Open AccessComprehensive Evaluation Method of Driving Behavior Based on Neural Network
Author(s) -
Jiayao Li,
Li Li,
G. Jin,
Xiaoli Zhao,
Yuhong He
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2010/1/012190
Subject(s) - computer science , construct (python library) , artificial neural network , selection (genetic algorithm) , process (computing) , data mining , machine learning , artificial intelligence , operating system , programming language
In recent years, the number of traffic accidents in the world has increased sharply. Reasonable mining of the OBD data generated in the process of vehicle driving will help to improve traffic safety. However, the existing driving behavior scoring models have the following shortcomings: the indexes are not comprehensive enough, and the selection of weights is not objective. In order to solve these shortcomings, this paper proposes 16 driving behavior indexes and related definitions; the neural network is used to construct the model to distribute the weight reasonably; a new comprehensive evaluation model of driving behavior is constructed. The feasibility and efficiency of the model are verified by experiments on real vehicle OBD data sets.