Highway traffic accident analytical prediction method based on multi-dimensional factors

A traffic accident and prediction method technology, applied in traffic flow detection, road vehicle traffic control system, traffic control system, etc. The effect of strengthening supervision and reducing impact

Active Publication Date: 2018-08-17
四川智慧高速科技有限公司
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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 managem

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  • Highway traffic accident analytical prediction method based on multi-dimensional factors
  • Highway traffic accident analytical prediction method based on multi-dimensional factors
  • Highway traffic accident analytical prediction method based on multi-dimensional factors

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[0036] The following describes the specific embodiments of the present invention to facilitate those skilled in the art to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments, for those of ordinary skill in the art, as long as various changes These changes are obvious within the spirit and scope of the present invention defined and determined by the appended claims, and all inventions and creations using the concept of the present invention are protected.

[0037] Such as figure 1 As shown, the high-speed traffic accident analysis and prediction method based on multi-dimensional factors includes the following steps:

[0038] S1. Establish a database based on historical traffic accident data and historical daily record data;

[0039] S2. Select the type of traffic accident and the corresponding daily record data from the database, and obtain the data of multi-dimensional influencing factors of the...

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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 an analysis and prediction method for expressway traffic accidents based on multidimensional factors. Background technique [0002] With the rapid development of expressways in our country and the increase of traffic flow, the number of traffic accidents on expressways is increasing year by year. At present, foreign countries have deep research on traffic safety and high management level, compared with our country, there is still a big gap, and there is a lack of systematic concepts, theories and methods for traffic improvement. [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-ma...

Claims

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Application Information

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IPC IPC(8): G08G1/01
CPCG08G1/0129G08G1/0137
Inventor 陈非王瑞锦李凯张凤荔杨婉懿刘崛雄蒋贵川高强陈学勤唐晨张雪岩翟嘉伊魏楷
Owner 四川智慧高速科技有限公司
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