Why do you always misunderstand driverless?

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At the end of March this year, Wang Jin, senior vice president of Baidu and former head of the autonomous driving department, announced his departure from Baidu to start his own company, Jingchi Technology, officially entering the field of driverless car startups. Shortly after, the company obtained a road test license from the California DMV (California Vehicle Authority). Let’s take a closer look at what the car electronics editor had to say about this development.

Wang Jin’s exit wasn’t entirely unexpected. In recent years, it has been a golden time for technical talents to start their own businesses. For instance, in 2016, Tiancheng, one of Baidu's youngest engineers and a top 10 engineer, left Baidu to found Pony.ai. The company also received a road test license from the California DMV. Similarly, Yu Kai and Huang Chang, who were deputies of Li Yanhong and key architects in the deep learning lab, left Baidu to establish Horizon Robotics. They later demonstrated an ADAS (Advanced Driver Assistance System) that could detect lanes, vehicles, and pedestrians on real vehicles. Later, Wu Enda also left and recently launched a new project called Deeplearning.ai, with speculation that it may focus on building essential infrastructure for AI technology.

As mentioned, several former Baidu employees have started their own companies. A common trait among them is that they are all involved in the revolution of autonomous driving.

Did you misunderstand driverless cars?

Driverless and autonomous driving are two completely different concepts. To be precise, autonomous driving should be referred to as “assisted driving,” while full automation can be called driverless. In a driverless vehicle, cloud data and more advanced algorithms replace the human driver as the “brain” of the car. In this world, humans can switch freely between being passengers or drivers. You decide where to go, when to stop, and the car acts like an invisible taxi driver, following your commands. Google even believes that driverless cars don’t need steering wheels, as these manual controls are seen as remnants of outdated technology.

On the other hand, autonomous driving systems can also control the vehicle, but they will return control to the driver when necessary. If an accident occurs under autonomous driving conditions, the law might not necessarily blame the car. This was evident in the unresolved Tesla incident in the U.S.

Compared to autonomous driving, driverless technology is a step further and represents the ultimate goal of automotive evolution, often referred to as fully autonomous driving. For example, Google’s driverless car doesn’t have a steering wheel or pedals—just a start and stop button. Once inside, you set your destination, and the car handles the rest. However, the driverless car Baidu tested on the road was still essentially a vehicle with autonomous features.

Currently, the technical routes for autonomous driving have split into two main paths: ADAS (Advanced Driver Assistance Systems) and artificial intelligence. One approach focuses on gradually automating through ADAS, while the other uses AI to directly enter the realm of autonomous driving. Both paths aim toward full autonomy, which is considered the ultimate stage of vehicle development.

A Revolution of “Everyone’s Participation”

The development of the automobile industry has brought many challenges, including traffic congestion, air pollution, and safety risks caused by human error. As private car ownership increases, utilization rates remain low. During driving, complex road conditions and unstable driver states lead to serious safety hazards, such as frequent accidents on highways. In China, according to recent government directives, traffic safety has surpassed coal mine safety as the top concern for public security.

This isn’t just a Chinese issue—it’s a global challenge faced by cities worldwide. Automated driving seems to be the solution people have found for these problems (which explains why so many companies are competing fiercely to get involved). With the accumulation of data and technological progress, all parties are racing ahead. Under intense competition, the trend toward driverless vehicles is unstoppable.

Seizing this opportunity, we’ve compiled a list of domestic and international startups involved in the driverless field for your reference.

The above image is just a partial list of startups entering the driverless space. From the perspective of various players in the automotive industry, everyone wants to capture important positions in the next generation of vehicles. Although many think of driverless projects as tech company initiatives, traditional car manufacturers are also making significant efforts in this field.

At CESAsia this year, Honda showcased a concept car called "HondaNeuV," equipped with an "emotional engine" that can assess the driver’s mental state and assist in safe driving based on expressions and tone. It can also learn the driver’s lifestyle and preferences, offering personalized suggestions accordingly.

