Group division and difference analysis method and system based on traffic safety risks
A technology for group division and traffic safety, applied in traffic control systems, road vehicle traffic control systems, traffic flow detection, etc., can solve problems such as limited application scenarios of traffic safety management, and achieve the effect of saving time and cost
Active Publication Date: 2019-04-09
JIANGSU ZHITONG TRANSPORTATION TECH
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Problems solved by technology
[0002] Using machine learning methods to predict the probability of traffic accidents of traffic participants can calibrate a clear safety risk indicator for each driver and vehicle with traffic violations and accident records. The application scenarios of traffic safety management are relatively limited
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[0029] A group division and difference analysis method based on traffic safety risks, taking drivers and motor vehicles as objects, and using an integrated learning algorithm to calibrate the safety risks of the objects, on this basis, perform group division, and identify significant differences through statistical methods indicators; such as figure 1 , the specific steps are:
[0030] S1. Determine the objects of traffic participants, including drivers and motor vehicles; obtain the historical records of traffic violations and traffic accidents according to the information of the target objects as sample data.
[0031] In the embodiment, the target object information of the driver is the certificate number, and the target object information of the motor vehicle is the combination of plate type and plate number; the time range of historical records is usually more than 1 year to ensure a sufficient sample size.
[0032] S2. Construct a risk degree prediction model of the targ...
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The invention provides a group division and difference analysis method and system based on traffic safety risks, a driver and a motor vehicle are taken as an object, the safety risk of the object is calibrated through an integrated learning algorithm, group division is carried out based thereon, and a significant difference index is identified through a statistical method. According to the methodand the system in the invention, features are mined from traffic behavioral expression of traffic participants based on the integrated learning algorithm, and the safety risk degree is calibrated, thedata granularity of analysis and research application is reduced, and a plurality of target groups with different safety levels are divided according to the risk degree; meanwhile, in order to solvethe problem that the integrated learning algorithm lacks an explanation degree in the safety risk calibration process, a significant difference index between the groups is identified through Fisher accurate detection, so that the characteristics of each risk level group are accurately described, and data support is provided for active traffic safety management.
Description
technical field [0001] The invention relates to a group division and difference analysis method and system based on traffic safety risks. Background technique [0002] Using machine learning methods to predict the probability of traffic accidents of traffic participants can calibrate a clear safety risk indicator for each driver and vehicle with traffic violations and accident records. The application scenarios of traffic safety management are relatively limited. [0003] Under such application conditions, reducing data granularity and identifying key security features from a group perspective has a more realistic guiding role in proactive security governance. Therefore, there is an urgent need for a method and system for group division and difference analysis based on traffic safety risks to achieve the above objectives. Contents of the invention [0004] The purpose of the present invention is to provide a group division and difference analysis method and system based ...
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IPC IPC(8): G08G1/01G06Q10/06
CPCG06Q10/0635G08G1/0104G08G1/0125G08G1/0129G08G1/0133
Inventor 刘林吕伟韬陈凝饶欢
Owner JIANGSU ZHITONG TRANSPORTATION TECH