The pace of development of autonomous vehicles has slowed in recent years due to regulatory issues and technical difficulties.
A few days ago, according to foreign media reports, Samsung Electronics has terminated the research and development of autonomous driving.
This decision is not an isolated one, as several global tech giants, including Apple, have abandoned research and development in the field of autonomous driving.
Specifically, Samsung Advanced Institute of Technology (SAIT), which is responsible for Samsung Electronics' mid- to long-term technology development, has removed autonomous driving from scheduled research projects this month to focus on robotics and other technologies. This adjustment reflects the current change in priorities for technological development.
In fact, many multinational companies have begun to slow down their investment in autonomous driving, and some have even withdrawn from this field altogether.
This is mainly because the commercialization of fully autonomous vehicles is taking much longer than expected, and at the same time, a number of self-driving-related accidents have also exacerbated concerns about the safety of the technology, leading to increased scrutiny of autonomous driving technology in the United States.
Earlier this year, Apple also announced that it was disabling the development of the Apple Car and disbanding a special project group focused on self-driving electric vehicle research. General Motors has also reduced its investment budget for the Cruise autonomous driving program, while Ford has abandoned the Level 4 autonomous driving program altogether.
At the same time, Hyundai Motor Group's U.S.-based self-driving technology joint venture, Motional, has also decided to delay the commercialization of its self-driving partnership with ride-hailing companies such as Uber Technologies and Lyft, and has laid off employees in the restructuring process to cut costs.
It's worth noting that Samsung Electronics has made significant progress in the field of autonomous vehicles, including the development of advanced semiconductors, displays, and sensors, and even last year its autonomous driving system successfully completed a 200-kilometer section of the road without driver intervention. However, considering the overall trend of the industry and the adjustment of internal R&D strategy, Samsung Electronics ultimately chose to stop the R&D work on autonomous driving.
The self-driving craze subsides
Since the mid-90s of the 20th century, with the introduction of adaptive cruise control (ACC) technology, the prototype of autonomous driving has emerged.
This technology can intelligently adjust the acceleration and deceleration of the vehicle according to the movement state of the vehicle in front, so as to realize the automatic driving of the vehicle to a certain extent.
In the 21st century, autonomous driving technology has developed by leaps and bounds, and has long surpassed the initial "Level 1" autonomous driving stage.
It is exciting to note that by 2023, Mercedes-Benz is expected to be the first to launch a batch of cars with "Level 3" autonomous driving capabilities, marking a new milestone in autonomous driving technology.
The new generation of autonomous vehicles is equipped with advanced optical sensors and radar systems, and these high-tech configurations give the vehicle the ability to operate independently for a certain period of time.
This means that, in certain situations, the driver can take their eyes off the road and the vehicle can still drive safely. The driver does not need to intervene again until the vehicle gives instructions to regain control of the vehicle.
We can foresee a higher level of autonomous vehicles becoming a reality, with "Level 4" autonomous vehicles capable of driving completely independently in specific environments, and "Level 5" autonomous vehicles, which are more advanced and can operate autonomously from any location without supervision.
However, despite the promise of autonomous driving technology, the timeline for the adoption of these high-tech vehicles has been delayed due to technical and regulatory challenges.
According to GlobalData's research projections, global sales of "Level 4" and "Level 5" autonomous vehicles are expected to be only 250,000 units by 2030, as most of the current autonomous vehicle prototypes are still in the experimental stage. But that number is expected to surge to 4 million over the next decade.
However, several high-profile accidents have sparked concerns about the safety of driverless cars. If autonomous driving programs are to be rolled out more widely in the coming decades, they must be adequately tested in the right environment and carefully rolled out gradually.
The biggest challenge to autonomous vehicle development today is the tough regulatory environment and the lack of public trust in the technology. Part of the reason for this is that glitches in some autonomous systems have led to fatal accidents, which has undoubtedly heightened public concerns about autonomous driving technology.
Sammy Chan, Automotive Sales Forecasting Manager at GlobalData, noted: "Despite the millions of miles of autonomous driving experience we have amassed, the pace of technological advancement remains relatively slow. Any setback could be so serious that it could even undermine a company's quest for full self-driving. ”
In order to prevent further accidents, we need to develop a well-developed regulatory framework to test autonomous driving under a wider variety of driving conditions.
