Strategy And Optimization Of Rear-side Driving Assistance System Of Car Based On Millimeter Wave Radar

In recent years,the widespread application of active safety technology has promoted the rapid development of Advanced Driver Assistance System(ADAS)in the car field.Advanced Driver Assistance Systems have received widespread attention for their advantages in that they can take countermeasures to avoid accidents before they occur.With the increase of safety requirements,people not only consider the safety issues in front of the car,but also pay more attention to the safety issues in side and rear of the car.The rear and side driving assistance system has become a hot topic in the research and development of ADAS products because it can remind the driver of collision risk through sound and light or directly realizes collision avoidance through braking when the vehicle stops,goes straight,changes lanes and backs up.In order to realize the function optimization of the rear and side driving assistance system,the main work of this paper is as follows:1、Design a hierarchical early warning and control strategy.By fully considering the vehicle state parameters and safety models such as safety distance and safety time,a hierarchical early warning and control strategy for the Rear-Side Driving Assistance System based on the driver’s operating behavior is designed,and it solves the problem that the existing early warning system has single function and does not conform to the driver’s operating habits.2、Establish a curve distance recognition algorithm.By collecting and fitting the vehicle trajectory points,and analyzing the movement and attitude when the vehicle entering and exiting the curve,a curve distance recognition algorithm was established,and it realizes the accurate detection of relative longitudinal distance and relative transverse distance under the condition of curve.In addition,the established early warning and control strategy of the Rear-Side Driving Assistance System and the curve distance recognition algorithm are organically combined,so that the Rear-Side Driving Assistance System is suitable for the curve condition,and the system adaptability is improved.3、Complement the test scenarios of the existing test evaluation scheme.Based on the national standard(draft for comments),i-VISTA and ISO’s test and evaluation procedures for Blind Spot Detection system,through the analysis of the existing test and evaluation methods and the traffic scenario of two lane and two vehicle overtaking each other,three new test scenarios are taken as the supplement of the existing specifications,and the test conditions of three scenarios are specifically designed in combination with the characteristics of road traffic in China.4、Set up a virtual simulation and test environment.The vehicle dynamic model of the subject vehicle was built based on Car Sim;the test scenario model and radar model required by the Rear-Side Driving Assistance System were established based on Pre Scan;the curve distance recognition algorithm and hierarchical early warning and control Strategy model were established based on MATLAB/Simulink.Through the joint modeling of Car Sim,Pre Scan and MATLAB/Simulink,the construction of a virtual simulation and test environment is completed.5、Carry out virtual simulation test and real vehicle field test.Use the established virtual simulation environment for simulation verification,and deploy the system’s early warning and control strategy and curve distance recognition algorithm to the real vehicle for real vehicle field testing.The experimental results show that the early warning and control strategy and the curve distance recognition algorithm proposed in this paper can provide timely early warning or breaking under the supplementary test conditions,which improves the adaptability of the system and will help to ensure public safety.