High-precision dynamic map data processing system and method based on roadside sensors
A data processing system and dynamic map technology, applied in the computer field, can solve the problems of low cost, large amount of data and high cost, and achieve the effect of reducing the cost of production
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Embodiment 1
[0068] Such as figure 1 As shown, the present invention provides a high-precision dynamic map data processing system based on roadside sensors, including:
[0069] The map data collection terminal is used to provide massive and diversified map road raw data for the high-precision map generation server;
[0070] The high-precision map generation server is used to generate high-precision dynamic maps based on the massive and diversified map road raw data provided by the map data collection terminal;
[0071] The high-precision map generation server includes:
[0072] The map data processing module is used to extract road features from the original road data of the map, adopt a layered design for all road features, and splicing the same road information, first complete the fusion of road feature data at the road feature level, and finally complete at the image level Image stitching, the result of stitching generates a top view projection map of the road;
[0073] The map gener...
Embodiment 2
[0114] Such as Figure 5 As shown, the present invention is also a high-precision dynamic map data processing method based on roadside sensors, including:
[0115] S1. Collect a large amount of map original road image data and map original road condition data;
[0116] S2. Perform preprocessing of image correction, image coordinate transformation, and image projection transformation on the original road image data of the map. After the preprocessing, the image overlapping areas collected by the image data acquisition modules at adjacent positions can be aligned;
[0117] S3. Establish a deep learning road dynamic feature recognition model using deep learning and image recognition related AI technologies, and use the deep learning road dynamic feature recognition model to identify road dynamic features from the original road image data on the map;
[0118] Perform refined feature modeling based on existing navigation maps to obtain road static features;
[0119] Through the d...
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