Currently, the technology is only approved for sale in California and Nevada, where regulators have approved Mercedes-Benz’s Level 3 autonomous driving system. According to Fortune, as of April 11, there were 65 Drive Pilot-enabled Mercedes cars available for sale in California, and one of them has already been sold, marking the birth of California’s first surveillance-free self-driving car.

Unlike companies like Tesla that still offer Level 2 autonomous driving technology, Level 3 autonomous driving allows drivers to shift their attention to other activities in certain situations without constantly monitoring the vehicle. However, the technology also has limitations, such as being able to only be used on pre-approved routes and not being able to handle highways in other states.

Currently, this technology is only available on certain highway sections in California and Nevada during congestion periods, during the day, and when the speed limit is less than 40 miles per hour (Note: approximately 64.37 kilometers) per hour. When the vehicle is traveling on a non-pre-approved route, such as a highway in another state, the driver still needs to be alert and ready to take over the vehicle.

Still, Mercedes-Benz’s Level 3 self-driving system represents a major step forward for autonomous driving in the United States. Although companies such as Google’s Waymo and General Motors’ Cruise have more advanced Level 4 self-driving technology, they are currently only used to operate taxi services and do not sell vehicles to consumers.

The Drive Pilot system is available on the 2024 EQS sedan and S-Class sedan, and consumers can gain access to it through a $2,500 annual subscription fee. It is worth mentioning that Mercedes-Benz will start selling Level 3 autonomous vehicles in Germany as early as May 2022, with a three-year membership in the European market costing between 5,000 and 7,000 euros.

To make it easier for other road users to identify Mercedes vehicles in automated driving mode, their rearview mirrors, headlights and taillights will illuminate in special turquoise colour. Additionally, the Drive Pilot system is only available on models equipped with certain hardware, such as front-facing sensors and rear windshield cameras.

Mercedes-Benz is working on developing Level 4 autonomous driving technology and plans to bring it to the consumer market around 2030. Level 4 technology will enable an experience closer to fully autonomous driving, with the driver only having to take over the vehicle if the system fails. This means the technology must be able to safely cope with almost any unpredictable situation on the road.

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In addition, Elon Musk said in reply to netizen comments: “Almost all cars will be self-driving in the future, and maybe only 1% of manually driven cars will be used for human entertainment, just like horses today.”

Elon Musk insists that Tesla’s value is mainly based on autonomous driving. As a promoter of autonomous driving, Elon Musk stated as early as 2018 that he would launch fully autonomous driving capabilities and that by 2019, more than 1 million vehicles would have fully autonomous driving capabilities. But so far, the autonomous driving promised by Elon Musk has not been realized. Although Autopilot and FSD functions have been launched, they are still in the assisted driving stage and need to be used under driver supervision.

Elon Musk announced on social media platform X not long ago that Tesla plans to launch a driverless taxi (Robotaxi) on August 8.

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The high-speed pilot assist function can realize high-speed end-to-end automatic driving, and realize automatic up and down ramps, overtaking and lane changes, overtaking long tunnels, avoiding construction areas, and smooth driving on large curvature curves based on navigation routes. It has also achieved important results that are firsts in many industries: the first developer in the country to apply the secure version of NVIDIA Drive OS to ensure software security from the system level; the first high-end intelligent driving solution provider in the country to apply the autonomous driving proprietary cloud to ensure data integrity. regulations; for the first time, AOS smart driving middleware was applied to mass production projects and reached functional safety ASIL-B.

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Although Elon Musk has predicted that FSD V12 will change the technical route, what is surprising is that Tesla only started training this neural network-based intelligent driving algorithm at the beginning of this year. Just four months later, the new system was ready to replace the old system; eight months later, the new FSD V12 was unveiled during Elon Musk’s live broadcast.

Behind this is a changing technical route, from rule-driven to data-driven; from modular design to end-to-end. It also brings new challenges.
FSD V12: only neural networks

In general, Tesla FSD V12 has only one core feature: no rule code, only neural networks.

