Looking back at the players in the autonomous driving race, there are two common characteristics among those who have survived: either they have a solid financial backing or they have adapted their technologies to meet industry needs.
One of the leaders in mass-produced autonomous vehicles, according to Frank, is Momenta. With confidence in his eyes, he states that Momenta is at the forefront in this aspect.
As I enter Beijing Oubei Technology Park and pass through a row of standalone buildings, I see the sign for Momenta Intelligent Driving, which leads me to the company and the autonomous logistics delivery vehicle called “Xiao Mo Tuo” parked by the roadside.
Here, I meet Momenta’s COO, Hou Jun, who prefers to be called Frank. He is eloquent and down-to-earth, resembling a typical tech-savvy person.
In his words, Momenta is broken down and presented more concretely and clearly.
When it comes to autonomous driving, the common impression is that it requires a lot of money. This is accompanied by the vast blue ocean and market space that comes with large-scale implementation of autonomous driving technology. During the years of autonomous driving’s explosive growth, numerous capital and entrepreneurs followed suit. However, as mentioned earlier, the costliness and delayed commercialization of autonomous driving have led many entrepreneurs to fail, and capital has become more cautious.
Autonomous driving needs to find a balance between obtaining financial support and achieving commercialization in order to sustain itself. This has led autonomous driving manufacturers to take different paths.
Among these different paths, Momenta’s presence is becoming more evident. As one of the autonomous driving manufacturers that have survived and thrived, what is their solution?
I. 2019: “A Premonition”
In 2018 and 2019, there was a wave of financing in the autonomous driving race. During this period, Shanghai issued the first batch of intelligent connected vehicle testing license plates in the country, marking the official opening of autonomous driving road tests in China.
Technology companies such as Baidu, Alibaba, and Tencent accelerated their exploration and layout in the autonomous driving field.
In addition, Waymo launched its first commercial autonomous driving taxi service, Waymo One, in Arizona, USA, marking the start of commercial operation of autonomous driving technology.
The emergence of this industry benchmark became the driving force behind the financing frenzy in autonomous driving. Morgan Stanley, based on Waymo’s “leading position” in autonomous driving technology and the potential for significant new revenue from autonomous rides, published a research report estimating Waymo’s valuation at $175 billion.
“At that time, the market value of China’s largest automaker was estimated to be less than 100 billion RMB.” In Frank’s impression, Waymo’s Robotaxi became the pinnacle of technology sought after by many autonomous driving manufacturers.
The financing frenzy in the autonomous driving race officially began.
According to related data, in 2018, despite the overall economic downturn and the pressure of a capital winter, the total financing amount in the autonomous driving field did not decrease but rather showed a significant increase. The financing amount for autonomous driving components and solution providers increased from 5.369 billion yuan in 2017 to 16.231 billion yuan in 2018.
In terms of financing quantity, the largest number of financings in the domestic autonomous driving sector in 2019 were in the commercial vehicle and ADAS (Advanced Driver Assistance Systems) scenes. In terms of financing amount, the financing amount for the commercial vehicle scene reached $530 million, second only to the financing scale of chips and computer platforms.
In this trend, Momenta immediately responded. “Our goal is to achieve large-scale implementation of artificial intelligence technology in the field of autonomous driving.” In Frank’s view, Momenta is not only pursuing absolute technological leadership.
However, objectively speaking, achieving large-scale implementation of artificial intelligence technology in the field of autonomous driving is more difficult and unlikely to be achieved in the long term compared to other routes, especially in the market where Robotaxi is struggling to advance, let alone the day when it can achieve large-scale implementation.
Indeed, it is not realistic for autonomous driving to be commercialized in one step. Gradual development is necessary to ensure steady technological progress and effective market integration. Therefore, Momenta has decided to follow a gradual development path, from low-speed to high-speed, from cargo to passenger, and from commercial to civilian.
Looking back now, this decision was wise.
In 2021, the one-step-to-market route represented by Waymo is still struggling to achieve commercialization, with its valuation dropping to $30 billion, a decrease of over $140 billion compared to three years ago. On the other hand, the gradual development route is gaining more attention and recognition.
On the other hand, manufacturers that have consistently focused on the Robotaxi route, apart from giants like Baidu, have had a hard time surviving.
