Research On Automatic Control Algorithm Of Emergency Lane Change Steering System Under Fast Driving

As people attach more and more importance to road traffic safety,more and more active safety technologies are integrated into automotive systems.At present,most of the obstacle avoidance systems are using warning and braking operations.However,in some emergency situations,such as the sudden stop of the front vehicle and pedestrians out of blind spot area,etc,due to the long braking distance,the effect is very limited.Aiming at the limitations,this paper proposes an emergency steering algorithm that changes the vehicle's lateral position to avoid obstacles during fast driving.Firstly,based on the current status of obstacle avoidance technology all around the world,this paper designs the overall architecture of the emergency lane change steering obstacle avoidance system,and the information interaction between the various functional modules is clarified.According to urgency,obstacle avoidance behavior is divided into three forms: collision warning,emergency braking,and emergency steering obstacle avoidance.the safety status of the ego vehicle is based on the reciprocal of the collision time in this paper.If there is a risk,the danger level is further determined based on the safety distance,According to the danger level,different operations are taken.At the same time,considering the relevant laws and the safety of drivers and passengers,this paper designs a driver takeover strategy to allocate control of the vehicle.Secondly,this paper analyzes the characteristics of the application scenario of emergency lane change,and propose five requirements for the lane change trajectory.Because the traditional several emergency lane change trajectory planning methods do not consider the impact of dynamic obstacles and other surrounding vehicles,this paper chooses a planning method based on numerical optimization.In the limited time domain,the emergency lane change obstacle avoidance system mathematically model the future state of the obstacle vehicle and others,then determine the longitudinal drivable area and driving trajectory.feasible longitudinal trajectory exists,the laterally drivable area and driving trajectory are determined according to the obstacle vehicle,the lane boundary,and the lane change width,etc.,and finally a series of expected motion state sets in the discrete time domain are obtained.Since the final trajectories are obtained by the optimal solution of the objective function,the comfort of the driver is guaranteed on the basis of obstacle avoidance.At the same time,in order to evaluate the safety status,A collision detection algorithm is proposed to detect the possibility of collision of planned trajectories.Then,according to the characteristics of the planned trajectory,this paper decouples the trajectory tracking algorithm into speed following control and lateral displacement tracking control.For speed following control,a fuzzy self-tuning proportional-integral controller is designed.For lateral displacement tracking control,this paper designs two controllers based on feedforward-feedback or model prediction,and double lane trajectory at different speeds tests the effect of these two controllers.Finally,based on the CarSim/Simulink co-simulation,this paper tested the coupling effects of the trajectory planning,speed following,and lateral displacement tracking algorithm based on model prediction.In order to verify the functionality of the algorithm in a real environment,this paper has upgraded a SUV and established a real vehicle test platform.At the same time,considering the danger of the real vehicle test,this paper simplified the actual lane changing environment,and tested the general lane changing behavior of the planning algorithm and the lateral displacement tracking controller based on feedforward-feedback in the highway scene.