Highway outburst accident influence factor identification method based on negative binomial regression

Abstract

The invention discloses a road outburst accident influence factor identification method based on negative binomial regression. The method comprises the steps that a sliding window method is adopted to carry out road section analysis unit division on a road in a to-be-analyzed operation period; performing data extraction by taking the divided road section analysis units as units, and extracting a linear index variable and a traffic volume of each road section analysis unit; selecting a linear index variable and a traffic volume of the road section analysis unit as initial accident influence factors; assuming that all line shape condition index items corresponding to the road section analysis units to be analyzed are ideal line shape conditions, namely assigning null value items according to line shape index values under the ideal line shape conditions; and on the basis of the determined initial accident influence factor, analyzing the initial accident influence factor based on negative binomial distribution regression, and identifying the prominent accident influence factor of the road section to be analyzed from the initial accident influence factor. According to the invention, simple and rapid identification of accident-prone points of the high-grade highway is realized, and important guarantee is provided for safe operation management of the high-grade highway.

Description

technical field [0001] The invention relates to the field of identifying influencing factors of traffic engineering and accidents, in particular to a method for identifying influencing factors of outstanding highway accidents based on negative binomial regression. Background technique [0002] According to statistics, traffic accidents rank first in the number of non-disease deaths in the world. Therefore, the analysis, identification and management of prominent factors affecting road accidents during the operation period is a safety governance work that many developed countries need to carry out regularly. Although there are no clear regulations and requirements in this regard in our country, the identification of the influencing factors of outstanding highway accidents has always been one of the important tasks of the traffic management department in our country. Highway traffic accidents are often random, discrete, and independent events. According to the current mainstre...

AI Technical Summary

Problems solved by technology

[0006] The invention solves the problems of difficulty in identifying the influencing factors of prominent road accidents during the operation period, etc.

Images