Analysis and Prediction Method of Expressway Traffic Accidents Based on Multidimensional Factors

Abstract

The invention discloses a highway traffic accident analytical prediction method based on multi-dimensional factors. The method comprises the following steps: S1, establishing a database according to historical traffic accident data and historical daily record data; S2, selecting a traffic accident type and corresponding daily record data from the database and obtaining the multi-dimensional influence factor data of the traffic accident; S3, establishing a Bayesian network for the multi-dimensional influence factor data, obtaining the influence probabilities of various factors on the traffic accident, and using influence probabilities as predictive models; and S4, predicting highway traffic accidents according to the predictive models and the real-time data. The method can preprocess and transform historical traffic accident data, analyzes and utilizes the multi-dimensional influence factor of traffic accidents to establish the corresponding Bayesian network to form a predictive model of traffic accidents, uses data mining technology to find a probability relationship between the multi-dimensional factors affecting the traffic accidents, and predict whether an accident occurs by using real-time observation data based on the results of the analysis.

Description

Technical field [0001] The invention relates to the field of road accident prediction, in particular to a highway traffic accident analysis and prediction method based on multi-dimensional factors. Background technique [0002] With the rapid development of expressways in my country and the increase in traffic volume, the number of traffic accidents on expressways is increasing year by year. At present, foreign countries have a deep research on traffic safety and a high level of management. Compared with my country, there is still a big gap and lack of systematic concepts, theories and methods for traffic improvement. [0003] Traditional traffic accident analysis methods have the following shortcomings: First, the collection of traffic safety data is not comprehensive and accurate, which makes it difficult to carry out research work in a comprehensive and smooth manner, and the research results have little effect on the guidance and decision-making reference of traffic safety mana...

AI Technical Summary

Problems solved by technology

[0003] The traditional analysis methods of traffic accidents have the following deficiencies: firstly, the collection of traffic safety data is not comprehensive and accurate, which makes it difficult to carry out the research work in a comprehensive and smooth manner, and the research results have little reference to the guidance and decision-making of traffic safety management; secondly , the method of research and analysis is not scientific and reasonable, and the research on the distribution of traffic accidents only stays at the macroscopic and single level, lacking comprehensive consideration of the effects of multiple factors; finally, the decision-making based on traditional statistical methods is more subjective , the error is too large

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