A brand new entry ticket defined by the new wave of “people-made cars”
The “new power of car manufacturing” currently on the market was mostly founded in 2014 and 2015. Several companies have emerged as the leaders, each with its own unique strengths and experiencing various challenges that provide valuable lessons for future entrants. Taking a look back at the first half of the battle from a mid-point perspective, we can get a better picture of the new entry ticket they have defined.
At present, the top new car manufacturing powers consist of three companies that have delivered over 10,000 vehicles each in the first quarter of this year. They are the well-deserved leader in China’s new car manufacturing sector, NIO, with 20,060 vehicles delivered, XPeng Motors, which has just released its third car model with 13,340 vehicles delivered, and Li Auto, which has secured a place in the first tier through the sales of its single car model, the ONE, with 12,579 vehicles delivered. If there is one thing that they all have in common, it is a focus on addressing range anxiety, which is the biggest obstacle for users to switch from traditional fuel vehicles to pure electric vehicles. NIO has invested heavily in battery swapping networks, XPeng Motors has achieved 700+ km NEDC range on its P7 extended range version, and Li Auto has adopted range extender technology for its first car model, the ONE. These seemingly different approaches aim to solve the same problem and lead to the ultimate sacrifice–eliminating range anxiety.
The technical strength behind these solutions has become the foundation of these new car manufacturing powers during the early days, but this foundation is only passing grade-level. Every new power that has successfully made its way to the top has taken a different route, whether it’s strong services, user experience, or software and hardware interaction. However, all of them have emphasized intelligent cabins and autonomous driving as selling points for their products.
Compared to traditional manufacturers who have adopted functional configuration methods to improve the cabin, new car manufacturers have already opened up a brand new battlefield in the intelligent cabin. Basic driving functions, entertainment, and communication functions are essential, while the integration of mobile Internet services in APPs has become the bare minimum requirement. The focus of these efforts has shifted towards proactive human-machine interaction and diversified application ecosystems, attempting to develop more application scenarios for the cabin space of cars. These new development directions call for new requirements for the vehicle’s in-car perception capabilities, the multi-modal AI technology and computational capability of the car’s intelligent hardware, and the cloud ecosystem platform behind the operating systems of these cars.
Similarly, intelligent driving has evolved from the previous method of stacking functional points for active safety and assisted driving systems to higher-level, longer-term, semi-autonomous driving functions that require less intervention. The tedious operation of a single functional point has been replaced by more universal application scenarios and the state of assisted driving that needs to be activated or taken over. Such changes present new requirements for the hardware perceptual ability, underlying algorithms, data models, and computing power of in-vehicle assisted driving systems.
Apart from the three-electric hard strength that serves as the passing line, a user-friendly intelligent cockpit and truly available intelligent driving have become essential skills for the leading players of these new automakers. And this should also be the entry ticket for players who enter the “people’s car making” era.
Newcomers and the Path They Must Take to Succeed in the “People’s Car Making” Era
Since the early players of the new automakers have defined a brand new entry ticket, how should these latecomers who began to join the market last year narrow the gap with the “predecessors” in essential skills and develop new skill points to achieve a leapfrog?
As the essential skills for new automakers, intelligent cockpit and intelligent driving will transform the car from a simple means of transportation into a good steed that understands you, and begin to gradually free the driver’s hands, eyes, and brain. Together, they can expand the possibilities of the car beyond its primitive identity as a means of transportation.
Newcomers from consumer electronics and internet industries who enter the “people’s car making” era will undoubtedly rely on their existing advantages in their past industries to emphasize the originality and advantages of their products compared to other first-mover competitors. However, the advantages of these new entrants are more focused on user experience or ecological extension, rather than the mechanical attributes inherent in the automobile industry or the interaction between autonomous driving and intelligent cabin favored by emerging powers. These companies still need to lay a solid foundation on the basic dimensions that have been established as the new evaluation system for new car makers in the early stages of new car making to leverage other advantages they possess.The requirements of intelligent cockpits and intelligent driving products elevate automobiles from ordinary transportation tools to true mobile intelligent terminals. This places new demands on the ability of vehicles to perceive, decide, plan, and interact. These requirements for vehicle intelligence ultimately rest on the computing power of the vehicle, much like the chip arms race in the computing power of smartphones in the past few years. Intelligent automobiles will also follow suit in the chip arms race that will determine the computing power of the entire vehicle intelligence platform.
