Please fill in your name

Mobile phone format error

Please enter the telephone

Please enter your company name

Please enter your company email

Please enter the data requirement

Successful submission! Thank you for your support.

Format error, Please fill in again


The data requirement cannot be less than 5 words and cannot be pure numbers

How Data Labeling Service Empowers Intelligent Driving?

From:Nexdata Date:2024-04-07

2021 is called the first year of China’ s intelligent cars. At the WAIC 2021, many manufacturers and OEMs showcased the latest intelligent driving products and technology, indicating the blooming development in the field of intelligent driving.
Inceptio Technology showcased two intelligent-driving heavy truck mass-produced models
Alibaba showcased the latest unmanned logistics vehicle “XiaoManLu”

Relevant agencies predict that by 2030, intelligent cars will account for more than 40% of the overall travel mileage, and the penetration rate of fully intelligent new cars can reach 10%. According to the data from the CPCA, the scale of China intelligent driving market will continue to grow in the next five years. By 2024, the scale of the intelligent driving market is expected to exceed 100 billion yuan. Driven by huge market dividends, numerous companies are competing on the track of intelligent driving.

Challenges of Intelligent Driving

Although the intelligent driving has been rapidly developed, it also faces many problems. At present, the main problem is that artificial intelligence is not so intelligent. Complex traffic scenes and uncontrollable random factors will challenge the perception of AI. Therefore, improving the perception of AI becomes the challenge of the future development of intelligent driving.

As is known, Data, Algorithms, and Computing are the three indispensable elements of AI. Among them, data plays a supporting role in enhancing the perception of AI. At present, the main way to solve the perception problem is to feed piles of training data to the algorithm through supervised learning, so that the algorithm models get universal perception capabilities. The balloons on the road, the dummy, the advertisement on the car body, the reflection of the buildings, etc., which may be difficult to imagine for us, also need to be fed to the algorithm one by one, to ensure that the algorithm can correctly perceive.

Intelligent Driving Data Solutions

As the first listed company in China’s AI data service industry, Nexdata’s core business is to provide integrated data solutions, including high-quality training datasets, data customization services, data labeling platform deployment, etc.

In the field of intelligent driving, Nexdata provides a variety of customized data labeling services:

2D Vehicle/Pedestrian/Traffic Sign Boxing

It’s applied to the basic recognition of vehicles and pedestrians.

Vehicle Polygon

Drivable area labeling and objec classification can train intelligent cars to follow other cars or change lanes on the road.

3D Cube

3D cube labeling can help to train intelligent cars to judge the volume of passing or overtaking vehicles.


Polyline labeling can help to train intelligent cars to drive according to the lane rules

Semantic Segmentation

The segmentation of different areas can help intelligent cars to recognize the real-world drivable areas.

Point Cloud

Point cloud is mainly applied to the construction of VR training scenes for intelligent driving.

In addition, Nexdata supports customized data collection services, such as cockpit crew behavior collection, 2D street view data collection, multi-language and multi-crowd speech collection, etc.

With a variety of template tools, flexible coordination of manpower and algorithms, and professional data services, Nexdata will continue to spare no efforts to satisfy customers’ data processing needs.

If you need data collection and labeling services, please feel free to contact us: [email protected]