What’s the meaning?

Most of the common autonomous driving systems on the market adopt a modular design, including three modules: perception, decision-making, and control. Each task uses its own algorithm model. Among them, the AI algorithm is mainly used in the perception module, and the decision-making and control modules are still conventional codes based on if-else logic.

That is, the code written by the algorithm engineer will establish a set of rules for the autonomous driving system, such as stopping when the light is red, passing when the light is green, driving in the middle of the lane, etc.

Therefore, the shortcomings of this system are obvious. The rules-setting standards are determined by engineers of various companies. The driving style can easily not match the driver’s habits, resulting in a poor experience. It is better to drive it yourself.

The Tesla FSD V12 only has neural networks, which means that in the past, the major modules of perception, decision-making, and control were not needed in the design. Just determine the neural network architecture and then input the data for training.

A neural network processes all input signals and outputs driving decisions. Based on real human driving data, the system can learn how to drive and drive better.

This is the so-called transition from rule-driven to data-driven.

From the input of various environmental information, the system determines how to drive in this situation based on rules; to the training of human driving data, after the system fully learns human driving habits, it will drive itself in the actual driving environment based on the input environmental information. Decide how to open it.

If there is a situation that is not handled well, enter more data specifically for this scenario. It is a training method similar to ChatGPT, but a version more suitable for cars.

Before deciding to change the technical route, Tesla’s autonomous driving team showed Elon Musk that a system based on neural networks could handle better situations.

On a road littered with trash cans, downed traffic cones, and random obstacles, the car was able to accurately maneuver around them, cross lane lines, and break some traffic rules when necessary.

Before the live broadcast, Elon Musk also conducted a test on FSD developed based on neural networks. During a total of 25 minutes of driving, Elon Musk only stepped on the accelerator when the system was too cautious, but never touched the steering wheel. There was also a time when the system performed better than he expected.

 My human neural network fails here.

How to treat

In fact, long before Elon Musk announced that FSD V12 would become an end-to-end technical route, this concept had already emerged among autonomous driving players.

Because the end-to-end autonomous driving system is easy to develop, there is no need to write massive amounts of code in the early stage (there are more than 300,000 lines of C++ code in the FSD V11 version control stack), and there is no need for engineers to design rules in advance. Just keep inputting human driving data, and the system will learn by itself.

But this also places high demands on autonomous driving players. For example, the input must be a large amount of high-quality data to better help the system learn.

Elon Musk found that neural network-based self-driving systems only started to perform well when fed more than 1 million videos.

At the beginning of this year, Tesla had already input 10 million human driving videos into this system, and they were all screened by experienced drivers.

Tesla’s fleet of nearly 2 million vehicles around the world also provides approximately 160 billion frames of video for training every day. Tesla expects that the number of videos used for training will reach billions of frames in the future.

This is a challenge for data volume, data annotation, computing power, etc.

Moreover, the reason why end-to-end technology has not become popular among autonomous driving players on a large scale is that there is a key problem: this will increase the unexplainability of the autonomous driving system.

At this stage, end-to-end autonomous driving is still a “black box”, and there is no way to accurately explain why the system does not handle well in certain situations.

Therefore, the solution given by Tesla is to feed more data in a targeted manner if the system is not processed well during testing.

For example, during Elon Musk’s live broadcast, the system almost ran a red light. The solution he gave was to input more traffic lights, especially videos of left-turn signals.

In addition, Elon Musk also set an indicator for the team to display the number of miles traveled by the FSD system without human intervention in real time. If intervention occurs, the corresponding problem will be dealt with.

More importantly, if learning continues in this way, a new problem will arise: the system will not only learn the smooth operation of experienced drivers but also learn the behaviors of human drivers that do not comply with traffic rules.

For example, when encountering a stop sign, more than 95% of people will pass slowly rather than stop completely. This means regulators need to clearly regulate standards.