Similar to the competition among multiple chip suppliers in the past for smartphone chips, there are multiple choices for smart car chips. In the intelligent cockpit field, Qualcomm’s 820A, the upcoming 8155 and 8195, and the domestic AI chip companies such as Horizon’s Halo 2.0 and Halo 3.0 based on its Journey 2 and Journey 3 chips are more well-known. In the intelligent driving field, there is NVIDIA’s Xavier which has already been implemented, the upcoming Orin in the end of this year or early next year, Intel’s MobileEye’s Q4 and Q5, Huawei’s newly released MDC series, Horizon’s Journey 2 and Journey 3 that have already been implemented for the past two years and Journey 5 and Journey 6 that will be produced subsequently.
The entrance ticket for intelligentization defined by the current new car makers will become a competition of intelligent computing power between new entrants in the “mass manufacturing of cars for all” era, which is a must-go for them.
The Path to Integration of Intelligent Cockpits and Intelligent Driving
The competition of intelligent computing abilities ensures that intelligent cockpits and intelligent driving will no longer be bound by hardware capabilities and fragmented function points that were previously arranged by feature configuration methodologies, but provide a unified and complete driving experience. Furthermore, intelligent cockpits and intelligent driving cannot be separated into two independent subsystems. Only by working together and creating unified experiences can we break through the crowded “mass manufacturing of cars for all” era and truly achieve the vision of software-defined cars.
The evolution of intelligent cars is based on the evolution of the vehicle computing platform, from the initial distributed computing and single subsystems having their own ECU, to domain controller logic and integrated control operation based on functional divisions, and finally to high-speed centralized operation and intelligent distribution of computing power to achieve the entire vehicle computing ability.
Against the backdrop of the continuous integration and evolution of the vehicle computing platform, the perception capability of the vehicle has been integrated to form a fusion perception center. The upper-layer applications in the architecture can then provide a more unified and seamless user experience by leveraging these perception results.
An example of this is Horizon Robotics’ solution for connecting the interior and exterior of the car. By fusing information from the external visual perception, internal visual perception, and voice perception of the car, intelligent cars can identify user intentions and understand user behavior and habits based on scenario-based analysis and understanding, breaking down the boundary between the intelligent cockpit interaction and the intelligent driving decision-making. This makes it possible to achieve a smoother human-machine co-driving experience by breaking down the boundaries between single user initiative and single assisted driving initiative.
On the one hand, this boundary-breaking solution allows users to gradually free their hands, eyes, and brains with the support of intelligent driving, and fully utilize the experience enhancement brought by the intelligent cockpit. On the other hand, after the intelligent cockpit obtains internal perception information, it can fully understand the user’s status and intentions, and communicate external vehicle information status to the user to ensure smooth and safe intelligent driving experience.
By integrating the intelligence inside and outside of the car, people can understand the decision-making and execution of the machine more easily and intervene and understand the vehicle system behaviors more conveniently and easily. At the same time, machine can also understand human behavior habits, proactively intervene in dangerous situations, and establish a relationship of trust between humans and machines to achieve human-machine co-driving. This makes the car not only a tool for mobile travel or a simple entertainment and office space, but also an intelligent robot assistant with human-machine trust and dependence.
On the road to the coordinated integration and mutual improvement of the intelligent cockpit and intelligent driving, it may become a new path for the “mass production of cars” era to break through the predicament and achieve long-term competitive goals and move towards a better future.
This article is a translation by ChatGPT of a Chinese report from 42HOW. If you have any questions about it, please email bd@42how.com.