At CES 2017 in Las Vegas, Hyundai’s IONIQ Electric completed a day-and-night autopilot road test and received a Level 4 rating from the American Society of Automotive Engineers.

Traditional car manufacturers focus more on the performance of their vehicles in the driverless space, leveraging their decades of experience in manufacturing and design. Moreover, they tend to be more cautious, such as retaining steering wheels and brakes, to preserve the driving experience and user control.

Interestingly, a market research agency recently released a list of 18 global driverless car manufacturers in a report, ranking them. The top five were Ford, General Motors, Renault-Nissan, Daimler, and Volkswagen—five traditional car manufacturers.

Domestic manufacturers are also making strides. In June 2015, BAIC and Didi signed a strategic cooperation agreement to work together in the driverless field. In 2011, the National Defense University of Science and Technology and FAW Group completed the development of the Red Flag HQ3 driverless car, though no further updates have been reported. BYD and Singapore Labs reached a joint research agreement to develop driverless vehicles, while Geely relies on Volvo’s safety technology for testing. GAC collaborates with the Chinese Academy of Sciences for driverless tests, and SAIC works with AVIC on similar projects.

Unlike traditional car companies focusing on upgrading intelligent assistant systems, internet companies aim to eliminate the steering wheel altogether using cloud computing, big data, and AI. This represents a different technical route.

This choice is closely tied to the tech DNA of internet companies. Additionally, the business logic behind it creates a difference in focus: car companies launch self-driving cars primarily from the perspective of active safety and still rely on car sales for profit. Meanwhile, internet companies use cars as a gateway to enhance driving experience and explore value-added opportunities once drivers are freed up.

In terms of chip makers, Intel spent $15.3 billion (about 105.6 billion yuan) to acquire Mobileye, a leading supplier of self-driving hardware. Other chipmakers like Qualcomm and NVIDIA are also heavily investing in the autonomous driving space.

Shortly after Intel acquired Mobileye, its rival Nvidia announced a partnership with Bosch to jointly develop an AI-based autopilot system. They also introduced the Xavier chip, designed to handle various levels of autonomous driving tasks. The resulting system will be sold to all automakers.

Previously, Qualcomm acquired NXP, a major player in automotive semiconductors, while Freescale, another strong player in automotive chips, was also part of the acquisition.

Google and others in the driverless space

To better distinguish different levels of autonomous driving technology, SAE International released a six-level classification system in 2014. The U.S. National Highway Traffic Safety Administration originally had its own system but adopted the SAE standard in September 2016.

The SAE classification divides autonomous driving into six levels, from 0 to 5, as shown below:

Why do you always misunderstand driverless?

Most cars currently in use fall between levels 0 and 1. Features like cruise control and driver-assist systems are classified as level 1 or 2. Tesla’s Autopilot is at level 2.

The existence of level 3 is somewhat controversial. According to the definition, the driver must be ready to respond to system requests and handle situations the system can't manage. This means drivers can't play games or browse the web. While level 3 exists technically, its practical application is questionable.

Many companies are working on level 4, such as Drive.ai, Baidu Autopilot, Uber, Tesla, and BMW. Level 4 is widely seen as having clear commercial potential.

Google, which popularized the concept of driverless cars, takes a different approach by aiming for level 5, full autonomy. This is different from most automakers and internet companies, which are progressing step by step. Google's strategy is to reach the top of the pyramid from the start.

Cao Xudong, founder of Momenta, once told us, “Google is doing driverless cars, but the path is too long. Despite strong funding and R&D capabilities, it hasn’t commercialized yet. The main reason is the current commercialization process. If there are issues, it’s because the core problems haven’t been solved.”

Alphabet, Google’s parent company, seems focused on business interests. When it sold Boston Dynamics to SoftBank, it was speculated that the company might not be able to produce a marketable product soon. For Google’s driverless car initiative, it’s impossible to move into that field immediately. But if it wants to commercialize quickly, it must follow the rules of the game and evolve step by step.

It's easy to break into the game

Many companies are drawn to the driverless car market. No one wants to miss out on such a huge opportunity. People believe that drones will eventually become a reality.