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Tesla patent reveals Autopilot’s efficient method to enhance object identification
Tesla has a new patent that aims to improve the accuracy and efficiency of identifying objects inside images, as captured through its vehicle’s Autopilot cameras.
The patent, titled “Enhanced Object Detection for Autonomous Vehicles Based on Field View,” outlines Tesla’s plan to focus high computational requirements on objects that are more critical for self-driving, while downsampling less critical image data.
The patent states, “There may be…image sensors positioned at different locations on the vehicle. Certain image sensors, such as forward-facing image sensors, may thus obtain images of a real-world location towards which the vehicle is heading. It may be appreciated that a portion of these images may tend to depict pedestrians, vehicles, obstacles, and so on that are important in applications such as autonomous vehicle navigation.”
After determining the type of object that’s before a vehicle, “the particular field of view may be cropped from an input image. A remaining portion of the input image may then be downsampled. The high resolution cropped portion of the input image and the lower resolution downsampled portion of the input image may then be analyzed by an object detector.”
- Tesla Autopilot (Source: Elon Musk | Twitter)
- Credit: YouTube | JuliansRandomProject
Tesla vehicles utilize a series of eight cameras, or sensors, to identify and recognize real-world objects. The cameras obtain these images, which are sometimes pedestrians, other vehicles, animals, or other obstacles that are important to not only the safety of the driver in the Tesla vehicle but others as well. It is crucial that the cameras recognize these objects accurately and in real-time without any delay.
- Tesla’s “Enhanced Object Detection for Autonomous Vehicles Based on Field View.” (Credit: U.S. Patent Office)
- Tesla’s “Enhanced Object Detection for Autonomous Vehicles Based on Field View.” (Credit: U.S. Patent Office)
- Tesla’s “Enhanced Object Detection for Autonomous Vehicles Based on Field View.” (Credit: U.S. Patent Office)
Tesla CEO Elon Musk has mentioned in the past that Autopilot’s core code and 3D labeling is being finished. Once completed, the electric carmaker can efficiently roll out more functionalities of its Full Self-Driving suite.
3D labeling is an integral part of the FSD suite because it allows the Neural Network to process information more efficiently and can help Tesla’s vehicles learn about rare and unforeseen occurrences on the road. Anyone who has ever ridden in a car knows that expecting the unexpected is one of the best ways to avoid an accident. With over 3 billion miles of Autopilot driving under the company’s belt, Teslas have seen a lot more than any human being will ever see.
The importance of 3D labeling and accurate object identification is crucial to Tesla’s eventual rollout of a “feature complete” Full Self-Driving suite. Tesla has continued to improve driving visualizations in vehicles that operate with Hardware 3 by recognizing objects on the road that could be a barrier between the vehicle and safe travel. It seems the company’s primary focus with this patent is to dial in on the effectiveness of the car’s cameras and sensors, allowing for a more accurate depiction of what lies on the road ahead.
Read Tesla’s patent for Enhanced Object Detection for Autonomous Vehicles Based on Field View below.
ENHANCED OBJECT DETECTION FOR AUTONOMOUS VEHICLES BASED ON FIELD VIEW by Joey Klender on Scribd
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Tesla FSD fleet is nearing 7 billion total miles, including 2.5 billion city miles
As can be seen on Tesla’s official FSD webpage, vehicles equipped with the system have now navigated over 6.99 billion miles.
Tesla’s Full Self-Driving (Supervised) fleet is closing in on almost 7 billion total miles driven, as per data posted by the company on its official FSD webpage.
These figures hint at the massive scale of data fueling Tesla’s rapid FSD improvements, which have been quite notable as of late.
FSD mileage milestones
As can be seen on Tesla’s official FSD webpage, vehicles equipped with the system have now navigated over 6.99 billion miles. Tesla owner and avid FSD tester Whole Mars Catalog also shared a screenshot indicating that from the nearly 7 billion miles traveled by the FSD fleet, more than 2.5 billion miles were driven inside cities.
City miles are particularly valuable for complex urban scenarios like unprotected turns, pedestrian interactions, and traffic lights. This is also the difference-maker for FSD, as only complex solutions, such as Waymo’s self-driving taxis, operate similarly on inner-city streets. And even then, incidents such as the San Francisco blackouts have proven challenging for sensor-rich vehicles like Waymos.
