Road traffic accident risk factor analysis method based on random forest

A random forest and accident risk technology, applied in the traffic control system of road vehicles, traffic flow detection, traffic control system, etc., to achieve good anti-noise ability, avoid over-fitting phenomenon, and analyze comprehensive effects

Inactive Publication Date: 2019-09-24
NANJING UNIV OF SCI & TECH
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Problems solved by technology

However, these traditional methods have not fundamentally solved the causes of road traffic accidents

Method used

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  • Road traffic accident risk factor analysis method based on random forest
  • Road traffic accident risk factor analysis method based on random forest
  • Road traffic accident risk factor analysis method based on random forest

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Experimental program
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Embodiment 1

[0044] Step 1. Data collection

[0045] The acquired data is the accident-related risk factors related to road conditions, driver status, vehicle conditions and environmental conditions when traffic accidents occur between motor vehicles on the road, and the corresponding accident severity is recorded. The road-related accident-related risk factors are Road curvature, annual average daily traffic volume, road gradient, etc.; accident-related risk factors related to driver status include driver’s gender, age, whether drunk driving, etc.; accident-related risk factors related to vehicle conditions include vehicle age, vehicle type, The number of vehicles involved in the accident, etc.; the accident-related risk factors related to environmental conditions include visibility, weather conditions, etc.; because the severity of the accident is difficult to accurately divide the degree of injury of the personnel, the three aspects of the death toll, number of injuries and direct proper...

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Abstract

The invention discloses a road traffic accident risk factor analysis method based on a random forest. According to the road traffic accident risk factor analysis method, influence factors related to four aspects of people, vehicles, roads and environments and corresponding accident severity data are extracted when traffic accidents occur; a road traffic accident severity prediction model is established according to a random forest prediction model algorithm; model training is carried out, and model parameters are adjusted; and then variable importance measurement is carried out on the established prediction model by using a Gini exponential method, and importance sorting is carried out on related risk factors, and factors which have a remarkable influence on the severity of the accident are identified. According to the road traffic accident risk factor analysis method, influence factors of road traffic accidents, deep mining risk factors and accident severity can be considered in many aspects, and road safety management is facilitated.

Description

technical field [0001] The invention belongs to the field of road traffic safety research, in particular to a method for analyzing risk factors of road traffic accidents based on random forests. Background technique [0002] With the rapid economic growth, the number of private car ownership in my country has grown rapidly, reaching 186.95 million in 2017, while the number of road traffic accidents remains high. According to statistics, the total number of deaths due to traffic accidents in the world exceeds 1 million people every year, and 20 to 50 million people are injured or disabled due to road traffic accidents. Road traffic accidents not only seriously threaten people's lives and health, but also cause huge economic losses. The annual cumulative economic loss of traffic injuries is estimated at about 20 billion US dollars, reaching 1% to 3% of the world's gross national product. Therefore, effectively controlling and reducing road traffic safety problems is the most ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G08G1/01
CPCG08G1/0104G06F18/24323
Inventor 张蔚周竹萍彭云龙周泱李磊黄锐
Owner NANJING UNIV OF SCI & TECH
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