Take, for example, the "Level 3" Mercedes-Benz S-Class, which was launched last year, which currently only allows its autonomous driving features to be used on certain roads, such as some motorways in Germany.
From the US to the EU to Singapore, regulators across the globe are currently cautious.
Nevertheless, they have already approved the testing of unmanned vehicles at specific sites. This shows that the development of autonomous driving technology is still progressing steadily, and it is expected that it will be more widely used on a global scale in the future.
Recently, discussions among some stock investors abroad have shown that the growth of the mobility industry has slowed as electric vehicles reach a so-called "impasse" (i.e., a period of stagnation before a new product or service is accepted by the public).
However, experts suggest that now is the time to focus on artificial intelligence and related products related to radar and camera sensors related to autonomous driving.
Musk's bet
A few years ago, both electric and autonomous vehicles stocks were popular with investors.
However, EV demand has failed to keep pace with supply, with a number of companies such as Fisker, Lucid Motors and Polestar lowering their production guidance for 2023.
Traditional automakers such as Ford and General Motors have also taken a cautious stance on their EV investments, and even Tesla has been slow to build a new factory in Mexico.
As a result, autonomous driving is also being closely watched. Last year, Cruise, which is backed by General Motors, suspended operations after a collision. Tesla CEO Elon Musk has also believed that much of its valuation is related to its self-driving business, and the company is also facing a crash investigation.
But Musk has made big bets on self-driving cars, such as a robotaxi planned to be launched in August. Previously, Tesla's FSD (Full Self-Driving) only used cameras to work, which was almost the opposite of the entire autonomous driving industry, which generally considered lidar essential for any fully autonomous vehicle.
As a result, there is a huge question: whether Tesla can build a safe self-driving car with its current methods, which is deeply worrying considering that Musk is betting the future of the entire company on unlocking this technology.
However, Musk seems to have realized that what he did was wrong, as Tesla soon bought $2 million worth of lidar from Luminar.
This shift may seem insignificant, but it could save Tesla.
Why is Musk betting entirely on autonomous driving? Tesla has ditched the highly anticipated Model 2 in favor of a robotaxi on the same platform. It also halted the development of all-in-one die casting, which could make all Tesla models cheaper to manufacture.
Musk not long ago fired core talents such as battery development supervisors, vehicle development supervisors, and operations supervisors, and even disbanded the teams involved in these projects!
This appears to be a cost-saving move to dedicate as much money as possible to developing Tesla's FSD AI into a legally fully autonomous system.
In other words, Musk is sacrificing all of Tesla's strengths in the field of electric vehicles in order to achieve the results of self-driving cars.
It has been said that "autonomous driving systems contain hundreds of CPUs and software modules, including sensors, actuators, complex algorithms, machine learning systems, radar, lidar, cameras, and more." Even if the accuracy of each subsystem, the system is 99%, more than 100 of them will reduce the accuracy of the entire system to less than ...... 37%”。
And the safety of FSD based on the vision scheme is greatly reduced, which is confirmed by Tesla's recently released data. That's why almost all other autonomous driving programs combine lidar with cameras, radar, and ultrasonic sensors to provide the system with enough redundancy to manage complex conditions.
Now, all eyes are on Tesla, and investors are hesitant to shift the company's entire future focus on self-driving technology.
Even the slightest hint of robotaxi danger can have catastrophic effects. Musk simply can't afford to take any chances, so this lidar order is for the first robotaxi, which is also the first sign that FSD will adopt lidar technology in the coming years.
According to relevant information, Tesla is expected to launch a Model 2-based robotaxis later this year. It is reported that the last time he came to China, Musk even proposed to China to test this robotaxi on the road, which the Chinese side was very happy to accept. So, to recap, Tesla last month received permission to test its full self-driving technology in China.
Tesla's rapid adoption of lidar makes sense, as it makes it more likely that Musk's huge bet in the field of autonomous driving will stick around.
However, it is far from certain that it will pay off. We don't even know if current AI technology will be able to achieve the consistency and safety required for self-driving cars, as AI training and development are starting to show diminishing returns.
There are other questions, such as how to adapt these lidars to Tesla cars with FSD, which promises to eventually achieve self-driving.
Tesla also doesn't have a lot of real-world LiDAR driving data, and they need a lot of data to train FSD AI to use this new type of data.
On top of that, Tesla hasn't confirmed any lidar plans yet.