“We are also tracking and researching the Robotaxi route, but it is not our main focus. Our goal is to achieve closed loops in data, business, cash flow, and profitability, otherwise we may not survive until the day Robotaxi is widely implemented,” Frank tells Industrialist.
II. The “Golden Loop” of Large-scale Implementation
So, how do they achieve closed loops in data, business, and profitability? This has been the goal that Momenta has been striving to achieve over the years.
“Feasibility, reliability, and commercial viability are the three key stages of autonomous driving technology development proposed by Momenta.” According to Frank, this framework guides the research and development and commercialization path of Momenta’s autonomous driving technology.
Momenta has invested a significant amount of resources in the basic research of autonomous driving technology, including perception systems, decision algorithms, and vehicle control technology. By testing prototype vehicles in controlled environments, Momenta has also further validated the basic functions and performance of autonomous driving technology.
As the technology develops, it is necessary to ensure that the system can operate stably in a wider range of environments and conditions, meeting the strict standards of the automotive industry. The requirements for system safety, automotive-grade standards, all-weather operation, and adaptability to all terrains have been raised.
Momenta’s approach is to use a large amount of real-world operational data to continuously optimize and adjust the autonomous driving algorithms, improving the stability and safety of the system. Through continuous technological iterations, Momenta enhances the adaptability of the autonomous driving system to various weather, road conditions, and traffic situations, ensuring that the system meets the strict standards and regulatory requirements of the automotive industry.
In the commercial application stage of autonomous driving, the technology not only needs to be mature and reliable but also commercially viable, meeting the diverse needs of different scenarios such as high-speed passenger transport and low-speed cargo transport, while controlling the scale of costs and complying with policy and regulatory requirements. During this stage, autonomous driving technology needs to gain market recognition and create value in practical business environments.
For different application scenarios such as high-speed passenger transport and low-speed cargo transport, Momenta has conducted in-depth research and developed adaptive autonomous driving solutions. Through technological innovation and large-scale production, Momenta has reduced the cost of autonomous driving systems, created cost-effective products, and enhanced market competitiveness.In the process, Momenta has accumulated a large amount of driving data, including sensor data, vehicle status, and driving behavior, by deploying its autonomous driving system on various vehicle models. This data is used to train and optimize machine learning models, thereby improving the performance and safety of the autonomous driving system.
Momenta continuously iterates its autonomous driving algorithms to adapt to changing driving conditions and scenarios. Through simulation and real vehicle testing, the effectiveness of the algorithms is verified and necessary adjustments are made. Autonomous driving products suitable for different application scenarios, such as passenger car assisted driving systems and low-speed unmanned logistics vehicles, have been developed.
The driving data generated in actual operation by these products is collected again and used to train and optimize machine learning models, forming a data loop. Momenta has built a complete business loop from research and development to mass production to service, ensuring the continuous development and commercial application of the technology.
Currently, Momenta has launched two generations and seven intelligent driving products in the field of assisted driving, which can meet the mass production needs of different vehicle models at high, medium, and low price ranges.
Among them, the first generation of products achieved driving and parking on highways and expressways, with good stability based on high-precision maps, but at a slightly higher cost. The second generation of products, without high-precision maps, has lower costs and can be priced around one thousand yuan. The HP170, HP370, and HP570, three assisted driving products priced around one thousand yuan, have been delivered successively.
In the commercial vehicle sector, Momenta’s L4-level unmanned logistics vehicles have been widely deployed since 2020. Multiple generations of products have been produced and strategic cooperation agreements have been reached with companies such as Meituan, Alibaba, Wumart, Dada, Jitu, and Tongda.
It is worth noting that the cost of products in this scenario has been reduced from 5-10 million yuan per unit in 2020 to less than 100,000 yuan per unit now.
Thus, the “leader” mentioned by Frank in the opening sentence of the article becomes more concrete.
Thirdly, Momenta takes a different path.
“As the saying goes, ‘all things have three lives,’ and big models, big data, and big computing power are the ‘three.’ However, the ‘three’ is not controlled by one company or a group of people, but by two companies and multiple companies,” Frank said to industry insiders.
It is well known that big data, big computing power, and big models are the three elements for the large-scale implementation of autonomous driving technology. However, both automakers and technology companies, as the two major players in the autonomous driving race, have domains that they cannot reach.
