware 4 vehicles feature higher-resolution cameras with improved dynamic range and significantly more processing power than the previous HW3, essential for running the increasingly complex neural network models. Each system includes two FSD chips for redundancy.
The Data Engine
Tesla's competitive advantage lies in its fleet-learning approach. With millions of FSD-equipped vehicles on the road, the company continuously collects real-world driving data at an unprecedented scale—billions of miles of diverse scenarios. When the system encounters edge cases or driver interventions, it uploads scene data for analysis. This data trains improved models at Tesla's data centers, which are then deployed back to the entire fleet through over-the-air software updates.
Occupancy Networks and Spatial Understanding
The system uses Occupancy Networks to build a real-time 3D understanding of the vehicle's surroundings. This technology predicts what space is occupied and what's free, enabling the car to navigate around objects that don't fit neatly into predefined categories. Combined with temporal fusion—the ability to integrate visual data across multiple frames—the system maintains object permanence even when obstacles are briefly obscured.
Current Classification
Despite these capabilities, Tesla's FSD remains classified as an SAE Level 2 driver assistance system, requiring active driver supervision at all times. The technology continues to evolve through continuous software updates, with each iteration expanding the system's capability to handle increasingly complex real-world scenarios.
Owners say FSD makes rush hour and long drives easier. It shines in stop-and-go traffic and on highways—less stress, more time to enjoy the ride.
What FSD Can Handle
Recent versions (particularly V14) have demonstrated increasingly capable performance in adverse conditions. Just this week, a Tesla Model S completed the first zero-intervention "Cannonball Run" from LA to NYC—3,081 miles through extreme cold, snow, ice, slush, and rain with FSD driving 100% of the route. TESLARATI Owners have also been posting impressive results with FSD v14.2.1 navigating snowy conditions including unplowed roads and steep hills, with the system handling turns slowly and confidently.
The neural networks have been retrained with a much larger and more diverse dataset of adverse weather conditions, including terabytes of data from vehicles driving in heavy rain, dense fog, and even moderate snow.
The Limitations
The vision-only approach has an inherent vulnerability: if the cameras cannot see, the car cannot think. Artificial Intelligence World You'll sometimes see messages that a camera's vision is partially blocked and needs to be cleaned. In heavy rain, camera vision can be obstructed, triggering warnings about degraded performance Ainvest—though one driver reported completing a 4.5-hour drive through nonstop rain and snow where visibility warnings went away by themselves after a few minutes.
The Practical Reality
Rain is generally the easiest adverse condition since lane markings remain visible. Snow is more challenging when it obscures road markings, though the system is learning to "hallucinate" the road based on previous trips—if it has driven a road many times in clear weather, it knows where the lanes are even when covered in snow. Artificial Intelligence World
FSD handles rain and moderate snow increasingly well, but keeping cameras clean during stops helps maintain optimal performance.
The Full Self-Driving system is designed to be intuitive, allowing users to become proficient after a few sessions. It is advisable to begin with caution, familiarize yourself with its functionalities, and gradually build confidence as you accumulate experience.
Tesla periodically releases new features and improvements multiple times annually—without requiring a service visit. Your vehicle continues to become increasingly intelligent right in your driveway.