Vehicle regulation and control method based on dangerous traffic flow characteristics under sunny condition

Abstract

The invention discloses a vehicle regulation and control method based on dangerous traffic flow characteristics under a sunny condition. The method comprises a first step of obtaining traffic information in an accident road section; a second step of collecting accident group traffic data under a sunny condition; a third step of collecting normal group traffic data under the sunny condition; a fourth step of building a traffic flow data total sample; a fifth step of building an initial traffic accident probability relational expression; a sixth step of confirming a standardized traffic accident probability relational expression under the sunny condition; a seventh step of detecting probability of traffic accident occurrence of the road section under the sunny condition, and regulating and controlling vehicles; and an eighth step of repeating the seventh step, collecting a traffic flow parameter in a next set time T, and judging the probability of the traffic accident occurrence of the road section until detection is finished. The vehicle regulation and control method detects the probability of the traffic accident occurrence on freeways in real time, and regulation and control to vehicles are achieved, and number of traffic accidents is reduced.

Description

technical field [0001] The invention belongs to the field of intelligent management and control of vehicle traffic on urban express roads, and in particular relates to a vehicle control method based on the characteristics of dangerous traffic flow in sunny conditions. Background technique [0002] In order to identify traffic accident black spots and evaluate the impact of various traffic facilities on traffic safety, traditional traffic safety research uses traffic accident prediction models to predict the expected accident frequency (or accident rate) of a road or certain road sections in the future. ). Traditional traffic accident prediction models usually use the average value of traffic parameters (such as annual average daily traffic volume, etc.), traffic facility characteristics (such as the number of lanes, shoulder width, etc.) and environmental conditions ( Such as weather conditions, road surface conditions, etc.) and other data to establish the macroscopic rela...

AI Technical Summary

Problems solved by technology

However, existing studies often ignore the influence of weather conditions on the risk of traffic accidents, that is, the characteristics of high-risk traffic flow states are different under different weather conditions (such as sunny and rainy days)

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