An automatic driving device and system
A technology for autonomous driving and equipment, applied in the field of vehicles, can solve the problems of high cost, the accuracy of distance information acquisition is not as good as radar, and the influence of field of view.
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Embodiment 1
[0024] figure 1 A schematic structural diagram of an automatic driving device provided in Embodiment 1 of the present invention is based on the fact that the automatic driving device has been installed in a vehicle, figure 1 A top view of the vehicle. like figure 1 As shown, the device includes: a solid-state lidar sensing module, a blind-filling radar sensing module, and a millimeter-wave radar sensing module.
[0025] Among them, the solid-state lidar sensing module includes one long-range solid-state radar 11 and eight medium-range solid-state radars 12 ; the blind-filling radar sensing module includes four blind-filling radars 13 ; the millimeter-wave radar sensing module includes two millimeter-wave radars 14 .
[0026] The long-range solid-state radar 11 is arranged on the front side of the central axis of the roof, and is used to detect information about obstacles in the middle and long distances directly in front of the vehicle. 8 mid-range solid-state radars 12 are...
Embodiment 2
[0034] Figure 5 is a schematic structural diagram of an automatic driving system provided by the second embodiment of the present invention, such as Figure 5 As shown, the system includes: an automatic driving device 210 , a data calibration module 220 , a data fusion module 230 , a first obstacle detection module 240 , a second obstacle detection module 250 , an obstacle classification module 260 and a target tracking module 270 .
[0035] Among them, the automatic driving device 210 is used to obtain the point cloud data of the surrounding environment of the vehicle; the data calibration module 220 is used to convert the point cloud data to the set coordinate system according to the calibration parameters; the data fusion module 230 is used for the converted point cloud. The data is synchronously fused in space and time; the first obstacle detection module 240 is used to analyze the fused point cloud data by using a deep learning model to obtain the first obstacle informat...
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