The U.S. National Highway Safety Commission is studying whether to allow autonomous driving systems to operate without fully complying with traffic regulations.

In short, the launch of the Tesla FSD V12 is indeed of great significance for autonomous driving. Now that the entire process can be AI-enabled, it is more possible to move towards AGI, that is, artificial general intelligence.

When will autonomous driving have its ChatGPT moment? The gears of fate may start turning from this moment on.

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At the same time, Tesla is also trying to set up a data labelling team in China, with a scale of about a hundred people, the report said. This is also a preparation for training the FSD algorithm.

A person familiar with the matter said that for Tesla to conduct tests in Shanghai, it needs to apply for a temporary license in Pudong Lingang, where it is registered, and after two weeks of trial operation, it must pass the approval of relevant review committees before it can obtain long-term test qualifications. It will take at least three months to obtain this qualification.

It is worth mentioning that there is information feedback from the user side. One of the vehicle system updates on August 9 involves automatic driving data collection. Users can choose whether to participate according to their own wishes.

In addition, Tesla China stated in a statement yesterday that Tesla has established a data center in China, and all data generated by selling vehicles in the Chinese mainland market will be stored in China.

FSD is a fully autonomous driving solution developed by Tesla for many years, with the goal of driving without human intervention. At present, FSD has launched a beta version in North America, and will soon push the official version to all users. Tesla CEO Musk said at the Artificial Intelligence Conference last month that FSD may have L4 or even L5 fully autonomous driving capabilities later this year.

To succeed in the Chinese market, Tesla faces many challenges. First of all, the road conditions and traffic conditions in the Chinese market are very different from those in the US market, especially in first-tier cities, where complex scenarios require more data collection and algorithm optimization. Secondly, Tesla also needs to comply with the regulatory requirements and safety standards of the Chinese market and conduct relevant tests and approvals. Finally, Tesla also needs to compete with domestic car companies and technology companies. These companies are also actively promoting high-end intelligent driving solutions and have localization advantages.

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▲ Source Mobileye’s official website

Mobileye, whose current customers include BMW, Nissan and Volkswagen, beat second-quarter estimates on the back of strong demand for its driving technology in North America and Europe, which offset the current weakness in China.

Analysts said Mobileye’s shipments in 2023-2024 will be driven primarily by Geely’s Polar Kryptonite cars, but Mobileye’s ongoing channel expansion could also be a positive catalyst for its results.

As a result of this news, Mobileye’s stock price rose 2% in the U.S. pre-market trading session.

Mobileye recently announced in Jerusalem the launch of the world’s first automotive-grade pure vision Intelligent Speed Assist solution. Officially, this is the first solution to meet the requirements of the new EU regulations and is scheduled for mass production in the fourth quarter of this year.

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Tesla is the world’s most valuable automaker, with a market capitalization of about US$800 billion, but has failed to achieve the goal of fully autonomous driving set by Elon Musk for many years.

“Although I’ve said this before, I think we’ll be able to solve the self-driving problem very quickly,” the billionaire said at the conference. “The value of the company is mainly based on self-driving, which is really our key driver of value.”

The electric carmaker said its so-called “full self-driving” software doesn’t make its vehicles truly autonomous and still requires driver supervision.

Earlier in the day, Elon Musk met French President Emmanuel Macron for the second time in more than a month, as French officials hope to persuade Elon Musk to choose France as the location for his next Tesla Gigafactory in Europe.

Elon Musk also had lunch with Bernard Arnault, the head of luxury goods giant LVMH (LVMH.PA ), and his two sons, Anthony and Alexander, who took turns being world leaders, according to people familiar with the matter. The richest man in the world, but in recent weeks, as luxury stocks fell and Tesla shares rose, Elon Musk regained the status of the world’s richest man.