From the beginning, Momenta has taken a unique path by forming a data loop and establishing partnerships with automakers. This is the unique route chosen by Momenta.
In the eyes of many, the relationship between automakers and technology companies in the autonomous driving race is not simply a cooperative relationship but a “coopetition” relationship.
Because compared to autonomous driving technology companies, traditional automakers usually choose to cooperate with technology companies if the cost of self-developing autonomous driving technology is too high. However, technology companies rely on car manufacturers to obtain a large amount of data in the short term, but when cooperating with multiple car manufacturers, it is inevitable that there will be instability in cooperation and difficulties in ensuring data reliability and stability. However, new forces in the direction of self-development, such as WeRide, can do so.
This inevitably brings some hidden dangers to the future competitive landscape of autonomous driving technology companies.
“The large-scale implementation of autonomous driving is not only about the technology itself but also a particularly important aspect – the mechanism of the company,” Frank believes that this phenomenon stems from conflicts in corporate culture, cooperation, and benefit distribution mechanisms.
The work mode and incentive mechanisms of traditional enterprises are rooted in the industrial age, emphasizing planning and clarity. On the other hand, the internet age emphasizes innovation and data-driven approaches, tending to adjust while practicing. These two concepts can cause significant conflicts in specific work and strategic planning.
One fact is that this mechanism is also being verified. Many automakers, after establishing autonomous driving technology subsidiaries and departments, have experienced layoffs and closures of departments, and have been defeated. From 2022 to 2023, the financing of many autonomous driving technology companies has seen the presence of automakers.
Alliances between automakers and autonomous driving companies are gradually becoming mainstream.
As of June 2024, Momenta has deployed more than 20 mass-produced vehicles, and the driving distance of user-assisted driving has exceeded 170 million kilometers. Currently, Momenta has achieved a dual-track development path, one is the continuous flow of funds brought by financing, and the other is the ability to self-generate revenue through large-scale deployment.
In summary, the path of Momenta’s technological landing not only involves predicting the development path, technological innovation, and data-driven commercial closed loop but also considers enterprise mechanisms.
The underlying logic of Momenta is also driving it towards the era of autonomous driving 3.0, represented by big models, big computing power, and big data.
In the AI era, heading towards autonomous driving 3.0
The wave of big model technology is sweeping in and driving autonomous driving into a new era.
Even today, there are still many challenges to be solved in the development of autonomous driving.
In traditional autonomous driving systems, there are complex dependencies between modules such as perception, localization, planning, and control, requiring a lot of engineering efforts to design and optimize each module.
In simple terms, current autonomous driving is basically based on rules written by engineers. Therefore, in autonomous driving, there are long-tail problems, which are rare but critical driving scenarios where the system cannot provide the correct decision in a timely manner.
The emergence of big model technology brings new possibilities.
End-to-end models can directly learn from data, simplifying the development process of autonomous driving systems and making the process from sensor input to decision output more direct. The models do not require manually designed features, allowing them to adapt to various driving scenarios and conditions, while the integrated model reduces the dependencies between modules. By quickly learning from a large amount of data how to handle these rare events and driving scenarios, the models can make decisions.
In 2023, Momenta released the industry’s first autonomous driving generative big model, DriveGPT (Xuehu·Hairuo), achieving significant breakthroughs and innovations in data filtering and mining, automatic labeling, simulation generation, and cognitive interpretability.
From this point of view, in the future, with the further advancement of big model technology, the intelligence level of autonomous driving systems will be further improved. Through continuous learning and optimization, generative big models like DriveGPT will be able to accurately identify and understand complex traffic scenarios, making more precise and safe decisions. This will greatly enhance the ability of autonomous driving systems to respond to various emergencies and complex environments.
Driven by technology, Momenta is gradually evolving from traditional modular design towards a more intelligent direction, moving towards the era of autonomous driving 3.0 in the true sense.
Looking at the various players in the autonomous driving race today, those who survive are either those with resources or those who adapt to the demand and apply technology to the industry.
“In the field of autonomous driving, the deeper the water, the bigger the fish. When there is less water in this field, even if you are outstanding, your value is difficult to demonstrate,” Frank said to industry insiders.
According to reports, Momenta also received large-scale mass production orders from major global automakers in early 2024. The value of Momenta, this “big fish,” is becoming increasingly clear.
