China’s High-end Autonomous Driving is Speeding Up
Autonomous Driving Industry Has Shown Explosive Growth
Thanks to factors such as technological progress and cost reduction, high-end autonomous driving ushered in a period of accelerated development in 2021, and some brokerages defined 2021 as the first year of the development of China’s autonomous driving industry chain.
Public information shows that since the beginning of this year, the autonomous driving industry has shown explosive growth, and various companies are seizing the commanding heights of high-end autonomous driving. During the Shanghai Auto Show in April this year, Huawei demonstrated its autonomous driving technology and realized the launch of its high-end autonomous driving ADS on the Polar Fox Alpha S Huawei HI version.
In terms of traditional car companies, GAC and Changan have respectively announced their own plans for the advancement of L4 autonomous driving technology. Among them, GAC Group has developed L4 autonomous vehicles together with Huawei and plans to mass-produce them in 2024; Changan announced that In 2022, L4 intelligent networked cars will be launched in the market. In terms of new forces, the new car W6 launched by Weimar this year already has the L4 level automatic driving function in specific scenarios.
Benefiting from the acceleration of vehicle companies in the field of autonomous driving, leading Chinese autonomous driving solution companies such as Pony.ai and Weride will also complete C/C+ rounds of financing in 2021.
According to the analysis of CMB International Securities, the pursuit of a sense of science and technology by the younger generation of Chinese consumers puts the demand for autonomous driving on the eve of the outbreak. Although L4+ level full-scenario autonomous driving still faces technical, legal, and regulatory restrictions, there is no doubt that the industrialization process of autonomous driving far exceeds previous market expectations. According to forecasts, the sales of autonomous driving vehicles above the L2 level are expected to reach 17.72 million vehicles in 2025, and the compound growth rate from 2020 to 2025 will reach 42%.
Baidu Driving Robot Vehicle
On August 18, Baidu, which has been deeply involved in the field of autonomous driving for a long time, released a car robot that cancels the basic configuration of traditional cars such as steering wheels and pedals and has L5 autonomous driving. Although the product is still in the conceptual stage, Baidu’s move still made an impression in the autonomous driving sector.
CITIC Securities pointed out that previously, the market had big differences in the industry status and commercialization prospects of Baidu’s intelligent driving. However, combined with Baidu’s recently launched autonomous driving products, its commercialization path is clearer and will open up greater valuation flexibility for the company.
It is reported that in addition to the release of car robots, Baidu has also released a new and upgraded unmanned car travel service platform-” Carrot Run”. Prior to this, Baidu’s unmanned vehicles had opened Robotaxi shared unmanned vehicle travel services in Beijing, Guangzhou, Changsha, and Cangzhou, and opened normal operations to the public. Up to now, Baidu’s autonomous driving travel service has received 400,000 customers, and the business will expand to 30 cities in the next 2–3 years.
High-end Autonomous Driving Technology is the Key
The industry generally believes that the autonomous driving industry has entered the second half of the competition, and large-scale commercial operations have become the focus of the development of the entire industry. Zhang Jian, co-founder, and CEO of Superstar Future told the Securities Times reporter that the current global auto industry is facing a profound change, and the protagonist of this change must be high-end autonomous driving technology.
Under the premise that the prospect of industrial transformation is very certain, whether it is traditional vehicle companies, new car companies, and crossovers, they will feel unprecedented pressure. In order to maintain their existing competitiveness, companies must seize the commanding heights of high-end autonomous driving technology.
Data Annotation Service Behind Self-driving Industry
The mainstream algorithm model of autonomous driving is mainly based on supervised deep learning. It is an algorithm model that derives the functional relationship between known variables and dependent variables. A large amount of structured labeled data is required to train and tune the model.
On this basis, if you want to make self-driving cars more “intelligent”, and form a closed loop of the business model for self-driving applications that can be replicated in different vertical landing scenarios, the model needs to be supported by massive and high-quality real road data.
In the field of autonomous driving, data annotation scenes usually include changing lanes and overtaking, passing intersections, unprotected left and right turn without traffic light control, and some complex long-tail scenes such as vehicles running red lights, pedestrians crossing the road, and roadsides as well as illegally parked vehicles, etc.
The current artificial intelligence is also called data intelligence. At this stage of development, the more layers of the neural network, the larger amount of labeled data is needed. For deep learning, data is meaningful only if it is well labeled.
Common Data Labeling Types Include:
- 2D Bounding Boxes
- Semantic Segmentation
- Lane Marking
- Video tracking annotation
- Point Annotation
- 3D Object Recognition
- 3D Segmentation
- Sensor Fusion: Sensor Fusion Cuboids/Sensor Fusion Segmentation/Sensor Fusion Cuboids Tracking
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