The Research About Risk Situation Assessment And Lane-change Trajectory Tracking Control Of Intelligent Vehicles

At present,with the development of advanced driver assistance systems(ADAS),in order to further improve the safety and comfort of smart driving vehicles,the concept of highly automated driving is proposed.Situation assessment is an important part of many Advanced Driver Assistance Systems(ADAS).To achieve this goal,it is important to assess traffic conditions and automatically adopt maneuvering decisions.Therefore,this paper studies the situation assessment and tracking trajectory tracking technology.Specifically,the study includes the following sections:(1)In order to enable smart vehicles to have good environmental awareness,considering the advantages and disadvantages of different on-vehicle sensors and the working environment requirements of the on-board sensors,a long-range millimeterwave radar is installed on the front bumper of the vehicle,and two medium-distance millimeters-wave radar is installed on both sides of the rear bumper of the vehicle and a camera is installed in front of the vehicle to build an environment awareness system of the vehicle,so that the intelligent vehicle can accurately obtain surrounding vehicle information and road information and provide preconditions for the situation assessment.(2)Because the data obtained by the environment-based sensors may be incorrect or missing,this paper selects the TTC and DST as risk assessment indicators based on Bayesian network theory,and uses probabilistic methods to evaluate the situation of vehicle safety and assess the impact around the vehicle.The degree of risk provides decision-making advice for the vehicle to maintain the current lane or change lanes.n this paper,the simulation experiment analysis of CarSim software is carried out to verify the effectiveness of the situation assessment.(3)According to the design principle of lane change trajectory,design the constant velocity offset plus sine function lane change model and the cosine and Sigmoid function to superimpose the lane changing model.Through comparative analysis with the common lane change model,the constant offset plus sine function lane-changing model better meet safety and comfortability of lane changing and is therefore used as the desired trajectory for lane change.In order to make the intelligent vehicle follow the expected lane change lanes,the dynamic position error of the vehicle is established based on the two-degree-of-freedom vehicle model,and the deviation of the target pose of the vehicle’s current pose and expected track is used to determine the lateral position deviation and bearing.The angle deviation is used as the control quantity.The fuzzy PID tracking controller is designed and the trajectory tracking is simulated and analyzed.The results show that the tracking controller can accurately track the desired trajectory.