A displacement filling method and related device

Abstract

The present application discloses a displacement filling method and a related device, the method comprising: at t n‑2 moment, t n‑1 moment and t n The vehicle is recognized as the second vehicle by the point cloud of the first vehicle at all times; the t corresponding to the identification of the second vehicle n Time point cloud data to obtain the relative displacement s between the second vehicle and the first vehicle n ;according to the relative displacement s n and fill in the displacement Δs to obtain the actual relative displacement s between the second vehicle and the first vehicle n ’; filling displacement Δs is based on the corresponding t of the second vehicle n‑2 Time point cloud data, t n‑1 The relative displacement s between the second vehicle and the first vehicle obtained by point cloud data recognition at each moment n‑2 , relative velocity v n‑2 , relative displacement s n‑1 and the relative velocity v n‑1 obtained by the operation. It can be seen that based on the relative displacement s n‑2 , relative velocity v n‑2 , relative displacement s n‑1 and the relative velocity v n‑1 , pre-computing t n The filling displacement Δs that needs to be filled after point cloud data recognition at any time, using its relative displacement s n The actual relative displacement s obtained by filling n ’, reduce the delay difference and avoid the problem of inaccurate lag.

Description

technical field [0001] The present application relates to the technical field of vehicle data processing, in particular to a displacement filling method and a related device. Background technique [0002] When driving a vehicle, especially unmanned driving, it is necessary to clarify the relative displacement of other vehicles and the own vehicle. At present, the self-vehicle generally obtains the relative displacement of other vehicles and the self-vehicle through the point cloud recognition of the lidar. Specifically, the point cloud data corresponding to other vehicles is input into the point cloud recognition algorithm, and the output is obtained to obtain the relative displacement of other vehicles and the self-vehicle. [0003] However, the inventor found through research that the point cloud recognition algorithm requires a certain amount of computing time, and during the calculation process of the point cloud recognition algorithm, the self-vehicle and other vehicles...

AI Technical Summary

Problems solved by technology

[0003] However, the inventors have found through research that the point cloud recognition algorithm requires a certain amount of computing time, and during the calculation process of the point cloud recognition algorithm, the own vehicle and other vehicles still continue to move, the other vehicles obtained by the point cloud recognition algorithm and the own vehicle There is a certain delay difference between the relative displacement and the actual relative displacement, that is, the relative displacement between other vehicles and the self-vehicle obtained by the point cloud recognition algorithm has the problem of lag and inaccuracy

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