A real-time prediction method for urban road traffic accident risk

Abstract

The invention provides a real-time prediction method of urban road traffic accident risk, which calculates by extracting the geometric linear data of each observation object in the observation set, the basic data of historical traffic flow n minutes before the occurrence of the traffic accident, and the historical weather condition data to obtain traffic The characteristic parameters of traffic flow n minutes before the accident and weather condition data are transformed into grades of categorical variables and the distribution probability of this grade, and then a real-time prediction model of urban road traffic accidents based on Poisson distribution is established, using the determined traffic flow characteristic parameters The level of weather condition data and the distribution probability of this level are used to calibrate the prediction model. When predicting the traffic accident risk of the required prediction object, it is only necessary to calculate the real-time traffic flow characteristic parameters and weather conditions of the required prediction object in real time. The level after the data is converted into a categorical variable and the distribution probability of the level can be used to predict the traffic accident risk of the desired prediction object using the calibrated formula.

Description

technical field [0001] The invention relates to the technical field of traffic safety, and more specifically, to a method for real-time prediction of urban road traffic accident risks. Background technique [0002] With the continuous development of our country's social economy and the substantial increase of the number of domestic motor vehicles, the number of road traffic accidents in our country is also showing an increasing trend. In 2012, the number of road traffic accidents in my country was 204,000, and the casualties caused by road traffic accidents reached 284,000. This shows that my country's road traffic safety situation is still very serious. As an important part of my country's road traffic system, urban roads are essential public infrastructure for people's lives, and their traffic accidents account for more than 40% of the total accidents every year. The prediction of urban road traffic accidents can estimate and speculate the risk state of the road, find ou...

AI Technical Summary

Problems solved by technology

However, this method ignores the impact of short-term changes in traffic flow on the probability of traffic accidents, and this impact has a considerable impact on urban road traffic. Therefore, the prediction accuracy of the above method is low, and it cannot be applied to the real-time analysis of urban road traffic accidents. forecast

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