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Highway accident frequency prediction method considering time-varying features of risk factors

A technology of risk factors and accidents, applied in the direction of forecasting, traffic flow detection, road vehicle traffic control system, etc., can solve the problems of shortened driver's visual distance, rear-end collision, increased risk of lane-changing accidents, and impact of accident risks, etc., to achieve The effect of improving classification accuracy, reducing the number of non-accidents, and improving the goodness of fit

Active Publication Date: 2021-05-25
HEFEI UNIV OF TECH
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Problems solved by technology

However, the time-varying characteristics of the above factors have a significant impact on accident risk
Compared with non-peak hours, the road traffic volume during peak hours is large, the occupancy rate is high, and the vehicle speed is low. Reduced visibility for the driver, increased braking distance and increased risk of accidents
To sum up, the traditional accident frequency prediction model cannot accurately describe the influence of time-varying characteristics of factors on accident risk, resulting in inaccurate prediction of road accident frequency.

Method used

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  • Highway accident frequency prediction method considering time-varying features of risk factors
  • Highway accident frequency prediction method considering time-varying features of risk factors
  • Highway accident frequency prediction method considering time-varying features of risk factors

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Embodiment Construction

[0057] In this example, if figure 1 As shown, a road accident frequency prediction method considering the time-varying characteristics of risk factors, taking the I-880 highway in California, USA as an example, proceeds as follows:

[0058] Step 1. Collect and process historical traffic accident data and related risk factor data;

[0059] Step 1.1, carry out section division to I-880 highway, according to the section division method of the same nature, promptly have the same section of lane number and the section of plane alignment to be divided into the same section, divide the road into K homogeneous section; In addition, if divide If there is a road segment less than 0.1 mile in the road segment, the road segment is merged into the adjacent road segment with the highest similarity, and finally, the I-880 highway is divided into 174 homogeneous road segments;

[0060] Step 1.2, establish a training set;

[0061] Step 1.2.1, in the traffic accident database, obtain the hist...

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Abstract

The invention discloses a highway accident frequency prediction method considering time-varying features of risk factors. The method comprises the steps of 1, collecting and processing historical traffic accident data and related risk factor data; 2, establishing a Logistic regression model; 3, calculating a classification threshold value of the Logistic model by adopting a Youden index method; 4, on the basis of the Logistic model and the historical accident data, calculating a positive predictive value and a negative predictive value of the model; and 5, performing accident frequency prediction by using the positive prediction value and the negative prediction value obtained by calculation. The accident frequency prediction method can overcome the problem that a traditional accident frequency model cannot reflect the influence of the time-varying features of the risk factors on the accident, and facilitates the improvement of the prediction precision of the accident frequency prediction method.

Description

technical field [0001] The invention relates to a method for predicting the frequency of road accidents considering the time-varying characteristics of risk factors, and belongs to the technical field of road traffic safety analysis. Background technique [0002] Constructing the relationship between the frequency of traffic accidents and risk factors such as road geometric characteristics, traffic conditions, and weather, so as to predict the frequency of accidents, is a common method for road safety evaluation. In the traditional accident frequency prediction model, since the dependent variable is the total number of accidents in a long time range (such as one year), for time-varying risk factors such as traffic conditions and weather, only statistical indicators within the corresponding time range can be used ( Such as annual average daily traffic volume, total annual rainfall) as independent variables. However, the time-varying characteristics of the above factors have ...

Claims

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Application Information

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IPC IPC(8): G08G1/01G06Q10/04G06Q50/26G06Q50/30
CPCG08G1/0104G08G1/0125G06Q10/04G06Q50/26G06Q50/40
Inventor 陈一锴于淑君石琴王飞董满生
Owner HEFEI UNIV OF TECH
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