Tesla’s data edge
Tesla has a number of advantages in the autonomous vehicle sector, one of which is the size of its fleet and the number of vehicles training FSD on real-world roads. Tesla’s nearly 7 billion FSD miles then allow the company to roll out updates that make its vehicles behave like they are being driven by experienced drivers, even if they are operating on their own.
So notable are Tesla’s improvements to FSD that NVIDIA Director of Robotics Jim Fan, after experiencing FSD v14, noted that the system is the first AI that passes what he described as a “Physical Turing Test.”
“Despite knowing exactly how robot learning works, I still find it magical watching the steering wheel turn by itself. First it feels surreal, next it becomes routine. Then, like the smartphone, taking it away actively hurts. This is how humanity gets rewired and glued to god-like technologies,” Fan wrote in a post on X.
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Tesla starts showing how FSD will change lives in Europe
Local officials tested the system on narrow country roads and were impressed by FSD’s smooth, human-like driving, with some calling the service a game-changer for everyday life in areas that are far from urban centers.
Tesla has launched Europe’s first public shuttle service using Full Self-Driving (Supervised) in the rural Eifelkreis Bitburg-Prüm region of Germany, demonstrating how the technology can restore independence and mobility for people who struggle with limited transport options.
Local officials tested the system on narrow country roads and were impressed by FSD’s smooth, human-like driving, with some calling the service a game-changer for everyday life in areas that are far from urban centers.
Officials see real impact on rural residents
Arzfeld Mayor Johannes Kuhl and District Administrator Andreas Kruppert personally tested the Tesla shuttle service. This allowed them to see just how well FSD navigated winding lanes and rural roads confidently. Kruppert said, “Autonomous driving sounds like science fiction to many, but we simply see here that it works totally well in rural regions too.” Kuhl, for his part, also noted that FSD “feels like a very experienced driver.”
The pilot complements the area’s “Citizen Bus” program, which provides on-demand rides for elderly residents who can no longer drive themselves. Tesla Europe shared a video of a demonstration of the service, highlighting how FSD gives people their freedom back, even in places where public transport is not as prevalent.
What the Ministry for Economic Affairs and Transport says
Rhineland-Palatinate’s Minister Daniela Schmitt supported the project, praising the collaboration that made this “first of its kind in Europe” possible. As per the ministry, the rural rollout for the service shows FSD’s potential beyond major cities, and it delivers tangible benefits like grocery runs, doctor visits, and social connections for isolated residents.
“Reliable and flexible mobility is especially vital in rural areas. With the launch of a shuttle service using self-driving vehicles (FSD supervised) by Tesla in the Eifelkreis Bitburg-Prüm, an innovative pilot project is now getting underway that complements local community bus services. It is the first project of its kind in Europe.
“The result is a real gain for rural mobility: greater accessibility, more flexibility and tangible benefits for everyday life. A strong signal for innovation, cooperation and future-oriented mobility beyond urban centers,” the ministry wrote in a LinkedIn post.
News
Tesla China quietly posts Robotaxi-related job listing
Tesla China is currently seeking a Low Voltage Electrical Engineer to work on circuit board design for the company’s autonomous vehicles.
Tesla has posted a new job listing in Shanghai explicitly tied to its Robotaxi program, fueling speculation that the company is preparing to launch its dedicated autonomous ride-hailing service in China.
As noted in the listing, Tesla China is currently seeking a Low Voltage Electrical Engineer to work on circuit board design for the company’s autonomous vehicles.
Robotaxi-specific role
The listing, which was shared on social media platform X by industry watcher @tslaming, suggested that Tesla China is looking to fill the role urgently. The job listing itself specifically mentions that the person hired for the role will be working on the Low Voltage Hardware team, which would design the circuit boards that would serve as the nervous system of the Robotaxi.
Key tasks for the role, as indicated in the job listing, include collaboration with PCB layout, firmware, mechanical, program management, and validation teams, among other responsibilities. The role is based in Shanghai.
China Robotaxi launch
China represents a massive potential market for robotaxis, with its dense urban centers and supportive policies in select cities. Tesla has limited permission to roll out FSD in the country, though despite this, its vehicles have been hailed as among the best in the market when it comes to autonomous features. So far, at least, it appears that China supports Tesla’s FSD and Robotaxi rollout.
This was hinted at in November, when Tesla brought the Cybercab to the 8th China International Import Expo (CIIE) in Shanghai, marking the first time that the autonomous two-seater was brought to the Asia-Pacific region. The vehicle, despite not having a release date in China, received a significant amount of interest among the event’s attendees.




