Vehicle collision detection method based on machine learning

Abstract

The invention discloses a vehicle collision detection method based on machine learning. The vehicle collision detection method based on machine learning comprises the following steps: acquiring a velocity vector, an acceleration vector, an angular velocity vector and longitude and latitude; preprocessing the acquired speed data respectively; calculating new vector data through the preprocessed data and acquiring a road scene label; composing the calculated data into an input vector; calculating collision probabilities under different models through input vectors and calculating comprehensive collision probabilities; acquiring the category of the input vector through a preset method and judging whether the comprehensive collision probability value and the category of the input vector are abnormal or not; and marking the input vector as a collision vector or a non-collision vector. By integrating supervised learning and unsupervised learning algorithms, the cost of machine learning is reduced; collision detection is carried out by using a plurality of trained classifiers, and collision detection under a plurality of collision scenes is covered by adopting a mode of deep mining of a plurality of dimensions and a plurality of collision scenes, so that the accuracy rate and the recall rate of collision detection are improved.

Description

technical field [0001] The invention relates to the field of automobile safety, in particular to a vehicle collision detection method based on machine learning. Background technique [0002] Machine learning technology is the hottest branch of AI at present, and all walks of life use this technology to solve some problems in the industry. In the field of automobile collision detection, there are many successful practices of deep learning in the collision detection technology based on video images. However, in the collision detection technology based on basic data, few people in the industry can use machine learning technology to solve the problem of collision detection. The main reasons are as follows: the cost based on supervised learning is too high, and in a limited dimension, it is difficult to use machine learning technology, and it is difficult to achieve better results; the collision detection technology based on basic data itself is rarely used. It is often solved ...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the invention of the present invention is to: aim at the above existing problems, provide a vehicle collision detection method based on machine learning; the present invention solves the problem of high cost of machine learning detection; also solves the problems of low detection accuracy and low recall rate question

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