Vehicle intelligent safety decision-making method based on driving safety field

Abstract

The invention discloses a vehicle intelligent safety decision-making method based on a driving safety field. The method includes: step 1, setting a driving safety field model and a driving safety field model in advance in the electronic control unit of the vehicle or in the central computer system of the intelligent traffic management system. Risk identification model; wherein, the driving safety field model is used to reflect the change of traffic risk with time and space, which is constructed by analyzing the influence of various factors of the human-vehicle-road system on the traffic system; step 2, through the driving safety field model, Obtain the current optimal driving speed and the safe driving distance between the vehicle and objects other than the vehicle when the traffic system is in a steady state; step 3, according to the current optimal driving speed and safe driving distance, by obtaining the driving risk identification model The minimum value of the amount, and then get the current driving risk level value of the vehicle. The invention can realize the safety control of the road traffic system, and is beneficial to reduce the occurrence rate of road collision traffic accidents.

Description

technical field [0001] The invention relates to the field of traffic safety, in particular to a vehicle intelligent safety decision-making method based on a driving safety field. Background technique [0002] In recent years, my country's national economy has developed rapidly, the process of automobileization has also been promoted rapidly, and the number of automobiles has increased rapidly. At the same time, the situation of road traffic safety in my country has become increasingly severe. Traditional traffic safety control is based on vehicle dynamics or road planning, and its theoretical assumptions do not fully consider the role of the human-vehicle-road system in traffic behavior, especially the lack of attention to the psychological characteristics of people (drivers) and research. In addition, in terms of research methods, it is basically on a single level of correlation, that is, a certain influencing factor is used as an independent variable, and the change of ve...

AI Technical Summary

Problems solved by technology

Aiming at the problem that the current traffic safety model is difficult to fully reflect the risks caused by various traffic factors such as people, vehicles and roads to the traffic environment, Wang Jianqiang et al. proposed the idea of ​​driving risk field, and its model covers people, vehicles and roads. A large number of parameters, but the model only provides auxiliary decision-making for driving safety, and cannot provide an accurate basis for road safety assessment in complex traffic environments

[0005] At present, the existing studies are relatively scattered when considering the factors causing driving risks, mainly for specific scenarios, similar to the driving assistance equipment configured on cars, and only deal with the problem, but have not yet formed a system to coordinate and solve the overall problem

This may cause the car to drive in a complex traffic environment without an effective strategy to control the entire traffic system, and cannot provide timely decision-making information support for the entire traffic traveler in mixed traffic.

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