Driving risk assessment method based on principal component linear weighting

Abstract

A driving risk assessment method based on principal component linear weighting includes the following steps that S1, n tested vehicles are selected, and a vehicle networking device is used for obtaining assessment factors of the tested vehicles and owners of the tested vehicles; S2, a forecasting function model is constructed, S2.1, a sample matrix is constructed; S2.2, a covariance matrix of the sample matrix is obtained, orthogonal transformation is carried out on the covariance matrix, and the eigenvalue and eigenvector of the matrix after orthogonal transformation is carried out are obtained; S2.3, an assessment function of samples is constructed; S2.4, an i principal component is expressed as a linear combination of n original indexes; driving risk levels are obtained. Objective weighting coefficients can be obtained, a principal component method emphasizes the difference principle, the obtained objective weighting coefficients are completely based on data themselves, in this way, the obtained index weighting coefficients have objectivity, and excessive human factor interference is avoided.

Description

technical field [0001] The present invention relates to an evaluation method, in particular to a driving risk evaluation method based on principal component linear weighting. Background technique [0002] With the rise of UBI Internet of Vehicles insurance and big data, there is an urgent need for a scientific method to evaluate the driver's driving risk. The evaluation results can be used as the support of the driving risk data of the test vehicle owner to remind and urge the owner to improve driving habits. , so as to improve the safety awareness of car owners, and can also provide a basis for insurance companies to formulate different levels of premiums. At present, the insurance evaluation of UBI at home and abroad is only after assigning appropriate weights to risk factors and doing simple fitting and calculation. But The evaluation results obtained by these methods cannot accurately reflect the actual dangerous situation. Contents of the invention [0003] In order ...

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Problems solved by technology

[0002] With the rise of UBI Internet of Vehicles insurance and big data, there is an urgent need for a scientific method to evaluate the driver's driving risk. The evaluation results can be used as the support of the driving risk data of the test vehicle owner to remind and urge the owner to improve driving habits. , so as to improve the safety awareness of car owners, and can also provide a basis for insurance companies to formulate different levels of premiums. At present, the insurance evaluation of UBI at home and abroad is only after assigning appropriate weights to risk factors and doing simple fitting and calculation. But The evaluation results obtained by these methods cannot accurately reflect the actual dangerous situation

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