Research On Control Strategy Of Active Collision Avoidance System Of Autonomous Vehicle

In recent years,as the world’s productivity level has increased,the number of vehicles in various countries has continued to grow,and there have been worldwide problems such as traffic congestion and traffic accidents.Autonomous vehicle technology has attracted more and more people’s attention,and vehicle active collision avoidance technology is an important part of it.In view of the limitations of the current active collision avoidance system using a single longitudinal brake to avoid collisions,and the poor stability of steering collision avoidance under extreme conditions,this paper has carried out the research on the control strategy of the active collision avoidance system of autonomous vehicles,and designed the system The steering/steering collision avoidance coordinated control strategy optimizes the steering accuracy of steering collision avoidance trajectory and vehicle stability.The research results have important theoretical significance and application prospects.The main research contents of the thesis are as follows:First of all,in view of the limitations of a single braking collision avoidance method,a braking/steering collision avoidance control strategy was formulated based on the collision avoidance decision mechanism.For longitudinal braking and collision avoidance,the fuzzy control theory is used to design the longitudinal braking and collision avoidance controller,which outputs reasonable braking deceleration to achieve a safe distance from the vehicle in front.For steering collision avoidance,a three-degreeof-freedom vehicle dynamics model was established to analyze the lateral dynamics of the vehicle during lane changing.In order to ensure the continuity and safety of the vehicle’s steering collision avoidance trajectory,a fifth-order polynomial fitting method is used to plan the collision avoidance trajectory curve,and the minimum steering safety distance is used as a constraint condition.The model predictive control theory is used to build a vehicle steering and collision avoidance path tracking control module,and its effectiveness is verified under snake-like conditions.Secondly,in view of the fact that when the vehicle is running on a high-speed,lowadhesion road,the steering collision avoidance vehicle may lose stability.Using the method of centroid side slip angle-centroid side slip angle velocity phase plane method,the stability region change law under the influence of different vehicle speeds and road adhesion coefficients is analyzed,the boundary function of the vehicle stability region is determined,and the TS fuzzy neural network is combined with the sliding mode theory.The optimized additional yaw moment is assigned to each brake wheel,and the tracking ability and stability of the vehicle steering collision avoidance trajectory under extreme conditions are optimized.And through the double shift line(DLC)operating conditions for simulation experiments,the results show that the optimized control effect has better robustness.Finally,through Simulink/Carsim co-simulation,the vehicle braking/steering collision avoidance control algorithm was verified respectively.The simulation results of longitudinal braking and collision avoidance show that under different working conditions,the desired braking deceleration can be stably output and a reasonable safety distance between the vehicle ahead and the vehicle can be maintained.The simulation results of steering collision avoidance show that the coordinated control strategy based on T-S fuzzy neural network and sliding mode theory makes the vehicle more stable in extreme conditions and improves the ability of collision avoidance trajectory tracking to a certain extent.