Traffic flow machine-learning modeling system and method applied to vehicles
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United States of America
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Mar 18, 2025
Grant Date -
Oct 27, 2022
app pub date -
Apr 19, 2022
filing date -
Apr 19, 2022
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Abstract
The invention relates to a traffic flow machine-learning modeling system and method applied to vehicles. The system includes: a target fusion module configured to perform target fusion on radar measurement data and camera measurement data, and output target attribute information; a lane line model module configured to output an original lane line model based on the camera measurement data; a target selection module configured to determine a position of a lane where each target is located based on the target attribute information output by the target fusion module and the original lane line model output by the lane line model module, and output the target; and a traffic flow calculation module configured to model the vehicle position by using a clustering algorithm based on the output of the target fusion module, the output of the target selection module, and the output of the lane line model module, and output a traffic flow-based lane line model. According to the invention, accurate lane line parameters can be obtained, and related lane flow characteristic information can be provided.
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