Tesla, a leader in the electric vehicle industry, continues to set trends with its innovative technology and design. Recently, Tesla made headlines again with a major update. On the evening of December 21st, Eastern Time, Tesla launched its latest version of the Full Self-Driving (FSD) system, Beta V12, to the public. This release, akin to a blockbuster, has set the automotive world abuzz.
Surprisingly, despite Elon Musk's confident claims that V12 would mark the end of the beta phase, reality was somewhat unexpected. Screenshots from users who received the FSD V12 update show that it still carries a "beta" label! Compared to previous versions, FSD V12 introduces a groundbreaking feature: automatic speed adjustment. This feature enhances Tesla's FSD by using AI vision technology to intelligently adjust the car’s speed based on different environments and scenarios. This is just the tip of the iceberg of Tesla's end-to-end autonomous driving capabilities.
In short, Tesla's FSD V12 not only takes its technology to the next level but also focuses more on emulating human driving behavior, making autonomous driving more human-like.
Perception Upgrade: Enthusiasm Unleashed
One of the most notable upgrades in FSD V12 is its perception system. With advanced sensor technology and algorithms, Tesla vehicles can now more accurately recognize their surroundings, including other vehicles, pedestrians, road signs, and other traffic conditions. This upgrade enhances vehicle safety and road efficiency and paves the way for future full autonomy. Recently, international users have showcased the real-world performance of Tesla FSD Beta V12. Operating without high-definition maps or judgement codes, and relying solely on data training, FSD V12 has demonstrated impressive capabilities in various complex scenarios. From rainy weather and intersections without traffic lights to unprotected left turns and responding to emergency vehicles, FSD V12 has handled these challenges with ease.
Many international owners have raved about the new version of FSD, filling comment sections with excitement. Vehicles equipped with FSD Beta V12 accurately recognize stop signs at intersections and road markings. In videos, vehicles steadily stop at the stop lines at intersections, patiently waiting for a clear path on both sides before gracefully starting and smoothly crossing intersections. At traffic light intersections, FSD V12 operates more effortlessly, recognizing overhead signals and adhering to traffic rules. When the green light illuminates, the vehicle quickly starts, while also making sure to yield to nearby vehicles. However, this system still relies on human intervention and judgement, underscoring the critical importance of ethical considerations for drivers.
Strategic Depth: A New Chapter in Navigation
In FSD V12, Tesla has made significant improvements to its navigation and route planning algorithms. The new navigation system intelligently plans driving routes, considering multiple factors like traffic conditions, road changes, and driver preferences. Moreover, the updated FSD has enhanced real-time traffic analysis capabilities, adjusting routes based on actual conditions to ensure a smoother driving experience.
Compared to Musk's previous test version, this update to FSD V12 has brought more surprises to owners! From videos released by owners, we can see several key points.
Firstly, FSD now has the ability to accurately recognize traffic lights and road signs and can navigate according to standard traffic logic. This means that in complex traffic environments, Tesla vehicles can make correct judgments and actions.
Additionally, even in conditions of low visibility such as rain or darkness, FSD continues to function effectively, enhancing Tesla's autonomous driving system's adaptability to different weather and time conditions.
Finally, when facing complex scenes with pedestrians, vehicles, and unusual objects simultaneously, FSD handles these challenges effortlessly, demonstrating the stability and reliability of Tesla's autonomous driving system in dealing with sudden situations.
The technical advancements of the public beta version FSD V12 are supported by several key contributors:
- Hardware Upgrades: The HW4.0 platform, like a magician's assistant, provides strong support for FSD, enhancing both image processing speed and road recognition accuracy.
- Big Data Training: By training on millions of video clips, FSD has learned to handle various driving scenarios effortlessly, ready for any situation.
- End-to-end Large Model Technology: This is akin to a magician's large cape, perfectly integrating perception and standards, not only speeding up data processing but also making FSD's decisions and driving behaviors quicker and more accurate.
- Shadow Mode: Tesla's shadow mode, like a mysterious spectator, silently collects valuable corner case data, providing invaluable training material for FSD to continuously break new ground.
FSD V12's end-to-end autonomous driving technology is like a futuristic driver who has broken free from the constraints of traditional coding. In this new domain, its performance is no longer bound by rigid instructions but driven by massive data and powerful computational capabilities.
With the technological power of FSD V12, Tesla utilizes rich local driving data to deliver an exceptional intelligent driving experience. Moreover, by discarding traditional instruction sets, Tesla does not need to establish a large technical team in China. Just a team of 20 engineers and hundreds of technical specialists is sufficient to ensure the smooth deployment and operation of FSD in the Chinese market.
Conclusion
Tesla's release of the new version of FSD Beta V12 can be described as the first end-to-end AI autonomous driving system in history. In last year's test drive livestream, Musk stated that this version of FSD upgrades the urban street driving stack to a single end-to-end neural network, breaking free from the constraints of traditional coding.
Through training on millions of video clips, FSD Beta V12 replaces the original 300,000 lines of explicit C++ code with the power of neural networks, giving intelligent driving a stronger capacity for thought and opening up more possibilities for a pure vision-based approach.
