Research On Design Of Traveling Obstacle Avoidance System And Semi-active Suspension Control Of Unmanned Vehicle Based On Lidar

As one of the main driving forces to promote the development of modern transportation,unmanned vehicle can not only improve the travel experience,but also promote cross-border cooperation and collaborative innovation of related industries.In order to ensure the safety,comfort and operational stability of unmanned vehicle in the face of some typical obstacle avoidance conditions,this thesis takes the lidar traveling obstacle avoidance system and semi-active suspension system of unmanned vehicle as the research objects,and focuses on the environment perception of vehicle,the design of obstacle avoidance system and the development of suspension control strategy under obstacle avoidance condition,the main research contents are as follows:（1）In order to increase the accuracy of environment perception for unmanned vehicle,the ground segmentation method based on slope and height is combined to preprocess the original point cloud data of lidar,and a density clustering algorithm is used for non-ground points for obstacle detection,and a bounding box is added for each obstacle.Considering the nonlinear motion of multiple obstacles,obstacles are tracked based on joint probability data association and unscented Kalman filter algorithm.The simulation results show that the proposed method can effectively detect the obstacles that may have influence on its own motion state,and the tracking of obstacles is also very stable.（2）In order to improve the ability of unmanned vehicle to drive autonomously and safely,the traveling obstacle avoidance system of the vehicle is designed based on layered control architecture.Among them,the upper controller based on optimal control calculates the desired acceleration of the vehicle based on the effective information collected by the lidar;The lower controller based on PID control takes the error between the desired acceleration and the actual acceleration as the input of the controller to calculate the control acceleration of the vehicle.The control acceleration is transformed into the vehicle’s throttle opening and brake cylinder pressure by the drive/brake switching module and the inverse longitudinal dynamics model,which are input into the overall vehicle dynamics model.The simulation results show that the unmanned vehicle can fully ensure its safety under the four typical obstacle avoidance conditions set,and the actual acceleration achieves stable tracking of the desired acceleration.（3）In order to take into account the comfort and operational stability of the unmanned vehicle under typical obstacle avoidance conditions,a four-degree-of-freedom semi-active suspension model is established according to the motion characteristics of the vehicle under typical obstacle avoidance conditions.Considering the multi-objective optimization of the suspension system,the H₂/H∞state feedback controller is designed by defining the comfort of vehicle as performance output,and the operational stability as constraint output.The corresponding control objectives are formulated according to the performance requirements of the suspension at different road levels,and the controller parameters are optimized by using an improved particle swarm algorithm.The simulation results show that the vertical acceleration and pitch angle acceleration of the body under class A road surface are optimized by 57.0%and 60.3%,the front and rear dynamic loads under class C road surface are optimized by 16.6%and 21.0%,respectively,compared with the passive suspension,which balances the comfort and operational stability of the unmanned vehicle under mixed road classes.（4）In order to solve the time delay problem in the semi-active suspension system of unmanned vehicle,a four-degree-of-freedom semi-active suspension model considering time delay is established based on the motion characteristics and suspension response time delay under typical obstacle avoidance conditions of vehicle.Taking the road surface information felt by the front wheels as the preview information of the rear wheels,an augmented system with wheelbase preview information is established based on the H₂/H∞control strategy,and an adaptive Smith compensator is designed to compensate the system time delay.The simulation results show that the road preview information can further optimize the performance of the suspension,and the suspension with time delay compensation optimizes the vertical acceleration and pitch angle acceleration of the body by 51.9%and 65.0%,and the dynamic loads of the front and rear wheels by 22.9%and 27.0%,respectively,compared with the passive suspension,which leads to better overall performance of the vehicle.