A traffic accident cause analysis method based on multiple correspondence and K-means clustering

Abstract

The invention discloses a method based on multiple correspondence and K. The method comprises the following steps: (1) according to the obtained traffic accident data set, selecting and classifying the variables that affect the occurrence of traffic accidents; (2) Through the statistics of the number of categories of each variable and the corresponding accident number in the database, the variablecategories of the merged abnormal values are screened to obtain the accident data table; (3) processing the obtained accident data table to obtain a binary index matrix; (4) Multiple correspondence analysis is carried out by taking accident type as the variable representing accident characteristics, and the coordinates of multiple correspondence analysis of each variable type are obtained; 5) uselocal linear embedding algorithm to reduce that dimension of the variable category coordinate obtained from the multi-correspondence analysis of the accident data, and obtaining the LLE reduced dimension coordinate; (6) Use of K-Means clustering algorithm is used to cluster the variables, and the results are analyzed according to the clustering results. According to the clustering result, the invention comprehensively probes into the causes of traffic accidents from multiple dimensions, and not only analyzes two-dimensional correspondence analysis diagrams.

Description

technical field [0001] The invention relates to the technical field of road traffic, in particular to a traffic accident cause analysis method based on multiple correspondence and K-means clustering. Background technique [0002] The elements of the road traffic system include people, vehicles, roads, and the environment. Each element is a subsystem and interacts with each other. The occurrence of traffic accidents is due to the problems of each subsystem itself or the interaction between them. Through the study of a large amount of traffic accident data, targeted intervention measures or improvement measures for road safety are proposed to achieve the purpose of reducing the risk of accidents and the severity of accident injuries. [0003] There are many potential risks affecting traffic accidents, including traffic participants, vehicles, roads and the environment. At present, the existing research mainly focuses on the driver's age, gender, driving experience, etc. and d...

AI Technical Summary

Problems solved by technology

[0004] At present, the public security traffic management department has recorded a large amount of traffic accident data, but it is only based on the collected data for simple classification statistics, without correlation analysis, it is difficult to find the comprehensive impact of various elements of the traffic system on traffic accidents, Unable to analyze the causes of traffic accidents in detail

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