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Road traffic accident multi-happening section identifying method

A technology for accident-prone sections and traffic accidents, applied in the field of road traffic accident-prone section identification, can solve problems such as being unable to be the same, unable to explain the actual meaning, and not taking into account differences in national regions and regions, to avoid subjectivity and enhance identification. Effect

Inactive Publication Date: 2007-03-21
BEIJING UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

One is that the number of accidents calculated according to the average road section length does not conform to the Poisson distribution on some roads, so it cannot be widely promoted and applied; in addition, a numerical value cannot be determined uniformly, without considering regional and regional differences across the country
[0005] The accumulative frequency method does not consider the traffic volume factor and the severity of the accident. At the same time, the mutation point of the accumulative frequency fitting curve is used as the criterion for defining the accident-prone road section. The situation where the composite curve has an inflection point (mutation) cannot explain its actual meaning in practice

Method used

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  • Road traffic accident multi-happening section identifying method
  • Road traffic accident multi-happening section identifying method
  • Road traffic accident multi-happening section identifying method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] Embodiment 1 The number of accidents and the accident rate conform to the example of Poisson distribution

[0024] The number of traffic accidents refers to the number of traffic accidents corresponding to the mileage of the highway in a statistical period on the road section to be identified. In this example, the number of accidents on the road section with a length of 1Km is used as the statistical unit, and the road type is a road dedicated to automobiles. The division of other road types is shown in Table 1. Corresponding to the second type of road type urban roads, when identifying road traffic accident-prone road sections, replace "1Km length road section with length less than L and the number of accidents ≥ 2" when identifying road traffic accident-prone road sections, and other steps remain unchanged. guidelines. Among them, L refers to the distance between urban intersections: 30m for secondary arterial roads and 60m for main arterial roads.

[0025] ...

Embodiment 2

[0040] Embodiment 2 The number of accidents and the accident rate do not conform to the example of Poisson distribution:

[0041] For the case where the number of accidents and the accident rate do not conform to the Poisson distribution, the road to be studied is divided into several small road sections according to the length of 1Km, and the number of small road sections with the same number of accidents is found, that is, the number of accidents on the road to be studied is For the frequency of occurrence, divide the accident frequency by the total number of small road sections to obtain the frequency of the accident number, and add the frequency according to the number of accidents from small to large to obtain the cumulative frequency of traffic accidents. After the significance level α is given, the number of accidents corresponding to the cumulative frequency equivalent to (1-α) is the critical value γ. Divide the number of accidents by the traffic volume to get the acc...

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Abstract

The invention is concerned with the distinguishing method for the road with more traffic accident. The invention uses double target of alpha-gamma to distinguish the road with more traffic accident, assigns the remarkable level alpha, according to the Poisson probability formula or the frequency accumulation chart, after computes the critical value gamma of the high accident number and the critical value R of the high accident rate, compares the gamma and the R of the un-distinguish road to get the distinguishing result of the road with more traffic accident.

Description

technical field [0001] The invention relates to the field of road traffic safety, and more particularly to a complete and reliable method for identifying road sections with frequent occurrence of road traffic accidents in the field. Background technique [0002] The first and most critical step in a road safety improvement project is to identify the location of the accident-prone road sections that need urgent improvement. At present, the most widely used method is accident data statistical analysis method, which can be divided into many different methods according to different discriminant indicators and methods for statistical processing of accident data, but these methods have their own applicable conditions and shortcomings. [0003] The absolute number method is further divided into the accident frequency method and the accident rate method. The number of accidents method does not take into account factors such as traffic volume and accident severity. Using it alone is...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06F19/00
Inventor 胡江碧刘小明荣建邵长桥李强
Owner BEIJING UNIV OF TECH
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