To scientifically screen out drivers with different accident proneness and make road traffic safety education more targeted

this paper designs a questionnaire and scales suitable for non-professional drivers of motor vehicles

analyzes and identifies factors influencing driver′s accident proneness

and calculates corresponding weight values. The fuzzy mathematics model was used to construct membership function so as to complete grading evaluation of driver′s accident proneness

and the rationality of the grading evaluation method was verified via collected road traffic accident data. Results show that six influencing factors including driver′s age

driving frequency

illegal operation score

stable driving personality

smart driving personality

as well as daily work and driving environment were screened out. Driver′s accident proneness scales and membership function could effectively identify drivers with different levels of accident proneness. When the score was within (0

3.5]

the driver′s accident proneness was high; when the score was within (73.5

4]

the driver′s accident proneness was relatively high; when the score was within (4

0)

the driver′s accident proneness was ordinary. It was verified by examples that the proposed method can effectively screen out drivers with different accident proneness and provide reference for driver training and safety education.