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Home > News > What applications does Lidar have in driverless driving?
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What applications does Lidar have in driverless driving?

1. Positioning

Positioning in unmanned driving for ten minutes is important. Only with real-time location information can the system make the next interpretation, decide where to go, and how to get there. There are many ways to position it now. Such as carrier phase difference technology (RTK), but RTK is still subject to signal interference. Especially in some cities, buildings and trees, as well as tunnels and tunnels, its signal is easily interrupted. At the same time, sensors such as cameras are also used to sense the external environment, construct an environmental model, and use the model to determine the location of the vehicle, but its dependence on the environment is relatively strong, such as backlighting or rain and snow, such positioning is prone to failure. LiDAR relies on comparing the initial position of the vehicle with the high-precision map information to obtain a precise position. First, sensors such as GPS, IMU, and wheel speed give an initial position. Secondly, the local point cloud information of the lidar is extracted, and the vector features in the global coordinate system are obtained by combining the initial positions. Finally, the vector features of the previous step are matched with the feature information of the high-precision map to obtain accurate global positioning. Therefore, in terms of positioning, the use of laser radar has an unparalleled advantage in terms of accuracy and stability.

2. Obstacle detection and classification
For obstacle detection and classification, there are currently applications of vision and lidar, which are not in conflict. Lidar does not rely on illumination, its viewing angle is 360 degrees, the calculation is relatively small, and it can be scanned in real time. It is generally used within 100 milliseconds. In the process of scanning, the laser radar first identifies obstacles, knows the position of the obstacle in space, and then classifies according to the existing obstacles. For example, cars and people, we divide these obstacles into independent individuals, and then separate and separate the individual to match, so as to classify the obstacles and track the objects.
3. For advanced driver assistance systems (ADAS)
The Advanced Driver Assistance System (ADAS) uses a variety of sensors installed in the vehicle to collect environmental data inside and outside the vehicle at the first time to identify and detect static and dynamic objects. Technical processing such as tracking, which allows the driver to detect the dangers that may occur in the fastest time, to attract attention and improve the safety of active safety technology.