Research On Automated Lane Change System Of Full X-by-Wire Electric Vehicles For Individualized Driver Design

Intelligent and electric are the development trend of future automobile industry.Intelligent vehicle,as the important part of intelligent transportation system（ITS）,has attracted more and more attention in recent years.As a member of advanced driving assistance system（ADAS）,automated lane change system can effectively improve the safety and comfort in the process of lane change,and reduce the driver’s workload.At present,many of the existing automated lane change systems assist the driver according to the usage habits of most people.However,because each driver has different subjective preferences in the lane change process,such a design will affect the acceptance of the individual driver for the automated lane change system.Drivers still need to play a role in the driving process for intelligent vehicles equipped with ADAS.Hence,it is necessary to design and develop a novel vehicle to solve the problem of co-driving caused by the structural limitation of the electric steering system.Full X-by-Wire electric vehicle has the advantages that each wheel can be controlled independently and accurately.Compared with the traditional vehicle,it has higher flexibility,and it is easier to achieve the improvement of vehicle performance.To sum up,full X-by-Wire electric vehicle is an ideal carrier for the future development of intelligent vehicles.Based on the full X-by-Wire electric vehicle,this paper studies the automated lane change system which satisfies the individual driver design.The system not only realizes the individual driver’s personalized assistance,but also makes full use of the advantages of full X-by-Wire technology to ensure the performance of the vehicle.The main contents of this paper are summarized as the follows:（1）In this paper,a personalized human-like lane change trajectory planning method is proposed as the basis of realizing the function of automated lane change system.Firstly,based on the theory of psychology,the influencing factors of driver behavior in traffic environment are analyzed to determine the variables that affect driver characteristics;Then,a driving simulation platform was built to collect data based on CarSim RT,Matlab/Simulink,NI-Veristand and sensor-wheel.The experiment conditions are designed and the driving data is processed by algorithms.Finally,a personalized human-like lane change trajectory model including longitudinal driving behavior model and hyperbolic tangent lane change model is established.Among them,the former uses the-image to represent the longitudinal speed control behavior of the driver in the process of lane change,while the latter establishes the lane change model and uses the multi-dimensional time series regression method to calibrate and identify the parameters of the lane change model through historical data.（2）In order to track the personalized human-like lane change trajectory,a trajectory tracking control architecture of full X-by-wire electric vehicle is proposed in this paper.Firstly,a nonlinear three-degree-of-freedom four-wheel independent steering vehicle model considering wind resistance,rolling resistance and load transfer is established.In order to solve the problem of lateral and longitudinal motion coupling in vehicle dynamics control,a layered control architecture is designed.The trajectory tracking layer uses neural network PID algorithm to obtain the desired yaw rate with the cubic spline curve obtained from the target trajectory fitting as the input;the vehicle motion control layer takes the nonlinear time-varying characteristics of the vehicle into account,and uses terminal sliding mode control algorithm to obtain the desired total longitudinal force and lateral force.（3）To make full use of the advantages of high freedom degree of full X-by wire electric vehicles and improve the performance of vehicles while realizing the trajectory tracking,this paper designs an actuator control strategy considering multiple optimization objectives in the tire force distribution layer.In this layer,the control strategy of the actuator considering multiple optimization objectives is designed.Firstly,three different evaluation indexes are proposed and the cost function is designed:minimum stability margin,energy-saving distribution of tire longitudinal force and minimum tire wear energy consumption;For the full X-by wire intelligent vehicles,the expected trajectory obtained from the trajectory planning layer is known.Because the three evaluation indexes have different emphases in different situations,the fuzzy control method is adopted in this paper to design the self-adaptive weight coefficient adjustment strategy of working conditions;Finally,in order to make each wheel provide the required tire force,this paper designs the control layer of the actuator and calculates the required wheel angle and hub motor torque.（4）To verify the personalized automated lane change system of the full X-by wire electric vehicle,this paper uses the simulation platform of Matlab/Simulink and CarSim to verify the personalized human-like lane change trajectory planning method and the trajectory tracking control strategy of the full X-by wire electric vehicle.The simulation results show that the proposed trajectory planning method can effectively achieve personalized lane change trajectory planning for different drivers.At the same time,the proposed trajectory tracking control method can ensure the trajectory tracking accuracy and improve the performance of the full X-by Wire electric vehicle.