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Road safe state identification method

An identification method and safety state technology, applied in the traffic control system of road vehicles, traffic flow detection, instruments, etc., can solve the problems of increasing the amount of calculation, ignoring the multiplicity of accident causes, and reducing the accuracy of black spots, etc., to achieve accuracy high effect

Inactive Publication Date: 2019-10-15
王宣予
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Defining black spots only by the number of accidents, on the one hand, ignores the severity of accidents, and on the other hand, ignores the multiple causes of accidents
[0005] (2) When the traditional method is used to check and identify accident black spots, the screening process generally uses a certain step size to determine the accident black spots in a loop. When the step size is too large, some dangerous road sections will be missed, and the step size is too small. It will increase the amount of calculation, and at the same time include some non-black-spot road sections, which will reduce the accuracy of the black-spot identification

Method used

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Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment 1

[0092] Three traffic accidents occurred in a 5km road section within three years, one minor accident occurred in the 2km section, the coefficient was K=0.5; one general accident occurred in the 3km section, the coefficient was K=1; one major accident occurred in the 3.5km section Accident, the coefficient is K=2.

[0093] The distribution function of the black spots of three traffic accidents: in

[0094]

[0095] Make the orthogonal curve graphs of the distribution functions for the black points of the three traffic accidents, and use SPSS software to calibrate the Logistic model, superimpose the three traffic orthogonal curve graphs, and calculate the area enclosed by the superimposed curve and the X-axis as 3.782, the length of the curve on the x-axis after superposition is 5.44.

[0096] For general accidents: coefficient K=1, L=5, its critical area is:

[0097]

[0098] Identification conditions: the area enclosed by the superimposed curve on the x-axis is 3.782...

specific Embodiment 2

[0104] Two traffic accidents occurred within three years within a 5km road section, one minor accident occurred in the 2km section, and the coefficient was K=0.5; one minor accident occurred in the 3km section, and the coefficient was K=0.5.

[0105] The distribution function of the black spots of three traffic accidents: in

[0106]

[0107] Make the orthogonal curve graphs of the distribution functions for the black points of the two traffic accidents, and use SPSS software to calibrate the Logistic model, superimpose the two traffic orthogonal curve graphs, and calculate the area enclosed by the superimposed curve and the X-axis as 1.221, the length of the curve on the x-axis after superposition is 4.23.

[0108] For general accidents: coefficient K=1, L=5, its critical area is:

[0109]

[0110] Identification conditions: the area enclosed by the superimposed curve on the x-axis is 1.221<3S, the length of the superimposed curve on the x-axis is 4.23≤2L, and the nu...

specific Embodiment 3

[0127] Within three years within a 5km road section, one minor accident occurs in a 2km road section, and the coefficient is K=0.5.

[0128] The distribution function of a traffic accident black spot: in

[0129]

[0130] Make an orthogonal curve graph of the distribution function for the black points of a traffic accident, and use SPSS software to calibrate the Logistic model. The area enclosed by the traffic orthogonal graph and the X-axis is 0.612, and the curve is on the x-axis The length of 3.22.

[0131] For general accidents: coefficient K=1, L=5, its critical area is:

[0132]

[0133] Identification conditions: the area enclosed by the superimposed curve on the x-axis is 0.612<3S, the length of the superimposed curve on the x-axis is 3.22<2L, and the number of intersection points between the two endpoints of the superimposed curve and the x-axis is 0≤1;

[0134] Condition 1: The area enclosed by the curve on the x-axis after the superposition of step (2) is ...

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Abstract

The invention relates to a road safe state identification method. The method comprises the following steps: performing interval partition on the whole road to obtain a distribution function of an accident black point in each interval; respectively performing orthogonal curve chart on the distribution function of each accident black point in a certain interval of the road, overlaying the orthogonalcurve graph of each accident black point, and identifying the road section interval satisfying the following three conditions as the accident black point: the area surrounded by the curve at x ale after the overlaying is not less than 3S, the length of the overlaid curve on the x axle is not more than 2L, and the joint point number of the overlaid curve with the x axle at the internal of two endpoints is not more than 1. The identification method has the features of being scientific, comprehensive, objective, simple and clear and high in accuracy.

Description

technical field [0001] The invention belongs to the technical field of traffic accident assessment, in particular to a road safety state identification method. Background technique [0002] The traditional method mostly considers the accident as a separate discrete point. An accident is defined as a point on the road. After all the points are marked, the safety performance is judged according to the relationship between the points to determine the black point of the accident. point. The most commonly used method is, if there are more than n accidents in a certain section L within a specified time period, then define this road section as an accident black spot road section. [0003] This method has certain advantages, the required data is easy to obtain, and the determination process of accident black spots is simple and clear, but there are also shortcomings, which are specifically reflected in: [0004] (1) The reasons for the accident are comprehensive, such as road cond...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
CPCG08G1/0125G08G1/0129
Inventor 王宣予
Owner 王宣予
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