Research On Combined Control Of Steering Collision And Stability Of Intelligent Vehicles

Intelligent vehicle technology has been recognized by academia and industry field as a key force transforming the future of the automotive industry,and is an integral part of intelligent transportation system.In short,intelligent vehicles are mobile robots that contain environmental perception,planning and decision-making,low-level control and execution abilities.It covers many disciplines such as electronics,mechanics,automation,computer science and artificial intelligence.Specifically in the field of vehicle collision avoidance,the existing control strategy to a considerable extent relies on the driver's brake operation to avoid the risk.While failed to give full play to the environmental awareness potential.In this paper,a collision avoidance control strategy of steering based on model predictive control theory was designed.In addition,the reference path with obstacles,simplified vehicle dynamics model,steering controller,path tracking accuracy and parameter robustness verification were discussed.At the same time,in order to improve the steering stability of high-speed of vehicles under low adhesion coefficient.A direct yaw moment stability controller based on fuzzy control theory was designed for its robustness.The additional yaw moment was calculated according to the actual lateral dynamic response of vehicles,and then transformed to brake cylinder pressure according to the braking force distribution logic.The full text of this thesis could be summarized as the following aspects:(1)The status of the generation and development of intelligent vehicles,the related research results at home and abroad were introduced.In particular,this thesis analyzed in detail the control strategy,system composition,existing defects and deficiencies of vehicle steering avoidance control system,which was not yet mature and commercialized.(2)The overall scheme of the joint control system of steering avoidance and stability was designed.The longitudinal safety clearance required for the steering or braking of the vehicle is deduced.Based on this,a decision-making logic of collision avoidance action is proposed.The reference path followed by a specific vehicle is derived from the fifth-orderpolynomial planning.(3)In view of the strong non-linear characteristics of vehicles running at high speed,this thesis proposes a steering controller based on model predictive control theory,a simplified vehicle dynamics model and tire model were used as the predictive model.The control effect of steering controller is verified by double-lane change and pylon course slalom tests,followed by the simulation of vehicle speed and control parameters robustness.(4)Under the premise of meeting requirements of collision avoidance,the vehicle stability control strategy was designed based on fuzzy theory in Simulink.Followed by the details of input and output parameters of DYC fuzzy controller,fuzzification,fuzzy rules and defuzzification.Finally,through the steering wheel sinusoidal rotation test to verify the stability of vehicle.(5)The vehicle dynamics model was established in CarSim and the Simulink / CarSim co-simulation study was carried out.The test results under different vehicle speeds and road adhesion coefficients show that under the same collision avoidance conditions,the vehicle collision avoidance control effect and dynamic response curve with direct yaw moment control were superior to those without stability control.Joint control measures improved the driving safety of intelligent vehicles further.