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Li Wenguang said that Huawei has chosen the autonomous driving technology route of multi-sensor fusion and collaboration, which has a higher ceiling and better experience compared to Tesla’s pure vision route. According to him, “We have also seen the Tesla FSD experience videos posted by Tesla users in North America on the web, and when combined with the experience and evaluation videos of our domestic users, our smart driving experience is significantly better than Tesla’s, even in more complex road scenarios in China, compared to simple roads in North America.”

According to Li Wenguang, autonomous driving provides a service, and whether users are willing to pay depends on whether the service can solve the user’s problems and whether the experience is good enough. He points out that there are two needs for autonomous driving: safety and time. As long as these two needs can be met, there will be market space.

Li Wenguang said that autonomous driving is currently at the L2+ stage, and will develop towards L3, L4 and even driverless in the future. He expects that high-speed scenes will be the first to achieve L3-level commercialization, and scenes such as parks and basements are more suitable for driverless. The urban scenario will have to be driven with confidence on fixed routes. In addition, the parking scenario is relatively simple, and this year Huawei aims to make users park with confidence.

Finally, Li Wenguang also answered the netizens’ concern: “Is L3 autonomous driving really coming?” He said that L3 autonomous driving also involves the development of many standards and regulations, but the technical capabilities to be prepared first, in high-speed scenarios on the application is also a matter of these two years.

On April 16, Huawei’s Advanced Intelligent Driving System ADS 2.0 was released, which will not rely on high precision maps to achieve advanced assisted driving, asking the M5 Advanced Intelligent Driving Edition to debut with Huawei ADS 2.0.

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Electric drives are one of ZF’s core technology pillars, and to date, ZF’s Electric Drives Division has received a total of €30 billion in orders around the world. ZF is bringing a next-generation 800-volt electric drive system with a more efficient silicon carbide inverter, a higher power density motor and a lighter reduction mechanism; the innovative inverter technology has a faster switching frequency and low losses, with higher conductivity and heat resistance.

On the software side, ZF can offer a comprehensive combination of longitudinal, lateral and vertical chassis motion actuators to provide a complete system for the various functions of a software-defined vehicle.

ZF’s technology allows the vehicle to be controlled with six degrees of freedom without the need for a mechanical connection to the steering wheel or brake pedal.

ZF has announced that it will offer coDrive L2+ level driver assistance systems, including multi-lane changing and leading-edge memory parking assistance, for a Chinese OEM’s electric vehicle models in 2023, with the corresponding models to be launched in the Chinese and European markets successively in 2023.

The ZF Group achieved sales of 43.8 billion euros in 2022, with Asia Pacific sales, mainly in China, accounting for about 25% of the Group’s global sales, and plans to reach 30% by 2030.

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It is reported that Mercedes-Benz’s DRIVE Pilot system will be approved for use in Germany in May 2022. Last month, the system was approved for use in the United States, making the company the first automaker in the country to be approved to operate Level 3 autonomous vehicles.

In the U.S., Nevada was the first state to approve the DRIVE Pilot system, which allows self-driving cars to operate at a relatively low speed of 40 mph (about 64.37 kilometers) per hour, and only on suitable highway segments.

In addition to Nevada, Mercedes-Benz also hopes to expand the use of DRIVE Pilot system to California and other places. Previously, the company had provided certification documents to the state.

According to reports, Mercedes-Benz will apply the Drive Pilot system in the S-class and EQS models, and will deliver the first models to customers in the second half of 2023.

According to foreign media, Mercedes has quickly become the leader in the field of autonomous driving, ahead of traditional competitors such as BMW and Volkswagen, and even challenges the current market leader Tesla.

Tesla began to push the FSD beta software to some customers on the evening of October 20, 2020. The FSD beta software can almost allow the car to complete all tasks related to driving on city streets, but its level is not enough to be used in cars. Done without driver supervision. Drivers need to be constantly attentive and ready to take over the car.

Tesla’s FSD software has been in testing for more than two years so far. The company hopes to gradually approach L5 autonomous driving by improving the FSD beta software.

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