A Risky Driving Behavior Scoring Model for the Personalized Automobile Insurance Pricing

Liu, Zhishuo; Shen, Qianhui; Han, Lei; Ma, Jingmiao

doi:10.1145/3126973.3126978

Cited by 4 publications

(2 citation statements)

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“…According to the characteristics of entropy, the randomness and disorder degree of an event can be judged by calculating the entropy value, and the dispersion degree of an index can also be judged by the entropy value. The greater the dispersion degree of an index, the greater the influence (weight) of the index on the evaluation target will be; otherwise, the less it will be [20]. The steps of EWM algorithm are briefly summarized as follows:…”

Section: Entropy Weight Methods (Ewm)mentioning

confidence: 99%

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Research on Safety Evaluation of Commercial Vehicle Driving Behavior Based on Data Mining Technology

Wang

Chen³

et al. 2021

Journal of Sensors

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The arrival of big data era of internet of vehicles promotes the rapid development of logistics industry, which also indirectly leads to the high traffic accident rate, resulting in huge casualties and property losses. Driving behavior is considered the most central factor leading to traffic accidents. Therefore, a scientific and effective method for evaluating the safety of commercial vehicle driving behavior is urgently needed. In this study, a comprehensive evaluation model of driving behavior security based on multimembership function is proposed, and entropy weight method (EWM), analytic hierarchy process (AHP), and fuzzy comprehensive evaluation algorithm are integrated. Firstly, the evaluation system of commercial vehicle safety of driving behavior is established. Secondly, the weight vector of each evaluation index is determined by combining EW-AHP to eliminate the subjectivity of the traditional AHP algorithm. Then, the fuzzy comprehensive evaluation matrix is calculated based on the multimembership function and fuzzy mathematics theory, and the quantitative evaluation of driving behavior safety is realized based on the matrix. Finally, the real road vehicle driving data and driving behavior data are verified by experiments. The experimental results show that the model can accurately and reasonably evaluate the safety of driving behavior, which is of great significance to improve road traffic safety.

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Section: Entropy Weight Methods (Ewm)mentioning

confidence: 99%

“…In formula (20), R i is a single-factor membership vector. The basic principle is derived from the fuzzy transformation ⊙ of the weight vector corresponding to r i (the…”

Section: : ð21þmentioning

confidence: 99%